triz methodology of inventive problem solving

How it works

For Business

Join Mind Tools

Article • 8 min read

A Powerful Methodology for Creative Problem Solving

By the Mind Tools Content Team

Projects don't always run smoothly. Even with all the analysis and data you need at your fingertips, sometimes you just can't see a way forward. At times like these, you need to develop creative solutions to the problems you face.

Chances are you already know about brainstorming , which can help with this sort of situation. But brainstorming depends on intuition and the existing knowledge of team members, and its results are often unpredictable and unrepeatable.

TRIZ, however, is a problem-solving philosophy based on logic, data and research, rather than on intuition.

It draws on the past knowledge and ingenuity of thousands of engineers to speed up creative problem solving for project teams. Its approach brings repeatability, predictability and reliability to the problem-solving process and delivers a set of dependable tools.

This article walks you through the essentials of TRIZ.

What is TRIZ?

TRIZ is the Russian acronym for the "Theory of Inventive Problem Solving," an international system of creativity developed in the U.S.S.R. between 1946 and 1985, by engineer and scientist Genrich S. Altshuller and his colleagues.

According to TRIZ, universal principles of creativity form the basis of innovation. TRIZ identifies and codifies these principles, and uses them to make the creative process more predictable.

In other words, whatever problem you're facing, somebody, somewhere, has already solved it (or one very like it). Creative problem solving involves finding that solution and adapting it to your problem.

TRIZ is most useful in roles such as product development, design engineering, and process management. For example, Six Sigma quality improvement processes often make use of TRIZ.

The Key TRIZ Tools

Let's look at two of the central concepts behind TRIZ: generalizing problems and solutions, and eliminating contradictions.

1. Generalizing Problems and Solutions

The primary findings of TRIZ research are as follows:

• Problems and solutions are repeated across industries and sciences. By representing a problem as a "contradiction" (we explore this later in this article), you can predict creative solutions to that problem.
• Patterns of technical evolution tend to repeat themselves across industries and sciences.
• Creative innovations often use scientific effects outside the field where they were developed.

Using TRIZ consists of learning these repeating patterns of problem and solution, understanding the contradictions present in a situation, and developing new methods of using scientific effects.

You then apply the general TRIZ patterns to the specific situation that confronts you, and discover a generalized version of the problem.

Figure 1, below, illustrates this process.

Figure 1 – The TRIZ Problem-Solving Method

Here, you take the specific problem that you face and generalize it to one of the TRIZ general problems. From the TRIZ general problems, you identify the general TRIZ solution you need, and then consider how you can apply it to your specific problem.

The TRIZ databases are actually a collection of "open source" resources compiled by users and aficionados of the system (such as the 40 Principles and 76 Standard Solutions, which we look at, below).

2. Eliminating Contradictions

Another fundamental TRIZ concept is that there are fundamental contradictions at the root of most problems. In many cases, a reliable way to solve a problem is to eliminate these contradictions.

TRIZ recognizes two categories of contradictions:

• The product gets stronger (good), but the weight increases (bad).
• Service is customized to each customer (good), but the service delivery system gets complicated (bad).
• Training is comprehensive (good), but it keeps employees away from their assignments (bad).

The key technical contradictions are summarized in the TRIZ Contradiction Matrix . As with all TRIZ resources, it takes time and study to become familiar with the Contradiction Matrix.

• Software should be complex (to have many features), but simple (to be easy to learn).
• Coffee should be hot (to be enjoyed), but cool (to avoid burning the drinker).
• An umbrella should be large (to keep the rain off), but small (to be maneuverable in a crowd).

You can solve physical contradictions with the TRIZ Separation Principles . These separate your requirements according to basic categories of Space, Time and Scale.

How to Use TRIZ Principles – an Example

Begin to explore TRIZ by applying it to a simple, practical problem.

For example, consider the specific problem of a furniture store in a small building. The store wants to attract customers, so it needs to have its goods on display. But it also needs to have enough storage space to keep a range of products ready for sale.

Using TRIZ, you can establish that the store has a physical contradiction. The furniture needs to be large (to be useful and attractive), but also small (to be stored in as little space as possible). Using TRIZ, the store owners generalize this contradiction into a general problem and apply one of the 40 Principles of Problem Solving – a key TRIZ technique – to it.

They find a viable general solution in Principle 1 – Segmentation. This advocates dividing an object or system into different parts, or making it easy to take apart. This could lead the owners to devise flat-pack versions of their furniture, so that display models can take up the room that they need while inventory occupies much less space per unit. This is the specific solution.

You, too, can use the 40 Principles of Problem Solving, or the 40 Inventive Principles, and the Contradiction Matrix to help you with your problem-solving.

Five Top TRIZ Concepts and Techniques

TRIZ comes with a range of ideas and techniques beyond the basic principles outlined above. Some are conceptual and analytical, such as:

• The Law of Ideality. This states that any system tends to become more reliable throughout its life, through regular improvement.
• Functional Modeling, Analysis and Trimming. TRIZ uses these methods to define problems.
• Locating the Zones of Conflict. (This is known to Six Sigma problem-solvers as " Root Cause Analysis .")

Some are more prescriptive. For example:

• The Laws of Technical Evolution and Technology Forecasting . These categorize technical evolution by demand, function and system.
• The 76 Standard Solutions . These are specific solutions devised to a range of common problems in design and innovation.

You can use one such tool or many to solve a problem, depending on its nature.

TRIZ is a system of creative problem solving, commonly used in engineering and process management. It follows four basic steps:

• Define your specific problem.
• Find the TRIZ generalized problem that matches it.
• Find the generalized solution that solves the generalized problem.
• Adapt the generalized solution to solve your specific problem.

Most problems stem from technical or physical contradictions. Apply one of hundreds of TRIZ principles and laws to eliminate these contradictions, and you can solve the problem.

You've accessed 1 of your 2 free resources.

Get unlimited access

Discover more content

Starbursting.

Understanding New Ideas by Brainstorming Questions

Kano Model Analysis

Delivering Products That Will Delight

Add comment

Comments (0)

Be the first to comment!

Try Mind Tools for free

Get unlimited access to all our career-boosting content and member benefits with our 7-day free trial.

Sign-up to our newsletter

Subscribing to the Mind Tools newsletter will keep you up-to-date with our latest updates and newest resources.

Subscribe now

Business Skills

Personal Development

Leadership and Management

Most Popular

Newest Releases

The Quest For Fewer Interruptions

What Are Your Values?

Mind Tools Store

About Mind Tools Content

Discover something new today

Frederick taylor and scientific management.

Understanding Taylorism and Early Management Theory

What Is Frederick Taylor's Scientific Management Theory?

Applying science to management

How Emotionally Intelligent Are You?

Boosting Your People Skills

Self-Assessment

What's Your Leadership Style?

Learn About the Strengths and Weaknesses of the Way You Like to Lead

Recommended for you

Five moments of learning need.

Increase the Value of Learning Tools By Providing Them When Needed

Business Operations and Process Management

Strategy Tools

Customer Service

Business Ethics and Values

Handling Information and Data

Project Management

Knowledge Management

Self-Development and Goal Setting

Time Management

Presentation Skills

Learning Skills

Career Skills

Communication Skills

Negotiation, Persuasion and Influence

Working With Others

Difficult Conversations

Creativity Tools

Self-Management

Work-Life Balance

Stress Management and Wellbeing

Coaching and Mentoring

Change Management

Team Management

Managing Conflict

Delegation and Empowerment

Performance Management

Leadership Skills

Developing Your Team

Talent Management

Problem Solving

Decision Making

Six Sigma Study Guide

Study notes and guides for Six Sigma certification tests

TRIZ – The Theory of Inventive Problem Solving

Posted by Tanner Zornes

TRIZ is a Russian acronym for The Theory of Inventive Problem Solving. TRIZ began in the 1940s by a soviet engineer named Genrich Altshuller. He recognized that technological advancements follow a systematic and natural progression. As a result, Genrich invented TRIZ, creating common solutions that can be redeployed to business problems for specific improvements. The 40 Principles of TRIZ are like the old idiom, “Don’t reinvent the wheel.” 

In other words, hundreds of really smart inventors have lived before today. TRIZ takes what is already created, adapts, and deploys it to solve today’s problems. Moreover, TRIZ uses tables of inherent contradictions and innovation principles, not trial and error, to reform the design challenge and remove physical contradictions.

• By this point in the DMAIC methodology, you should have a solid understanding of the problem that needs to be solved.
• Find the TRIZ General Problems that match your specific problem
• Identify which general solutions of TRIZ best apply to your specific problem.
• Lastly, apply the general solutions to your specific problem

Applying TRIZ

TRIZ works best in situations where other Six Sigma tools have not worked. Think of it as another way to find solutions that exist outside the normal process boundaries. You could use it during the Improve phase of the Six Sigma technique DMAIC (define, measure, analyze, improve, control) or the design phase of DMADV (define, measure, analyze, design, verify). ( reference )

You are not expected to memorize all 40 principles as part of your Six Sigma preparation. Rather, you should be familiar with each TRIZ principle in order to recognize answers on the exam. With that said, each of the below principles has been paired with a brief explanation and examples.

Principle 1: Segmentation

Divide an object into similar sections to add value to the product.

• Different-sized cutting guards on hair clippers.
• Focal lenses on a camera

Principle 2: Taking Out or Extraction

Take out the unnecessary portions of a product or extract the most necessary portions. As a result, the product becomes streamlined.

• Self-check-in apps for dining-in restaurants (taking out long wait times)
• Music playing in restrooms (without the actual musicians)
• Take out lactose in milk, and the result is an allergy-friendly milk

Principle 3: Local Quality

Adjust item properties to fit user/application requirements.

• Ergonomic keyboards
• Pens with erasable ink

Principle 4: Asymmetry

Modify an object from a balanced state to an uneven state. Though contrary to nature, asymmetry adds value to a variety of products.

• Water bottles (small spout for easy drinking, large base to hold water)
• Pencil Grips

Principle 5: Merging, Consolidation, or Combining

Combine concepts, items, or systems with those of similar properties. Consequently, the objective becomes more lean.

• Printers that can print in color and black and white
• Roofers that put up Christmas lights during the winter season

Principle 6: Universality

Consolidate parts of an object into one singular function. With this in mind, the product receives a wider application of use.

• A tablet compared to a laptop when you are on the go.
• USB drivers verses CDs or floppy disks.

Principle 7: Nested Doll

Similar to Russian nesting dolls, objects fit inside each other. This allows for space consolidation.

• A portable chess set:
• Stackable chairs

Principle 8: Anti-Weight

Offset the weight of an object by combining it with things that provide lift. That is to say, the object has less weight.

• Hot air balloons
• Hydraulic car jacks

Principle 9: Preliminary Anti-action

Implement measures to control harmful actions or consequences DURING a necessary process.

• Cars with vehicle blind spot monitors in order to avoid collisions when changing lanes

Principle 10: Preliminary Action

Perform the required change in ADVANCE. To clarify, the action occurs before a process begins.

• Boxed furniture that contains pre-drilled holes for assembly
• Cell phone notification when power is low, which prevents the phone from dying

Principle 11: Beforehand Cushioning

In cases where there is low consistency, provide a means for cushioning the worse-case scenarios.

• Sprinkler systems in case of fires
• Emergency shut-off switches

Principle 12: Equipotentiality

Solutions that involve a change to an object’s environment enable the desired results compared to a direct change to the object.

• Laundry chute – using gravity to bring your laundry downstairs

Principle 13: The Other Way Around

Do it in reverse or opposite ways, such as drive-thru restaurants vs. sit-in diners.

Principle 14: Spheroidality – Curvature

Introduce a bend or shape to an object. In addition, this includes how the object moves.

• Archways expand the inside of buildings, which allows more room and improved acoustics.
• A drill gun’s motion compared to a hammer’s motion

Principle 15: Dynamics

Change an object or system in order to create optimal flow.

• Pressure valves for gas and liquid control

Principle 16: Partial or Excessive Actions

If optimal performance cannot be achieved, aim for more or less to create the desired effect.

• Using paint primer on an object before the actual painting process

Principle 17: Another Dimension

Take an object from one dimension or plan to two planes. This includes two dimensions to three, or vice versa.

• Spiral staircase compared to normal stairs
• A desk shipped pre-assembled versus assembled in advance.

Principle 18: Mechanical Vibration

Introduce vibration to an object. Though contrary to Six Sigma’s goal to reduce process variation, increased vibration is beneficial under the right circumstances

• Electric toothbrush, which allows for better teeth cleaning compared to a normal toothbrush
• Increased vibration in a foot massage leads to a better stronger massage

Principle 19: Periodic Action

Change a steady action to occur in intervals. This allows users to increase or decrease magnitude during the process.

• Lights and sirens on a fire truck notify other cars to move
• Spring-loaded nerf guns

Principle 20: Continuity of Useful Action

Continuous flow of a process or object. This can also include eliminating idle objects.

• Dams use falling water, thus generating electricity.
• Crossfit exercise routines, which consequently create a more complete workout.

Principle 21: Skipping or Rushing Through

Conduct at-risk or harmful stages at high speeds in order to avoid extra damage.

• Friction can heat up an object, which leads to warped material. Faster cutting speeds prevent more warping.

Principle 22: Blessing in Disguise – Harm into Benefit

Make the most out of harmful factors in order to create a positive effect.

• Composting, such as tossing egg shells into a garden to improve soil quality
• Rebuilding infrastructure after natural disasters

Principle 23: Feedback

Add performance data to a process or object. A Six Sigma example of feedback is Statistical Process Control .

• Automated survey inquiries allow people to receive quick feedback from customers.
• Audiovisuals on the TV so that viewers can know the TV volume

Principle 24: Intermediary/Mediator

Use an intermediary vehicle or process. In other words, using someone or something as a link between two processes.

• Using email in order to distribute communication to a group of people
• US Postal Services, which ships goods or letters between people
• Food processors so that people without teeth can eat, too!

Principle 25: Self-Service

An object or process that services itself or provides auxiliary assistance.

• Automated phone call screening so that callers are connected to the correct department.
• Car wash stations that include self-vacuum stations so that customers can clean inside and outside of their car!

Principle 26: Copying

Use less expensive material that is more accessible to replace expensive and less available parts.

• 3-D Printing
• Replacing metal components with high durable plastic ones

Principle 27: Cheap Short-Living Objects

Replace expensive, quality objects with multiple cheaper objects. This leads to a compromise on certain quality aspects, but provides lower costs.

• Glass plates and cups are nice until you need to wash them. However, paper plates and cups can be thrown away after use
• Washable diapers are cheaper compared to disposable diapers, but single-use diapers are more easy to use

Principle 28: Mechanics Substitution

Replace a mechanical system with an electronic, sensory, or chemical system.

• Dictation or saying words aloud to be typed compared to typing it out by hand
• A car fob can unlock the viable faster than using the car key slot

Principle 29: Pneumatics and Hydraulics

Use gas or liquid parts instead of solid parts.

• Hydraulic brakes compared to standard brakes
• Gel-filled insoles in shoes provide better foot support compared to standard insoles

Principle 30: Flexible Shells and Thin Films

Use flexible materials that are more durable, lighter, and cost effective. 

• Bullet-proof vests are made out of light-weight material called kevlar, which is better than heavy metal for firearm safety
• Bubble wrap is great for shipping goods because of its extra cushioning

Principle 31: Porous Materials

Add holes (pores) to an object. This leads to a lighter and less dense object.

• Homes that use fiberglass for insulation
• Sponges to absorb moisture

Principle 32: Color Changes

Change the color of an object or the color around the object.

• Camouflage, which allows users to blend in to their environment
• Lighter colored homes reduce heat absorption from the sun.

Principle 33: Homogeneity

The interaction of two or more objects of the same material or purpose.

• Blood transfusions only work if the user has the same blood type as the donor
• Wooden dowels to join pieces of wood together

Principle 34: Rejecting, Discarding – Recovering, Regeneration

Reject or discard the object after completion or recover it after completion.

• SpaceEx launch spacecraft and the rocket returns to the launch pad after ascent. As a result, the cost of space travel is reduced
• Climbing the career ladder by changing jobs

Principle 35: Parameter Changes

Includes any input/output change such as temperature, durability, or pressure. Lots of things can fit in this bucket!

• Move into a larger work space in order to increase output
• Cakes batter baked at a lower temperature makes a better cake

Principle 36: Phase Transitions

Gradual changes to certain specs such as volume or pressure.

• Switching gears in a vehicle, which reduces gas consumption
• Move objects to cooler temperatures such as a fridge to decrease its heat

Principle 37: Thermal Expansions

Use heat or pressure in order to achieve desired results.

• Use heat to expand pipes so that they can connect. Cool pipes to cement them

Principle 38: Accelerated Oxidation

Replace common air with oxygen rich air.

• Ventilators assist to treat patients that struggle to breath
• Oxygen rich air is better fuel for fire, which can be applied during heat treatment

Principle 39: Inert Atmosphere

Negate moving or changing settings with less mobile or chemically inactive spaces

• Fire extinguishers work to move oxygen way from the flames. This results in putting out the fire
• Vacuum sealed bags are great space savers because the air is taken out of the object

Principle 40: Composite Materials

Unlike principle 5, composite materials combine different types of materials together.

• The body of an aircrafts is made of metals, foam, plastics, kevlar, and more. The principle also applies to the insides of vehicles.

IASSC Green Belt Sample Question

Question: Which of the following ideas best follows the TRIZ principle of “The Other Way Around?”

(A) Using hydraulic technology over gas-powered equipment

(B) Utilizing a trash compactor to maximize tonnage per pickup

(C) Baking cookies at a higher temperature

(D) Escalators in an airport or mall

Unlock Additional Members-only Content!

Thank you for being a member.

D: “The Other Way Around” (Principle 13) refers to the opposite way of doing something. Stairs requires people to move in a stationary environment whereas escalators create a moving environment while the people remain stationary.

Additional Resources

https://www.aitriz.org/articles/40p_triz.pdf – This is a great book extract for anyone who wants to practice TRIZ.

Comments (1)

MODIFIER program is based on ARIZ, TRIZ tools (algorithmized method of finding innovative solutions) essentially an electronic guide to the stages of the search workflow solutions of inventive problems. Designed for learning and mastering (by examples) data techniques, as well as for further independent work on the search innovative solutions (the language in one version is Russian, in the other – English). Added 4 more PROGRAMS. “MODIFIER” program (version 1.7): https://b-b.by/modules/tr/mco_eng.htm

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed .

Insert/edit link

Enter the destination URL

Or link to existing content

• Memberships

TRIZ Method of Problem Solving explained

TRIZ Method of Problem Solving: this article explains the TRIZ Method of Problem Solving , developed by Genrich Altshuller in a practical way. Next to what it is, this article also highlights the founder, the reason of it’s excistenc, and the five basic principles and the 40 principles including practical examples. After reading you will understand the basics of this powerful problem solving tool. Enjoy reading!

What is TRIZ Method of Problem Solving?

In the 1980s the Russian engineer Genrich Altshuller developed the TRIZ theory which is an acronym for Teorya Resheniya Izobreatatelskikh Zadatch . The literal translation is: “theory of inventive problem solving” .

The most important result of the research was, that the evolution of technological progress follows a number of predictable patterns. It is an innovative way of looking at problems and solutions.

TRIZ Method of Problem Solving is not a coincidence

As a patent examiner Altshuller refused to accept the fact that inventions and creativity were random or chance acts.

His goal was to develop a standard process for successful innovations. This is how he discovered that 98% of patented innovations were based on an already known principle. Only 2% of all patents were really new innovations.

The TRIZ Method is universally applicable!

TRIZ starts from a number of principles and processes of innovation that are universally applicable. Large multinationals such as Hewlett-Packard , Boeing and Samsung have used the TRIZ method to develop new products, optimize processes and gaining a better understanding of developments and trends in the market for decades.

TRIZ has become an umbrella that covers a host of inventive concepts, tools and processes that are often used to solve difficult problems.

The TRIZ Method of Problem Solving: the basic principles

To arrive at improvement, the TRIZ method uses 5 basic principles and 40 inventive principles. It forces us to look at problems differently.

1. The ideal end result

Thinking out of the box is a good principle to achieve an ideal end result. The TRIZ Method of Problem Solving encourages people not to be satisfied too quickly with the solutions to a problem, but to be always open to even better ideas.

2. Less is more

There is not always a need to invest a lot of money to arrive at the best idea. Innovation can be realized with existing materials and sometimes the solution is close at hand.

3. Solutions already exist

The TRIZ Method of Problem Solving helps people define problems in terms of frequently used and general principles, which enables searching for solutions outside their primary field of expertise.

4. Search for fundamental contradictions

Innovating equals problem solving, which mostly exist of contradictions. When these contradictions are defined, the solution is often imminent.

5. Lines of evolution

Systems do not evolve randomly. There are fixed patterns that make the evolution of technology predictable,

The TRIZ method 40 inventive principles

Genrich Altshuller arrived at 40 inventive principles to solve complex problems. According to the TRIZ Method of Problem Solving, each innovation can be traced back to the application of one or more of these principles.

To arrive at the right application of the 40 inventive principles, it is important to formulate the right contradiction very clearly with respect to what should be improved and what should not get worse.

After this, the problem solving process can be started up.

1. Segmentation

Segment the product into independent parts as a result of which a useful or damaging quality is isolated (shop in shop).

2. Extraction

Extract a disturbing part or property from an object and/or single out the only necessary part or property (sugar free biscuits).

3. Local quality

By changing the structure of products in a specific place, the desired product is created (cap on milk carton).

4. Asymmetry

Change the shape an object from symmetrical to asymmetrical (trendy kettle).

By merging functions, properties or parts of a product in space or time, a new or unique result is created (day cream with UV filters).

6. Universality

Make a product more uniform, universal, extensive and multi-functional (hair-dryer).

7. Nested doll

Place multiple objects inside others (paper insulated coffee cups).

8. Counterweight

Compensate the negative property of the product by combining it with another object that provides a lifting force (hovercraft).

9. Preliminary counteraction

Analyse beforehand what can go wrong and take preliminary counteraction (sun milk).

10. Preliminary Action

Place object before it is needed so that it can go into action immediately from the most convenient location for their delivery (Emla numbing cream).

11. Cushion in advance

Because nothing is perfectly reliable, prepare emergency measures in advance (metallic car coating – anti-contamination).

12. Equipotentiality

Eliminate tension in or around an object’s environment (cling film).

13. The other way round

Implement an opposite or reverse action (reversible clothing).

14. Spheroidality

Replace linear parts with spherical parts (round brush head for hoover).

15. Dynamics

Make a product or property temporarily flexible or flexible for a short while (possibility to buy a car with unique stripes).

16. Partial or excessive actions

Use a little more than necessary or use a little less of the same product (high active enzymes in laundry detergents).

17. Transition into another dimension

Change the orientation of a linear product from vertical to horizontal etc. Use a different dimension or multi-storey arrangement (layered cake).

18. Mechanical vibrations

Use vibrations to achieve a positive effect (massage cushion).

19. Periodic Action

Instead of continuous actions use periodical or pulsating actions (electric toothbrush).

20. Continuity

Carry on work continuously and eliminate all idle or intermittent actions (boarding pass such as e-tickets).

21. Rushing through

Conduct a process at high speed to prevent errors (DSL internet versus fibre optic internet).

22. Blessing in disguise

Use harmful factors to add value. (3M yellow post-its with low tack adhesive).

23. Feedback

Introduce feedback by using output as a means of input, output audits can be improved (telephone number of service desk on packaging).

24. Intermediary

Merge one object temporarily with another (oven bag for cooking chicken).

25. Self-service

Make an object serve itself by performing auxiliary helpful functions (self-checkout at supermarkets).

26. Copying

Instead of a valuable or fragile object, use inexpensive copies (zirconia jewellery).

27. Cheap objects

Use inexpensive and/or disposable objects to reduce costs (disposable cutlery).

28. Replace mechanical system

Replace a mechanical system with a different shape, action or function (folding electric bikes).

29. Pneumatics and hydraulics

Replace solid parts of an object with pneumatic (air) or hydraulic (water) parts (barber chair).

30. Flexible shells

Replace traditional constructions with flexible shells (water repellent, breathable sports clothing).

31. Porous materials

Make properties of objects, systems or materials porous (read-to-use iodine band-aid).

32. Colour changes

Change the colour or other optical property of an object (Polaroid sunglasses).

33. Homogeneity

Make objects interact with a given object with identical properties (two-component adhesive).

34. Discarding and recovering

By making objects or parts of objects that have fulfilled their usefulness go away and by subsequently restoring them, they can be reused.(reusable make-up packaging)

35. Parameter changes

Change the properties of an object (steam shower).

36. Phase transitions

Use phenomena occurring during chemical phase transitions (pregnancy test).

37. Thermal expansion

Convert heat energy to mechanical energy (solar panels).

38. Strong oxidants

Reinforce oxidative processes to enhance a function or process (cryotherapy for warts).

39. Inert atmosphere

Replace a neutral environment to support a desired function (vacuum wine saver pump).

40. Composite materials

Change from homogeneous to composite materials (thermos flask).

The TRIZ Method of Problem Solving is all about Creativity

The TRIZ Method of Problem Solving stimulates creativity and the 40 inventive principles could inspire product development. Compare the TRIZ method to a brainstorming session in which participants are encouraged to emerge with ideas. The effects of the session are limited because only those attending the session make creative contributions.

It’s Your Turn

What do you think? Is the TRIZ Method of Problem Solving still applicable in today’s business companies? And if so, how do you use it and what are the general results and learning lessons? Are the basics principles the same or are there new ones?

Share your experience and knowledge in the comments box below.

More information

• Altshuller, G. , Shulyak, L., & Rodman, S. (2002). 40 Principles Extended Edition: Triz Keys to Technical Innovation . Technical Innovation Center, Inc.
• Altshuller, G. , & Shulyak, L. (1996). And Suddenly the Inventor Appeared: Triz, the Theory of Inventive Problem Solving . Technical Innovation Center, Inc.
• Chen, J. L., & Liu, C. C. (2001). An eco-innovative design approach incorporating the TRIZ method without contradiction analysis . The Journal of Sustainable Product Design, 1(4), 263-272.

How to cite this article: Mulder, P. (2016). TRIZ Method . Retrieved [insert date] from ToolsHero: https://www.toolshero.com/problem-solving/triz-method/

Published on: 12/09/2016 | Last update: 12/23/2023

Add a link to this page on your website: <a href=”https://www.toolshero.com/problem-solving/triz-method/”>Toolshero: TRIZ Method</a>

Did you find this article interesting?

Your rating is more than welcome or share this article via Social media!

Average rating 5 / 5. Vote count: 42

No votes so far! Be the first to rate this post.

We are sorry that this post was not useful for you!

Let us improve this post!

Tell us how we can improve this post?

Patty Mulder

Patty Mulder is an Dutch expert on Management Skills, Personal Effectiveness and Business Communication. She is also a Content writer, Business Coach and Company Trainer and lives in the Netherlands (Europe). Note: all her articles are written in Dutch and we translated her articles to English!

Related ARTICLES

Charles Kepner biography and books

Eight Dimensions of Quality by David Garvin

Measurement System Analysis (MSA)

Agile Crystal Method explained

Philip Crosby biography, quotes and books

Zero Defects philosophy by Philip Crosby

Also interesting.

Systematic Inventive Thinking (SIT)

CATWOE Analysis: theory and example

Means End Analysis: the basics and example

3 responses to “triz method of problem solving explained”.

Congratulations! An excellent article! Very well built! Once again Congratulations! Teach “Innovation Management in Education at the Christian University” Dimitrie Cantemir, Bucharest, Romania. In the course support we included a dedicated TRIZ module. Sincerely, Univ. Lecturer. Remus CHINA

This is really good article and would like to learn more. Looks very much useful in our industry.

Thank you for your comment, Bala Krishna.

Leave a Reply Cancel reply

You must be logged in to post a comment.

BOOST YOUR SKILLS

Toolshero supports people worldwide ( 10+ million visitors from 100+ countries ) to empower themselves through an easily accessible and high-quality learning platform for personal and professional development.

By making access to scientific knowledge simple and affordable, self-development becomes attainable for everyone, including you! Join our learning platform and boost your skills with Toolshero.

POPULAR TOPICS

• Change Management
• Marketing Theories
• Problem Solving Theories
• Psychology Theories

ABOUT TOOLSHERO

• Free Toolshero e-book
• Memberships & Pricing

TRIZ Inventive Problem Solving

Is your company interested in improving its products, services, and systems but not sure where to start? It is very likely that a solution to your problem has already been discovered by another industry somewhere in the world.

Many of the most innovative companies worldwide apply TRIZ inventive problem-solving methods to innovate their products as well as their processes. TRIZ (pronounced “( / ˈ t r iː z / ”) is a Russian acronym that translates to “theory of the resolution of invention-related tasks” and is “a problem-solving, analysis and forecasting tool derived from the study of patterns of invention in the global patent literature.”

History of TRIZ

TRIZ was first developed over 50 years ago by Russian inventor, Genrich Altshuller, and his colleagues. The team studied hundreds of thousands of published patents to discover patterns in the solutions and also the characteristics of the problems overcome.

The research found that problems and solutions repeated across industries and sciences. It also found that innovations often use scientific effects from outside the field in which they were developed. Somebody in a different industry or space has probably already solved your problem, or one very similar to it. TRIZ helps discover that solution and how to creatively apply it to your current problem.

This post will demonstrate how to use several of the key elements in the basic TRIZ inventive problem-solving process. This includes the contradictions matrix and the 40 Principles of TRIZ. We will share the 4-step TRIZ process and also demonstrate it with an example.

TRIZ process

TRIZ draws on the past ingenuity of many thousands of engineers and inventors to accelerate a project team’s ability to solve problems creatively. The TRIZ patent study found that inventive solutions either eliminate or resolve a contradiction without requiring a trade-off.

The 4-step procedure for TRIZ is:

• Define your problem(s). Be sure to consider the problem from the user’s point of view.
• Formulate a conflict statement with the contradictions identified: What we want to improve . . . but not at the expense of . . .
• The contradictions matrix will point to 3 or 4 of the 40 Inventive Principles of TRIZ to consider. Read the example below for more information on using these principles.
• Study these 3-4 relevant Inventive Principles and brainstorm which of the principles can apply to your problem. In this step, think like a detective. A good solution will likely come from one of the principles. Then, move forward and test the top solution .

TRIZ Example

An automotive company had a product innovation need related to the gas cap, so they brought a team together and used TRIZ to develop an innovative solution.

First, generate a problem statement : Multiple customer complaints state that gas caps are hard to install, easy to forget, make your hands smell like gas, and make the check engine light appear if not properly closed.

Next, generate a conflict statement : We want to make it easy to add gas to the automobile but not at the expense of safety and functionality .

Then, go to the contradictions matrix and select the contradictions from the list of 39 that best fit the conflict statement. We recommend an online resource rather than a complex paper-based matrix .

Now, set the contradictions. First, the feature to improve. Next, the feature to preserve. Feel free to try several options as it takes some getting used to. Here is an example of how we narrowed down our Inventive Principles for a focus:

The Contradictions Matrix points to these Inventive Principles based on the contradictions above:

Finally, expand the 3-4 Inventive Principles and brainstorm solutions. In this case, Principles 2 and 25 provided helpful ideas. When we “ single out the only necessary part (or property) of an object, ” we realize that the only function of the gas cap is to seal the gas tank filling port. So, we ask ourselves, can this be done without the cap?

Another clue came from Principle 25:

Can we “ make an object serve itself by performing auxiliary helpful functions ”?

The solution (we believe first implemented by Ford) was to use a spring-loaded flap in the fill nozzle. The flap seals the fuel tank in place of the gas cap!

We hope this simple example shows how to use the TRIZ inventive problem-solving methods to innovate. The method will support product, process, and system improvements. Some principles are fairly technical (e.g. dealing with material properties) and engineering-focused. You can review all 40 TRIZ Principles here .

TRIZ as a Competitive Advantage

It’s hard to gauge the popularity of TRIZ because it is believed that many companies do not share their use of the method. They prefer to keep it as a trade secret. However, some companies have reported use of TRIZ problem-solving methods including General Electric, Rolls-Royce, BAE Systems, NASA, Siemens, Ford, General Motors, Procter & Gamble, BMW, and Apple.

Samsung invested heavily in embedding TRIZ use throughout the company, training multiple employees and even the CEO. “ In 2003 TRIZ led to 50 new patents for Samsung and in 2004 one project alone, a DVD pick-up innovation, saved Samsung over $100 million. TRIZ is now an obligatory skill set if you want to advance within Samsung. ”

We love to help local innovators study their problems and apply TRIZ methodology to develop solutions. If you are in the New England region please connect with Lean East privately to discuss your challenge and see how TRIZ can help you discover an innovative solution.

Now go and use TRIZ to help invent something!

One thought on “ TRIZ Inventive Problem Solving ”

Read all the comments on the web about what goes wrong with this system and what an irritation it is to repair. This is not a good TRIZ example without also considering the failure analysis aspects of TRIZ.

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Related Posts

Leveraging Generational Differences in the Workplace

This Is More Important Than An Original Idea

Achieve Better Results with Elon Musk’s Five Step Improvement Process

Receive our lean east newsletter.

First Name -->

Select your industry: Healthcare related Manufacturing All other services

Our website uses cookies to improve and personalize your experience. Our website may also include cookies from third parties like Google Analytics. By using the website, you consent to the use of cookies. Please check our Privacy Policy at the bottom of the page.

TRIZ: Exploring the Revolutionary Theory of Inventive Problem Solving

The Theory of Inventive Problem Solving, known as TRIZ, is an insightful methodology developed for systematically approaching innovation and complex problem-solving. Its foundations are deeply rooted in empirical data, gathered from the analysis of thousands of patents to discern patterns that can forecast the direction of future technological advancement. The relevance of TRIZ in today's fast-paced and innovation-driven business realm cannot be overstated.

By equipping professionals with a structured framework for understanding and addressing challenges, TRIZ fosters an environment where creativity and efficiency thrive. As businesses continue to seek differentiation through innovation, TRIZ stands out as a potent tool for transforming the very nature of problems into tangible opportunities for growth and development.

History and Development of TRIZ

Origin and creator of triz.

TRIZ was conceived in the mid-20th century by Soviet inventor and science fiction writer Genrich Altshuller. His epiphany occurred during his tenure at a patent office, where he recognized common themes among numerous inventions that could potentially inspire innovation across various fields.

Altshuller posited that creativity could be codified into a repeatable and systematic process rather than remaining the seemingly mystical result of sporadic genius.

Evolution and Adaptation of TRIZ Over the Years

Since its inception, TRIZ has evolved through continual refinement and practical application, expanding far beyond its original roots within engineering disciplines. Altshuller's initial work has been substantiated and expanded upon by a growing community of thinkers and practitioners who have extended its applicability to diverse sectors including business management, software development, and even social sciences.

Global Acceptance and Implementation of TRIZ in Different Sectors

The relevance of TRIZ is not confined by geographic boundaries. It has been globally recognized and implemented in organizations as they realize its potential to tangibly enhance their innovation capacities. From the automotive industry to consumer electronics giants, TRIZ has transcended cultural and industrial barriers to become a cornerstone of modern inventive thinking and strategic planning.

Plato's Problem Solving: Doing the Right Thing

Pareto Chart: A Powerful Tool for Data Analysis and Decision-Making

Quality Improvement: Strategies, Principles, and Impact on Business Success

Failure Mode, Effects, and Criticality Analysis (FMECA): A Comprehensive Guide

Basic Principles of TRIZ

The 40 inventive principles and their application.

One of the core components of TRIZ is the 40 inventive principles, a set of general tactics for overcoming technical contradictions through novel approaches. For instance, the principle of segmentation — breaking a problem down into its parts — has led to advancements in modular design, wherein components can be replaced or upgraded individually without necessitating the redesign of the entire system.

The Contradiction Matrix and Its Usage

Another pivotal element of TRIZ is the contradiction matrix, which provides strategic recommendations for resolving specific problems without compromising other parameters. It essentially bridges the gap between different inventive principles and the particular characteristics of a problem, guiding the user towards plausible solutions that would otherwise require considerable time and effort to devise.

The Ideality and System Evolution Principles

The principle of ideality presses the visionary pursuit of an ideal final result — a solution that demands no resources yet delivers maximized benefits. Alongside this, the system evolution principles chart a path for the progressive development of a technological system through various stages, predicting and leveraging the natural progression of technical systems over time.

The TRIZ Process

Understanding the problem and collecting data.

The initial step in applying TRIZ involves a comprehensive understanding of the problem at hand, which requires meticulous data collection and analysis. Identifying the true nature of the problem rather than its superficial symptoms is critical to direct efforts effectively and to ensure that solutions are both relevant and sustainable.

Analyzing the Problem Through TRIZ Tools

Using TRIZ tools to analyze the problem enables users to reframe challenges in non-standard ways, facilitating fresh perspectives and unexpectedly effective solutions. It involves the strategic deconstruction of the problem into its fundamental components, scrutinizing them through the lens of TRIZ's inventive principles and contradiction matrix.

Developing and Implementing a Solution Using TRIZ Principles

The actual creation and implementation of a solution following the TRIZ framework require iterative prototyping, systematic validation, and refinement. Employing TRIZ principles empowers practitioners to ideate and invent with prowess and precision, often leading to groundbreaking solutions that redefine the market landscape.

Advantages of Applying TRIZ

Improving efficiency and effectiveness in problem solving.

The application of TRIZ significantly augments problem-solving efficiency and effectiveness by offering a structured approach that accelerates the innovation process. This often results in reduced development times and costs, as well as breakthroughs that can create competitive advantages.

Encouraging Innovation and Creativity in Organizations

A notable advantage of TRIZ is its ability to encourage continual innovation and creativity within organizations. TRIZ provides a concrete framework for channeling creative energies more productively, potentially fostering an organizational culture that consistently aspires to innovate.

Case Study to Exemplify the Benefits of TRIZ

A case study illustrating the benefits of TRIZ can be seen in the example of a manufacturing firm that applied the theory to redesign a problematic product assembly line. By identifying and resolving contradictions in the process, the firm was able to both enhance the product quality and increase the assembly line speed, which subsequently led to heightened customer satisfaction and market share growth.

TRIZ in Real-world Scenarios

Implementation of triz in various industries with examples.

Across various industries, the implementation of TRIZ has led to the resolution of long-standing issues that were believed to be impervious to improvement. For instance, in the automotive industry, TRIZ has been instrumental in reconciling conflicting goals of reducing vehicle weight while maintaining structural integrity, thereby advancing both fuel economy and safety standards.

How TRIZ is Transforming Traditional Problem-Solving Methods

Traditional problem-solving methods often rely on trial-and-error tactics or incremental improvements. In contrast, TRIZ advocates for a radical re-envisioning of problems that paves the way for inventive solutions, transforming problem-solving into a systematic, foresighted endeavor.

Limitations and Criticism of TRIZ

Possible pitfalls and limitations of triz.

Although TRIZ presents an array of advantages, it also has its limitations. The complexity and abstract nature of some of its principles can occasionally render it inaccessible or overly challenging for newcomers without proper problem solving skills training .

Criticism and Contrarian Views on TRIZ’s Effectiveness

Some critics argue that TRIZ's heavy reliance on past inventions limits its capacity to predict truly novel innovations. As a reaction, contrarian viewpoints often advocate for a more eclectic or integrated approach to innovation that merges TRIZ with other methodologies.

Recap of Key Points Discussed About TRIZ

TRIZ is a methodological beacon in the realm of inventive problem-solving that systematically enhances an organization's ability to innovate. By dissecting the historical landscape of inventions and distilling repeatable patterns of problem-solving, TRIZ enables businesses to ingeniously tackle challenges that might otherwise stifle progress.

The Future Potential of TRIZ in the Context of the Rapidly Changing Business Environment

As businesses continue to grapple with the unending flux of technological advancements and market dynamics, TRIZ is poised to gain even greater significance. Professionals possessing mastery of TRIZ principles, potentially fortified through online certificate courses , are well-equipped to lead the charge in an era defined by incessant innovation and transformation.

Final Thoughts and Areas for Further Exploration in TRIZ

Continuous exploration in the field of TRIZ, including the development of digital tools and the integration of machine learning algorithms, can expand its utility even further. By embracing both the rich legacy and potential evolution of TRIZ, practitioners and organizations can unlock a profound capacity for inventive and evolutionary change.

What are the basic principles underlying the TRIZ approach to problem-solving and innovation?

Triz fundamentals.

TRIZ stands for the Theory of Inventive Problem Solving . It hails from Russia. Genrich Altshuller developed it. He based TRIZ on extensive patent analysis. His goal was to universalize invention. How? By identifying patterns in problems and solutions.

Principles at the Core

TRIZ rests on several key principles. We'll explore these briefly.

Contradictions Foster Innovation

Problems often involve contradictions. That is, conflicting requirements or desires. TRIZ aims to resolve these directly. It doesn't settle for compromises. Instead, it seeks novel solutions.

Patterns of Technological Evolution Exist

Inventions follow predictable paths. These are patterns. TRIZ provides a roadmap. This roadmap helps innovators forecast and plan.

Creativity Can Be Systemic

Inspiration isn't always spontaneous. TRIZ offers a structured approach. This guides creativity. It makes innovation more predictable.

Ideal Final Result

Imagine a perfect solution. It requires no resources. Yet, it delivers functionality. TRIZ encourages such forward-thinking. It's the ideal final result.

Resources Are Everywhere

Look around. Every element has potential. TRIZ teaches us to use available resources. Think waste products or energy. They can solve problems.

Inventive Principles

Forty principles guide problem-solving in TRIZ. They offer strategies. You can overcome technical contradictions with these.

Standardized Approaches

TRIZ has standard solutions. These tackle common problems. They're based on past inventions. Why reinvent the wheel?

Function Analysis

Understand the problem fully. Analyze all functions and interactions. This is part of the TRIZ methodology.

Knowledge and Information Tools

TRIZ includes tools and methods. Examples are ARIZ and Algorithm of Inventive Problem Solving. They structure the problem-solving process.

Application of TRIZ

So, how does one apply TRIZ? First, define the problem. Identify the contradictions. Then, analyze the system. Seek the ideal final result. Utilize resources wisely. Apply inventive principles. And, use the knowledge tools.

Example in Action

Consider an overfilled teapot. The problem? It drips when poured. The contradiction? A full pot but no drips. TRIZ would analyze functions. Spout design may be key. Apply inventive principles. Perhaps altering the spout's shape. Use a knowledge tool to guide the redesign. Thus, solve the problem systematically.

TRIZ offers a robust framework. It shifts perspective on problem-solving. With its structured approach, TRIZ makes innovation less daunting. It nurtures creativity systematically. And it offers a strategy for overcoming obstacles to invention and development.

How can the TRIZ methodology be effectively applied to different industries to enhance innovation and problem-solving?

Understanding triz.

TRIZ stands for Teoriya Resheniya Izobretatelskikh Zadatch . It means Theory of Inventive Problem Solving. Genrich Altshuller developed it. He hoped to streamline innovation. Researchers and engineers often rely on TRIZ. It provides a systematic approach. This simplifies complex problems.

TRIZ Across Industries

TRIZ transcends industrial boundaries. It adapts to various fields. For instance, it applies to manufacturing, software development, and even healthcare. Each industry has unique challenges. Yet, TRIZ offers a universal toolkit. It fosters creative problem-solving.

Manufacturing

In manufacturing, efficiency is key. Time equals money. Delays can be costly. Workers need quick, innovative solutions. TRIZ brings structure to their creativity. It helps them identify and solve problems fast.

Software Development

Software development deals with abstract complications. Bugs and user experience issues abound. TRIZ assists by categorizing problems. It highlights contradictions. Developers thus find novel solutions.

In healthcare, patient safety is paramount. Yet resources often remain limited. TRIZ equips practitioners with strategies. They can innovate within constraints. Life-saving techniques often emerge.

Applying TRIZ Effectively

Applying TRIZ involves understanding its principles. There are 40 inventive principles. There are also contradiction tables and patterns of evolution. These are essential TRIZ tools.

Initial Assessment

Know your problem. TRIZ starts with clear problem identification. One cannot solve a vague issue.

Contradiction Analysis

Identify contradictions. Problems often have conflicting requirements. TRIZ helps to manage these.

Ideality and Resources

Focus on ideality. TRIZ promotes the ideal solution. Yet it considers available resources. Balance is crucial.

Using TRIZ Tools

Master the tools. The 40 principles guide the thought process. Contradiction tables clarify conflicts. Patterns of evolution predict industry changes.

The TRIZ Process in Action

Consider an assembly line issue. There's a need for speed without sacrificing quality. This is a classic contradiction. TRIZ principles offer solutions. One might separate the conflicting parts. Perhaps improve one without harming the other.

TRIZ remains versatile and effective. It adapts to diverse industries. It simplifies complex problems. Companies can thus foster innovation. Efficiency follows. TRIZ may well be a universal tool. It facilitates breakthroughs across various sectors. Innovation thrives with structured problem-solving.

How does the TRIZ approach challenge traditional thinking and redefine creative problem-solving strategies?

Triz transforms conventional problem-solving.

Traditional thinking often takes linear paths. Solutions build on known methods. Challenges look unique and isolated. Familiar strategies dominate the process. Yet, contradictions often block innovation. Complexity further complicates matters. Specialists work within narrow fields. TRIZ disrupts these patterns.

Embracing Systematic Innovation

TRIZ stands for Theory of Inventive Problem Solving . Genrich Altshuller developed it. He studied patents extensively. Patterns emerged from his analysis. Innovations followed identifiable principles. TRIZ encapsulates these into a structured methodology. It offers tools and concepts not found in conventional practice.

Overcoming Psychological Inertia

Psychological inertia stifles creativity. People repeat known patterns. Familiarity breeds comfort. TRIZ challenges this comfort. It pushes users to explore unfamiliar territory. The approach shakes up entrenched habits. By doing so, it opens up new avenues for solving problems.

Solving Problems with Patterns

Patterns underpin TRIZ philosophy. Every problem has a potential solution known elsewhere. TRIZ maps these patterns in problem spaces. Innovation becomes a matter of finding the right pattern. Knowledge transfer between domains flourishes.

Contradictions as Creative Fuel

Traditional thinking discourages contradictions. TRIZ, conversely, welcomes them. Contradictions signify opportunities for breakthroughs. Identifying and resolving them drives innovation. TRIZ provides specific principles for turning contradictions into advantages.

Predictive Problem-Solving

TRIZ enables predictive problem-solving. Trends of system evolution form its backbone. Designers and engineers anticipate problems and solutions. Future challenges become less daunting. TRIZ guides users to evolve their systems proactively.

System-Oriented Approach

TRIZ adopts a holistic viewpoint. It sees products as systems. These systems interact with other systems. Optimization thus involves the complete ecosystem. This perspective moves beyond isolated fixes. Sustainable solutions emerge as a result.

Knowledge Democratization

TRIZ democratizes problem-solving. It treats innovation as a skill that can be taught. Complex problems no longer require exclusive expertise. With TRIZ, diverse teams tackle sophisticated dilemmas. Knowledge sharing is integral to this process.

Multi-Level Problem Solving

Different problems demand different solutions. TRIZ acknowledges this with multi-level strategies. Surface-level issues receive simple fixes. Deep-rooted problems undergo thorough analysis. Multiple aspects of a problem get attention simultaneously.

Leveraging Resources

Resources often seem limited in traditional thinking. TRIZ turns every element of a system into a potential resource. Nothing is inconsequential. Hidden opportunities present themselves. Users tap into underutilized assets within their environment.

TRIZ redefines creativity in problem-solving. It challenges norms and fosters systematic innovation. This approach empowers individuals to transcend their cognitive and professional constraints. Consequently, TRIZ equips organizations to navigate the complexities of modern challenges efficiently.

He is a content producer who specializes in blog content. He has a master's degree in business administration and he lives in the Netherlands.

Game Theory: Strategic Analysis and Practical Applications

Lateral Thinking for Problem-Solving: Find the Haystack!

Unlocking Da Vinci's Problem Solving Skills

Critical Path Method (CPM): An Advanced Project Management Strategy

• ASQ® CQA Exam
• ASQ® CQE Exam
• ASQ® CSQP Exam
• ASQ® CSSYB Exam
• ASQ® CSSGB Exam
• ASQ® CSSBB Exam
• ASQ® CMQ/OE Exam
• ASQ® CQT Exam
• ASQ® CQPA Exam
• ASQ® CQIA Exam
• 7 Quality Tools
• Quality Gurus
• ISO 9001:2015
• Quality Cost
• Six Sigma Basics
• Risk Management
• Lean Manufacturing
• Design of Experiments
• Quality Acronyms
• Quality Awareness
• Quality Circles
• Acceptance Sampling
• Measurement System
• APQP + PPAP
• GD&T Symbols
• Project Quality (PMP)
• Full List of Quizzes >>
• Reliability Engineering
• Statistics with Excel
• Statistics with Minitab
• Multiple Regression
• Quality Function Deployment
• Benchmarking
• Statistical Process Control
• Quality Talks >> New
• Six Sigma White Belt
• Six Sigma Yellow Belt
• Six Sigma Green Belt
• Six Sigma Black Belt
• Minitab 17 for Six Sigma
• Casio fx-991MS Calculator
• CSSYB/LSSYB Mock Exam
• CSSGB/LSSGB Mock Exam
• CSSBB/LSSBB Mock Exam
• ASQ® CQA Preparation
• ASQ® CQE Preparation
• ASQ® CQPA Preparation
• ASQ® CQIA Preparation
• CQE Mock Exams
• CMQ/OE Mock Exams
• CQA Mock Exams
• CQIA Mock Exams
• CQPA Mock Exam
• CQT Mock Exam
• CQI Mock Exam
• CSQP Mock Exam
• Design of Experiments (DoE)
• Measurement System Analysis
• Statistics Using R
• Data Visualization with R
• Statistics Using Python
• Data Visualization with Python
• Regression with Minitab
• Logistic Regression
• Data Analysis Using Excel
• The Git Mindset
• Statistics Quiz
• Root Cause Analysis
• Kano Analysis
• Lean Management
• QMS Lead Auditor
• Quality Management
• ISO 9001:2015 Transition
• Project Quality Manager
• Practice Tests
• Summary Sheets
• गुणवत्ता.org
• Introduction to TRIZ: The Innovation and Problem-Solving Methodology

** Unlock Your Full Potential **

TRIZ, the Russian acronym for "Theory of Inventive Problem Solving," is a powerful, systematic methodology for innovation and problem-solving. Developed by Genrich Altshuller and his colleagues in the former Soviet Union, TRIZ is based on the idea that there are universal principles underlying the process of innovation, which can be identified, studied, and applied to enhance creative thinking and solve complex problems. In this post, we will provide an overview of TRIZ, discuss its key principles and tools, and explore how it can be used to foster innovation and enhance problem-solving capabilities in various fields.

Key Principles of TRIZ:

TRIZ is built on several foundational principles that guide the problem-solving process:

1. Patterns of innovation: TRIZ posits that technological systems evolve following predictable patterns, which can be identified and leveraged to generate innovative solutions.

2. Contradictions: TRIZ recognizes that problems often arise from inherent contradictions within a system, and solving these contradictions can lead to breakthrough solutions.

3. Ideality: TRIZ emphasizes the pursuit of ideality, which is achieved when a system delivers maximum value with minimal resources and complexity.

4. Resources: TRIZ encourages the efficient use of available resources, including materials, energy, and knowledge, to create innovative solutions.

Key Tools and Techniques in TRIZ:

TRIZ offers a range of tools and techniques designed to facilitate the problem-solving process, including:

1. 40 Inventive Principles: A collection of 40 general strategies that can be applied to resolve contradictions and generate innovative solutions.

2. Separation Principles: Techniques for resolving contradictions by separating conflicting requirements in time, space, or condition.

3. Contradiction Matrix: A tool that helps identify the most relevant inventive principles to apply based on the specific contradiction at hand.

4. Function Analysis: A method for understanding and optimizing the interactions between components within a system.

5. ARIZ (Algorithm for Inventive Problem Solving): A step-by-step algorithmic approach that guides users through the TRIZ problem-solving process.

Applications of TRIZ:

TRIZ has been successfully applied across various industries, including automotive, aerospace, electronics, manufacturing, and healthcare, among others. Its versatility allows it to be adapted to a wide range of problems, from incremental improvements to radical innovations. Some potential applications of TRIZ include:

1. Product development: TRIZ can be used to identify new product features, improve existing designs, and optimize performance by addressing contradictions and leveraging patterns of innovation.

2. Process improvement: TRIZ can help identify and resolve bottlenecks, inefficiencies, and contradictions within a process, leading to enhanced productivity and reduced costs.

3. Organizational problem solving: TRIZ can be employed to address complex organizational challenges, such as optimizing resource allocation, improving communication, and managing conflicts.

Conclusion:

TRIZ is a powerful and systematic approach to innovation and problem-solving that offers a range of tools and techniques to help users identify and resolve contradictions, leverage patterns of innovation, and pursue ideality. By incorporating TRIZ into their problem-solving toolkit, individuals and organizations can enhance their creative thinking capabilities, overcome complex challenges, and drive breakthrough innovations in a wide variety of fields.

Similar Posts:

March 31, 2018

4 Types of Teams

September 10, 2021

Communications in a Global Economy

December 22, 2021

What is Quality? – Different Perspectives

32 Courses on SALE!

Home Blog Business What is TRIZ and How to Use it in Problem Solving?

What is TRIZ and How to Use it in Problem Solving?

There are a number of problem-solving techniques and methodologies, including brainstorming , root cause analysis , and 5 whys analysis . We covered these methods in a previous post, in which we provided you with 5 Problem Solving Strategies . While the mentioned before can be effective for problem-solving, there is a strategy that goes a step further applying logic, aided by data and research. This strategy is known as TRIZ .

What sets TRIZ apart from other methodologies of its kind is that it provides 40 principles and 76 standards which can enable you to put your problem in a box, and match a solution to resolve it.

History of TRIZ

Genrich Altshuller and his colleagues developed TRIZ. Altshuller was a science fiction author and inventor; he began to work on TRIZ in 1946. For many years TRIZ was not practiced outside the Soviet Union . 

Altshuller worked at the Caspian Sea fleet from the Soviet Navy, more specifically, the Inventions Inspection department. He believed that there were “contradictions”, which occurred when improving a parameter negatively and impacted another. This, according to Altshuller, required inventive solutions. His work was briefly interrupted due to his arrest in 1950. He was sentenced to 25 years due to the letters he wrote to Stalin, top government officials, and newspapers, criticizing some decisions made by the Soviet Government. He resumed his work after he was freed in 1953, after the death of Stalin.

The first paper on TRIZ was published in 1956, and Altshuller expanded his work across the USSR till the 1980s. After the disintegration of the Soviet Union, the concept caught up in other countries, thanks to Soviet emigrants reaching other countries. In 1995, the Altshuller Institute for TRIZ Studies at Boston was established in the United States.

TRIZ has resulted in the birth of hundreds of thousands of inventions by being the base of extensive research across different fields.

What is the TRIZ Method for Problem Solving?

TRIZ is a Russian acronym for “ teoriya resheniya izobretatelskikh zadatch “, which translates in English as the “ theory of inventive problem solving “.

Altshuller lamented that while sailors had maps, the same cannot be said for inventors. Therefore, he developed a methodology that codifies creativity principles forming the basis of the invention. In other words, TRIZ offers generalized solutions for generalized problems. Consequently, they can be matched to your issue, because the problem you face has likely been faced by someone else previously. Applying the solution used back then, and adapting it to your problem, you can reach a solution.

TRIZ is widely used in design engineering, process management and the development of products. Some of the world’s most renowned companies that have used TRIZ in projects include Ford, General Electric, Samsung, LG, Intel, Kodak, Procter & Gamble, Motorola, HP Rolls-Royce..

In 2003, Samsung had 50 patents owing to TRIZ and saved $100 million the following year due to a TRIZ project.

Explanation of the TRIZ Concept by Genrich Altshuller

The video below shows Genrich Altshuller explaining the concept behind TRIZ to students.

Central Concepts of TRIZ

Let’s explore the two central concepts associated with the theory of inventive problem solving, i.e. generalizing problems and solutions & contradictions.

Generalizing Problems and Solutions

The basic concept behind TRIZ, based on research findings, implies that problems and solutions repeat themselves, they repeat across industries. These problems are contradictions that can be resolved using creative solutions. TRIZ is used for understanding these patterns of contradictions and solutions for developing new methods.

Problem Identification: Contradictions

The basic concept of TRIZ identifies contradictions as the primary issue related to a problem, and eliminating them can lead to a solution. Two categories of contradictions exist in TRIZ:

1. Technical Contradictions

Technical Contradictions occur when improving something leads to something else suffering from a negative effect.

Example 1: Processing power for a computer increases (good), but it uses hardware, making it bulkier (bad). . 

Old computers were bulkier, with fewer features; however, overtime, innovation in hardware resolved this problem with smaller processors, with increased processing speed, incorporated in lightweight computers.

Example 2 : A business customizes service for its customers (good); however, the service is now suffering from delays and a long waiting time for customers (bad). 

Many businesses employ many methods to resolve such contradictions, such as using AI-powered online services, portals, and shopping carts to offer customized service, with an estimated delivery time.

2. Physical Contradictions

Physical Contradictions are inherent. An object or system might have requirements that are contrary, resulting in Physical Contradictions.

Example 1: An operating system should be complex so that it can offer many features to the end user; however, it needs to be easy enough to use without many command lines. 

A primary example of this is the need for command lines in most Linux based operating systems. Many Microsoft based client and server operating systems resolve this contradiction by offering an easy to use Graphical User Interface or GUI. Easy search features also aid this within the OS.

Example 2: A cupboard should be large enough to accommodate many items but not take up too much space. 

There are a number of cupboards which are either detachable or can be folded to free up space. Smart cupboards for instance, provide combined solutions for storing more items in less space.

Inventive Principles and Standard Solutions

There are 40 Inventive Principles and 76 Standard Solutions of TRIZ which can be used for resolving problems.

The 40 Inventive Principles of TRIZ

The database of TRIZ has a collection of user compiled resources. This open source database consists of 40 principles. These principles provide the basis for resolving problems. These principles include the following:

Segmentation, extraction, local quality, asymmetry, combination, universality, nesting, counterweight, prior counteraction, prior action, cushion in advance, equipotentiality, inversion, spheroidality, dynamicity, partial, overdone or excessive action, moving to a new dimension, mechanical vibration, periodic action, continuity of useful action, rushing through, convert harm into benefit, feedback, mediator, self-service, copying, inexpensive short life, replacement of a mechanical system, use pneumatic or hydraulic systems, flexible film or thin membranes, use of porous materials, changing the colour, homogeneity, rejecting and regenerating parts, transforming physical or chemical states, phase transition, thermal expansion, use strong oxidisers, inert environment and composite materials.

Example: The first principle in the list, called “segmentation”, proposes breaking down objects into independent parts. This might include manufacturing an object so that it becomes easier to disassemble or use segmentation to resolve a technical issue. This might be done by using a trailer and truck instead of one large truck or by designing cubicles for an open plan office to enable easy reshuffling of the office layout according to need.

For more details, see these 40 TRIZ Principles with detailed explanations.

76 Standard Solutions of TRIZ

There are 76 Standard Solutions which were compiled by none other than Genrich Altshuller and his comrades over ten years between 1975-1985. These standard solutions are categorized in five broad categories.

1.      There are 13 standard solutions for “improving the system” with little or no change.

2.      There are 23 standard solutions for “improving the system” by changing the system.

3.      There are 6 standard solutions for “system transitions”.

4.      There are 17 standard solutions for “detection and measurement”.

5.       There are 17 standard solutions for “simplification and improvement”

For more details, see these 76 Standard Solutions with examples.

Applying TRIZ for Problem Solving 

If you wish to use TRIZ for problem-solving, you can use the following steps to resolve a problem.

1. Define the Problem: You can get started by defining the problem. You can assess if the issue suffers from a Physical or Technical contradiction.

2. Find the TRIZ Generalized Problem to Match your Problem: You can match the generalized problem to match your issue. Since problems are often repeating themselves across industries and sciences.

3. Find the Generalized Solution to Solve the Generalized Problem: You can match the generalized problem to a generalized solution to see how it resolved the former.

4. Use the Identified Solution to Resolve Your Problem: You can use the generalized problem and its generalized solution as an example and adapt it to your specific issue to resolve it.

How to Present a TRIZ Solution in 4 Steps

Do you want to present your TRIZ solution in the form of a PowerPoint presentation? You can use our 4 step guide mentioned below to present a TRIZ solution.

1. Present the Problem in a Single Slide: You can start by presenting a problem in the form of a single slide. This can come after an introductory slide, with the presentation title and the presenter’s name. Alternatively, you can transform the opening slide in a manner that it introduces the topic and also explains the problem. If your audience is new to TRIZ, you might need to explain the concept in a slide prior to discussing how a TRIZ solution might be suitable for it.

2. Compare a Suitable Generalized Problem with a Generalized Solution: You can create a comparison slide to compare a suitable generalized solution to a generalized problem that matches your issue. This can also be a good time to discuss the nature of the contradiction (physical or technical).

3. Explain How the Generalized Solution can be Adapted: The third slide should be focused on how the generalized solution can be adapted to your specific issue. You can use bullet points to discuss the basic elements of the generalized solution’s adaptability for your specific issue. Depending upon the nature of the problem, you can focus on the solution using 1-3 slides.

4. Add a Summary to Conclude the Presentation: You should summarize your TRIZ solution in the form of a closing slide. This should be brief, with a general explanation of the topic, with ideally some focus on the solution. 

Using the 4 step guide above, you can present a TRIZ solution within just 4-8 slides.

Final Words

The theory of inventive problem solving can help resolve a wide range of problems across a variety of fields. Using TRIZ can be a bit complex for people who might not have a scientific background of some sort; however, looking at some of the basic principles alone can help anyone benefit from TRIZ. It isn’t necessary that everyone uses TRIZ on their own. For example, a project or marketing manager can send recommendations to a relevant department to request engineers and designers to look at the possibility of incorporating features that can help reduce project costs or improve a product’s marketability.

The 40 TRIZ Principles alone are enough to provide a range of ideas even to newbies to look for a possible solution to a ‘contradiction’ they may be dealing with. Be it segmentation, extraction, changing the colour, homogeneity or self-service, inexpensive short life or  replacement of a mechanical system. Even behind complex TRIZ principles, the simple ideas have ideas that can be used for resolving problems with creative solutions.

1. Problem Solving PPDAC Diagram PowerPoint Template

The PPDAC diagram template provides an intuitive way to reach towards a solution with it’s unique approach to 5 keywords. Begin with the problem, create a plan, use the data, create an analysis, and finally draft a conclusion.  

Use This Template

Like this article? Please share

Brainstorming, Ideas, Innovation Strategy, Problem Solving, Root Cause Analysis Filed under Business

Related Articles

Filed under Business • October 5th, 2023

SCAMPER Technique & Ideation Method (Quick Guide for Interactive Presentations)

SCAMPER is a technique that provides a structured approach towards thinking outside the box. In this article, we explore how this technique can be used.

Filed under Business • October 2nd, 2023

How to Write a Problem Statement: Hands-On Guide With Examples

A well-written problem statement defines the stage for successful solution development and garnering support from stakeholders. Helpful tips here.

Filed under Business • June 19th, 2023

Quick Guide to Write and Present a Creative Brief

A creative brief is an industry-standard when working in marketing and advertising. However, it’s a useful tool for every creative project type. In this blog post, learn how to create and deliver a creative brief.

Leave a Reply

The Leading Source of Insights On Business Model Strategy & Tech Business Models

TRIZ: Theory of Inventive Problem Solving

• The TRIZ method is an organized, systematic, and creative problem-solving framework. It was developed in 1946 by Soviet inventor and author Genrich Altshuller who studied 200,000 patents to determine if there were patterns in innovation .
• Altshuller acknowledged that not every innovation was necessarily groundbreaking in scope or ambition. From the result of his research, he created five levels of innovation , with Level 1 innovations resulting from obvious or conventional solutions and Level 5 innovations resulting in new ideas that propelled technology forward.
• The TRIZ method has been altered multiple times since it was released and may appear complicated. However, problem-solving teams can take comfort from the fact that others have most likely prevailed against similar problems in the past.

The TRIZ method is an organized, systematic, and creative problem-solving framework. The TRIZ method was developed in 1946 by Soviet inventor and author Genrich Altshuller who studied thousands of inventions across many industries to determine if there were any patterns in innovation and the problems encountered. 

Table of Contents

Understanding the TRIZ method

TRIZ is a Russian acronym for Teoriya Resheniya Izobretatelskikh Zadatch , translated as “The Theory of Inventive Problem Solving” in English.

For this reason, the TRIZ method is sometimes referred to as the TIPS method.

From careful research of over 200,000 patents, Altshuller and his team discovered that 95% of problems faced by engineers in a specific industry had already been solved.

Instead, the list was used to provide a systematic methodology that would allow teams to focus their creativity and encourage innovation .

In essence, the TRIZ method is based on the simple hypothesis that somebody, somewhere in the world has solved the same problem already.

Creativity, according to Altshuller, meant finding that prior solution and then adapting it to the problem at hand.

The five levels of the TRIZ method

While Altshuller analyzed hundreds of thousands of patents, he acknowledged that not every innovation was necessarily groundbreaking in scope or ambition. 

After ten years of research between 1964 and 1974, he assigned each patent a value based on five levels of innovation :

Level 1 (32% of all patents)

These are innovations that utilize obvious or conventional solutions with well-established techniques.

Level 2 (45%)

The most common form where minor innovations are made that solve technical contradictions.

These are easily overcome when combining knowledge from different but related industries.

Level 3 (18%)

These are inventions that resolve a physical contradiction and require knowledge from non-related industries.

Elements of technical systems are either completely replaced or partly changed.

Level 4 (4%)

Or innovations where a new technical system is synthesized.

This means innovation is based on science and creative endeavor and not on technology.

Contradictions may be present in old, unrelated technical systems.

Level 5 (1%)

The rarest and most complex patents involved the discovery of new solutions and ideas that propel existing technology to new levels.

These are pioneering inventions that result in new systems and inspire subsequent innovation in the other four levels over time.

How the TRIZ method works

Since its release, the TRIZ method has been refined and altered by problem-solvers and scientists multiple times. But the problem-solving framework it espouses remains more or less the same:

Gather necessary information

Problem solvers must start by gathering the necessary information to solve the problem.

This includes reference materials, processes, materials, and tools.

Organize the information

Information related to the problem should also be collected, organized, and analyzed.

This may pertain to the practical experience of the problem, competitor solutions, and historical trial-and-error attempts.

Transform the information into a generic problem

Once the specific problem has been identified, the TRIZ method encourages the problem solvers to transform it into a generic problem.

Generic solutions can then be formulated and, with the tools at hand, the team can then create a specific solution that solves the specific problem.

Make sense of that

The last step in the TRIZ method appears to be rather complicated. But it is important for innovators to remember that most problems are not specific or unique to their particular circumstances.

Someone in the world at some point in time has faced the same issue and overcome it.

When to Use TRIZ:

TRIZ is a valuable problem-solving approach in a variety of scenarios:

1. Complex Technical Challenges:

TRIZ is particularly effective for solving complex engineering and technical problems, especially those involving conflicting requirements or constraints.

2. Innovation and Design:

When organizations seek to foster innovation in product design, TRIZ can help identify inventive solutions and drive creativity.

3. Product Development:

TRIZ can be applied at various stages of product development, from concept generation to troubleshooting and optimization.

4. Process Improvement:

It is useful for optimizing processes and operations, reducing inefficiencies, and eliminating bottlenecks.

5. Patent Analysis:

TRIZ can assist in analyzing patents and inventions to uncover the inventive principles and strategies used by others.

How to Use TRIZ:

Applying TRIZ effectively involves a systematic approach that leverages its principles and tools:

1. Define the Problem:

Clearly define the problem or challenge you are facing, including any contradictions or conflicts within the problem statement.

2. Identify Contradictions:

Identify the contradictions or conflicts inherent in the problem. These could be technical contradictions (e.g., increase strength vs. reduce weight) or physical contradictions (e.g., increase temperature vs. reduce temperature).

3. Apply Inventive Principles:

Consult the TRIZ inventive principles and tools to identify solutions that resolve the contradictions. These principles provide guidance on how to overcome specific challenges.

4. Ideate and Innovate:

Encourage creative thinking and brainstorming to generate potential solutions based on the inventive principles and insights gained from TRIZ analysis .

5. Evaluate and Select Solutions:

Evaluate the generated solutions for feasibility, effectiveness, and alignment with the ideal final result (IFR). Select the most promising solutions for further development.

6. Implement and Test:

Implement the chosen solutions and test them in practice. Monitor their effectiveness and make adjustments as needed.

Drawbacks and Limitations of TRIZ:

While TRIZ is a powerful methodology for inventive problem-solving, it is not without its drawbacks and limitations:

1. Complexity:

TRIZ can be complex and may require training and expertise to apply effectively, especially for novices.

2. Not a Panacea:

TRIZ may not be suitable for every problem. Some challenges may be better addressed through simpler problem-solving methods.

3. Cultural and Language Barriers:

TRIZ originated in Russia and has its own terminology, which can be a barrier for individuals from different cultural and linguistic backgrounds.

4. Resource-Intensive:

The extensive analysis and application of TRIZ principles can be resource-intensive, particularly in terms of time and expertise.

5. Not Suited for Non-Technical Problems:

TRIZ is primarily designed for technical and engineering problems and may not be well-suited for non-technical challenges.

What to Expect from Using TRIZ:

Using TRIZ can lead to several outcomes and benefits:

1. Creative Solutions:

TRIZ helps individuals and teams identify inventive solutions that may not be obvious through traditional problem-solving approaches.

2. Contradiction Resolution:

It offers a systematic way to address and resolve contradictions and conflicts within problems.

3. Innovation and Optimization:

TRIZ can drive innovation in product design, process improvement, and optimization efforts.

4. Structured Problem-Solving:

It provides a structured and systematic approach to problem-solving, making it easier to tackle complex challenges.

5. Knowledge Transfer:

TRIZ allows organizations to capture and transfer knowledge about inventive solutions across different projects and teams.

Complementary Frameworks to Enhance TRIZ:

TRIZ can be further enhanced when combined with complementary frameworks and techniques:

1. Lean Six Sigma:

Lean Six Sigma complements TRIZ by focusing on process improvement and waste reduction. Combining both approaches can lead to optimized processes with inventive solutions.

2. Design Thinking:

Design thinking complements TRIZ by emphasizing user-centered design, empathy, and iterative ideation. It encourages innovative solutions that meet user needs.

3. Brainstorming:

Brainstorming sessions can be used in conjunction with TRIZ to generate a wide range of ideas before applying TRIZ’s systematic analysis .

4. Root Cause Analysis:

Root cause analysis techniques help identify the underlying causes of problems, which can then be addressed using TRIZ’s inventive principles.

5. Simulation and Modeling:

Simulations and modeling tools can be used to test and validate TRIZ-based solutions before implementation.

Conclusion:

The Theory of Inventive Problem Solving (TRIZ) is a powerful and structured methodology for inventive problem-solving.

By leveraging the principles of TRIZ, individuals and teams can identify inventive solutions to complex technical challenges, foster innovation in product design, and optimize processes.

While TRIZ may have some limitations and complexities, its benefits in driving creativity, resolving contradictions, and providing a structured problem-solving approach make it a valuable tool for individuals and organizations seeking inventive solutions.

When combined with complementary frameworks and techniques, TRIZ becomes an even more potent force for innovation and creative problem-solving, allowing organizations to overcome technical challenges and achieve breakthroughs in their fields.

Case Studies

Product Design Improvement

Imagine a company that manufactures smartphones and wants to enhance the design of their devices to stand out in the market. They identify the problem as “Stagnant Smartphone Design.”

• Gather Necessary Information : The team collects data on existing smartphone designs, materials, user feedback, and market trends.
• Organize the Information : They analyze existing smartphone designs, including those of competitors, and categorize common design elements and user preferences.
• Transform into a Generic Problem : The generic problem becomes “How to create a smartphone design that appeals to a wide range of users and differentiates from competitors.”
• Apply Tools and Create a Solution : The team utilizes TRIZ tools to generate innovative design concepts. They explore principles like “Use of Contradictions” to balance features like aesthetics and functionality.
• Recognize Commonality : The team researches historical smartphone design breakthroughs and identifies elements that have successfully appealed to users in the past.

This process may lead to a novel smartphone design that incorporates innovative features, such as flexible displays, while addressing common user preferences.

Supply Chain Optimization

A logistics company faces challenges in optimizing its supply chain operations to reduce costs and improve efficiency. They define the problem as “Inefficient Supply Chain Operations.”

• Gather Necessary Information : Data on current supply chain processes, transportation methods, warehousing, and inventory management are gathered.
• Organize the Information : The team analyzes existing supply chain operations, identifies bottlenecks, and reviews industry best practices.
• Transform into a Generic Problem : The generic problem becomes “How to create a highly efficient and cost-effective supply chain system.”
• Apply Tools and Create a Solution : TRIZ tools are applied to generate innovative solutions. Principles like “Trimming” are used to eliminate redundant steps in the supply chain.
• Recognize Commonality : The team researches successful supply chain optimizations in other industries and adapts relevant strategies.

The result may be a streamlined supply chain system that reduces transportation costs, minimizes inventory waste, and enhances overall efficiency.

Energy-Efficient Building Design

An architectural firm aims to design environmentally friendly buildings with superior energy efficiency. They identify the problem as “Inefficient Building Energy Consumption.”

• Gather Necessary Information : Data on existing building designs, construction materials, HVAC systems, and renewable energy technologies are collected.
• Organize the Information : The team analyzes current building designs, identifies energy consumption patterns, and reviews sustainable building practices.
• Transform into a Generic Problem : The generic problem becomes “How to design buildings that maximize energy efficiency and minimize environmental impact.”
• Apply Tools and Create a Solution : TRIZ tools are used to generate innovative building design concepts. Principles like “Ideal Final Result” help in envisioning energy-neutral structures.
• Recognize Commonality : The team studies environmentally friendly building designs worldwide and integrates successful strategies into their projects.

The outcome may be groundbreaking building designs that incorporate passive heating and cooling, energy-efficient materials, and renewable energy sources to achieve net-zero energy consumption.

Medical Device Innovation

A medical device manufacturer wants to develop a groundbreaking medical device to revolutionize patient care. They identify the problem as “Limited Innovation in Medical Devices.”

• Gather Necessary Information : Data on current medical device technologies, patient needs, regulatory requirements, and clinical studies are gathered.
• Organize the Information : The team reviews existing medical devices, identifies gaps in patient care, and studies medical technology advancements.
• Transform into a Generic Problem : The generic problem becomes “How to create a transformative medical device that significantly improves patient outcomes.”
• Apply Tools and Create a Solution : TRIZ tools are applied to generate innovative medical device concepts. Principles like “Contradiction Resolution” help address challenges like miniaturization and enhanced functionality.
• Recognize Commonality : The team studies pioneering medical device innovations and incorporates successful design elements into their project.

Key takeaways

• TRIZ Method: The TRIZ method is a problem-solving framework developed by Genrich Altshuller in 1946. TRIZ stands for “Teoriya Resheniya Izobretatelskikh Zadatch,” which translates to “The Theory of Inventive Problem Solving.”
• Origin and Purpose: Altshuller studied thousands of patents to identify patterns in innovation and problem-solving across various industries. He aimed to create a systematic methodology for problem-solving that encourages creativity and innovation .
• Level 1: Obvious or conventional solutions using well-established techniques (32% of patents).
• Level 2: Minor innovations overcoming technical contradictions by combining knowledge from related industries (45%).
• Level 3: Inventions resolving physical contradictions using knowledge from non-related industries (18%).
• Level 4: Innovations synthesizing new technical systems based on science and creativity (4%).
• Level 5: Pioneering inventions that lead to new systems and inspire innovation in other levels (1%).
• Gather Necessary Information: Collect relevant information about the problem, processes, materials, and tools.
• Organize the Information: Analyze and organize information related to the problem, including practical experience, competitor solutions, and historical attempts.
• Transform into a Generic Problem: Transform the specific problem into a generic form to formulate generic solutions.
• Apply Tools and Create a Solution: Use available tools to create a specific solution that addresses the specific problem.
• Recognize Commonality: Recognize that most problems have been faced by others in the past and have likely been overcome.
• TRIZ is a systematic problem-solving framework developed by Genrich Altshuller.
• It categorizes innovation into five levels based on the nature of the solution.
• The TRIZ method involves gathering and organizing information, transforming the problem into a generic form, applying tools, and recognizing commonality with past solutions.
• The method encourages problem-solvers to leverage existing solutions and patterns to creatively address new challenges.

The 40 TRIZ Principles

Connected analysis frameworks.

Failure Mode And Effects Analysis

Agile Business Analysis

Business Valuation

Paired Comparison Analysis

Monte Carlo Analysis

Cost-Benefit Analysis

CATWOE Analysis

VTDF Framework

Pareto Analysis

Comparable Analysis

SWOT Analysis

PESTEL Analysis

Business Analysis

Financial Structure

Financial Modeling

Value Investing

Buffet Indicator

Financial Analysis

Post-Mortem Analysis

Retrospective Analysis

Root Cause Analysis

Blindspot Analysis

Break-even Analysis

Decision Analysis

DESTEP Analysis

STEEP Analysis

STEEPLE Analysis

Related Strategy Concepts:  Go-To-Market Strategy ,  Marketing Strategy ,  Business Models ,  Tech Business Models ,  Jobs-To-Be Done ,  Design Thinking ,  Lean Startup Canvas ,  Value Chain ,  Value Proposition Canvas ,  Balanced Scorecard ,  Business Model Canvas ,  SWOT Analysis ,  Growth Hacking ,  Bundling ,  Unbundling ,  Bootstrapping ,  Venture Capital ,  Porter’s Five Forces ,  Porter’s Generic Strategies ,  Porter’s Five Forces ,  PESTEL Analysis ,  SWOT ,  Porter’s Diamond Model ,  Ansoff ,  Technology Adoption Curve ,  TOWS ,  SOAR ,  Balanced Scorecard ,  OKR ,  Agile Methodology ,  Value Proposition ,  VTDF

More Resources

About The Author

Gennaro Cuofano

Discover more from fourweekmba.

Subscribe now to keep reading and get access to the full archive.

Type your email…

Continue reading

• 70+ Business Models
• Airbnb Business Model
• Amazon Business Model
• Apple Business Model
• Google Business Model
• Facebook [Meta] Business Model
• Microsoft Business Model
• Netflix Business Model
• Uber Business Model

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

An Overview of TRIZ Problem-Solving Methodology and its Applications

Related Papers

Gunes Kucukyazici

Creativity and Innovation Management

Darrell Mann

Procedia - Social and Behavioral Sciences

İsmail Ekmekçi

IAEME PUBLICATION

IAEME Publication

An account of innovative products, processes and services is a tough process which is possessed of approaches that have modern designs and structure. Nowadays, companies want to be more productive and more efficient. However, sudden and large changes have happened in competitive conditions and to prevail in this competitive and rapidly changing and expanding world, scientific developments had to be followed. To gain competitiveness, the companies need to procreate new products or removing the existing contradictory states. In these cases, TRIZ (Theory and Innovative Problem Solving) methodolgy is one of the most competent scientific approaches, used by managers or inventors. In this study, TRIZ methodolgy was explained in detail with innovation concepts. At the end, an example about TRIZ application has been explained.

Emmanuel Caillaud

Advances in Industrial Design Engineering

Helena Navas

Pavel Livotov

Content Introduction Preface 1 1 Innovation as a Process 3 2 TRIZ and Computer-Aided Innovation (CAI) 7 3 Anticipatory Failure Identification (AFI) 25 4 TRIZ for Business und Management 30 TRIZ tools and components 5 40 Innovation Principles 35 6 Principles for Business & Management 59 7 Separation Principles 73 8 Standard Solutions for Inventive Problem Solving 79 9 Evolution Patterns of Technical Systems 159 10 Resources Checklist 169 11 Application Catalogue of Physical Effects 181 12 Application Catalogue of Chemical Effects 211 13 Application Catalogue of Geometrical Effects 229 14 Contradiction Matrix 237 15 Comprehensive Search for Solutions 247 16 Elimination of harmful effects 279 17 TRIZ Literature 283

2010 34th IEEE/CPMT International Electronic Manufacturing Technology Symposium (IEMT)

Proceedings of the …

Imoh Ilevbare

RELATED TOPICS

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

• © 2018

Advances and Impacts of the Theory of Inventive Problem Solving

The TRIZ Methodology, Tools and Case Studies

• Sebastian Koziołek 0 ,
• Leonid Chechurin 1 ,
• Mikael Collan 2

Department of Machine Design and Research, Wrocław University of Science and Technology, Wrocław, Poland

You can also search for this editor in PubMed   Google Scholar

School of Engineering Science, Lappeenranta University of Technology, Lappeenranta, Finland

School of business and management, lappeenranta university of technology, lappeenranta, finland.

• Features ?a collection of case studies on the use of the Theory of Inventive Problem Solving (TRIZ) across various business activities
• Provides a research update to various TRIZ topics
• Highlights the importance and examples of TRIZ implementation

18k Accesses

36 Citations

• Table of contents

About this book

Editors and affiliations, about the editors, bibliographic information.

• Publish with us

Buying options

• Available as EPUB and PDF
• Read on any device
• Instant download
• Own it forever
• Durable hardcover edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

This is a preview of subscription content, log in via an institution to check for access.

Table of contents (21 chapters)

Front matter, digital learning design: from ideation via triz to implementation.

• Iuliia Shnai

Experimental Validation of Quantum-Economic Analysis (QEA) as a Screening Tool for New Product Development

• Oleg Abramov, Sergey Markosov, Alexander Medvedev

Can Altshuller’s Matrix Be Skipped Using CBR and Semantic Similarity Reasoning?

• Pei Zhang, Sarra Ghabri, Denis Cavallucci, Cecilia Zanni-Merk

A Critical Comparison of Two Creativity Methods for Fostering Participatory Innovation: Implications to Improve TRIZ

• Anna-Maija Nisula, Aino Kianto

Problem Formulation of Screw Feeding System of Fibrous Materials Using TRIZ

• Marek Mysior, Sebastian Koziołek, Eugeniusz Rusiński

Quantifying and Leading Innovation with TRIZ Within Competitiveness Strategies

• Stelian Brad, Emilia Brad

TRIZ to Support Disruptive Innovation of Shared Bikes in China

• Jianguang Sun, Kang Wang, Zhonghang Bai, Yu Wang, Runhua Tan

From Simulation to Contradictions, Different Ways to Formulate Innovation Directions

• Sébastien Dubois, Hicham Chibane, Roland De Guio, Ivana Rasovska

How Problems Are Solved in TRIZ Literature: The Need for Alternative Techniques to Individuate the Most Suitable Inventive Principles

• Yuri Borgianni, Francesco Saverio Frillici, Federico Rotini

TRIZ to Support Creation of Innovative Shared Value Business Initiatives

• Stelian Brad

Mobile Biogas Station Design: The TRIZ Approach

• Mariusz Ptak, Sebastian Koziołek, Damian Derlukiewicz, Marek Mysior, Mateusz Słupiński

Cause-Effect Chains Analysis Using Boolean Algebra

• Jerzy Chrząszcz, Piotr Salata

A Praxiological Model of Creative Actions in the Field of Mechanical Engineering

• Maksymilian Smolnik

A Long-Term Strategy to Spread TRIZ in SMEs. Analysis of Bergamo’s Experience

• Davide Russo, Daniele Regazzoni, Caterina Rizzi

Lessons for TRIZ from Design Thinking and Lean 3P

• Michal Halas

TRIZ Potential for IT Projects

• Monika Woźniak

TRIZ/CrePS Approach to the Social Problems of Poverty: ‘Liberty vs. Love’ Is Found the Principal Contradiction of the Human Culture

• Toru Nakagawa

Product Development Using Heuristic-Systematic Approach: A Case Study

• Bartosz Pryda, Marek Mysior

TRIZ Based Problem Solving of Tile Manufacturing System

• Sebastian Koziołek, Mateusz Słupiński

This book offers a collection of cutting-edge research on the Theory of Inventive Problem Solving (TRIZ). Introduced by Genrich Altshuller in 1956, TRIZ has since been used by engineers, inventors and creators as an essential structured innovation method at businesses and organizations around the globe. The chapters of this book showcase work by selected authors from the 'TRIZ Future' conferences, which are organized by the European TRIZ Association (ETRIA).

The chapters reflect an international mix of new ideas on TRIZ and knowledge-based innovation, highlight recent advances in the TRIZ community, and provide examples of successful collaboration between industry and academia. The book first introduces the reader to recent methodological innovations, then provides an overview of established and new TRIZ tools, followed by a collection of case studies and examples of TRIZ implementation in various scientific and social contexts.

• Case studies on TRIZ
• Advances in TRIZ methodology
• Application case studies for TRIZ
• Tools for TRIZ implementation
• Digital learning design with TRIZ methodology
• Altshuller's matrix
• Cause-effect chains analysis
• Participative innovation methods
• quality control, reliability, safety and risk

Sebastian Koziołek

Leonid Chechurin

Mikael Collan

Book Title : Advances and Impacts of the Theory of Inventive Problem Solving

Book Subtitle : The TRIZ Methodology, Tools and Case Studies

Editors : Sebastian Koziołek, Leonid Chechurin, Mikael Collan

DOI : https://doi.org/10.1007/978-3-319-96532-1

Publisher : Springer Cham

eBook Packages : Business and Management , Business and Management (R0)

Copyright Information : Springer Nature Switzerland AG 2018

Hardcover ISBN : 978-3-319-96531-4 Published: 12 December 2018

eBook ISBN : 978-3-319-96532-1 Published: 29 November 2018

Edition Number : 1

Number of Pages : VIII, 242

Number of Illustrations : 62 b/w illustrations, 57 illustrations in colour

Topics : Project Management , Quality Control, Reliability, Safety and Risk , Operations Research/Decision Theory , Production

Policies and ethics

• Find a journal
• Track your research

AutoTRIZ: Artificial Ideation with TRIZ and Large Langugae Models

Researchers and innovators have made enormous efforts in developing ideation methods, such as morphological analysis and design-by-analogy, to aid engineering design ideation for problem solving and innovation. Among these, TRIZ stands out as the most well-known approach, widely applied for systematic innovation. However, the complexity of TRIZ resources and concepts, coupled with its reliance on users’ knowledge, experience, and reasoning capabilities, limits its practicability. This paper proposes AutoTRIZ, an artificial ideation tool that leverages large language models (LLMs) to automate and enhance the TRIZ methodology. By leveraging the broad knowledge and advanced reasoning capabilities of LLMs, AutoTRIZ offers a novel approach to design automation and interpretable ideation with artificial intelligence. We demonstrate and evaluate the effectiveness of AutoTRIZ through consistency experiments in contradiction detection and comparative studies with cases collected from TRIZ textbooks. Moreover, the proposed LLM-based framework holds the potential for extension to automate other knowledge-based ideation methods, including SCAMPER, Design Heuristics, and Design-by-Analogy, paving the way for a new era of artificial ideation for design and innovation.

Keywords  Innovation   ⋅ ⋅ \cdot ⋅ Design Ideation   ⋅ ⋅ \cdot ⋅ Problem Solving   ⋅ ⋅ \cdot ⋅ TRIZ   ⋅ ⋅ \cdot ⋅ Large Language Models   ⋅ ⋅ \cdot ⋅ Artificial Intelligence

1 Introduction

Intuitive or structured ideation methods such as brainstorming, morphological analysis, and mind-mapping [ 1 , 2 , 3 ] have been used to aid creative ideation of human designers for concept generation. Among these, the Theory of Inventive Problem Solving (TRIZ) [ 4 ] stands out as the most well-known approach, widely applied for systematic innovation. TRIZ is a knowledge-based ideation methodology that provides a structured framework for engineering problem solving by identifying and overcoming technical contradictions using inventive principles derived from a large-scale patent database. However, the complexity of TRIZ resources and concepts poses significant cognitive challenges to effectively learning and applying it. In addition, the problem-solving process in TRIZ is highly dependent on the reasoning capabilities of human users. While some researchers have employed natural language processing [ 5 , 6 , 7 ] , the effectiveness still heavily depends on the users’ proficiency with TRIZ.

Large Language Models (LLMs) such as OpenAI’s GPT [ 8 ] and Meta’s Llama [ 9 ] have not only acquired broad knowledge but also developed emergent abilities such as in-context learning, following instructions, and step-by-step reasoning [ 10 ] . These capabilities have been applied across various domains, including medicine [ 11 ] , chemistry [ 12 ] , and mathematics [ 13 ] . Recently, researchers have evaluated the capabilities of LLMs in engineering-related tasks [ 14 , 15 ] and reported the extensive engineering knowledge within these models and their wide applicability in engineering design and manufacturing. In terms of engineering problem solving and idea generation, there has been preliminary exploration using LLMs [ 16 , 17 , 18 , 19 ] . However, the lack of transparency and limited control over reasoning steps during ideation often lead to divergent results, requiring multiple heuristic attempts by users to achieve desired outcomes. Besides, the interpretability of generated concepts remains challenging, as users obtain only the final results without understanding the ideation reasoning process.

In this work, we aim to leverage the broad knowledge and advanced reasoning capability of LLMs to automate the TRIZ method, showcasing the potential of LLMs in design automation and interpretable innovation. We have developed an LLM-based intelligent tool, AutoTRIZ, capable of artificial ideation for problem solving with TRIZ-based interpretability. AutoTRIZ begins with a problem statement from the user and automatically generates a solution report, strictly following the TRIZ thinking flow and reasoning process. In this paper, we also evaluate the effectiveness and performance of AutoTRIZ through quantitative and comparative experiments, as well as case studies involving human uses of TRIZ from TRIZ textbooks.

2 Related Work

TRIZ is a knowledge-based systematic approach of inventive problem solving, developed in the 1960s by Genrich S. Altshuller and his colleagues [ 4 ] . Through a thorough analysis of over 40,000 patents, Altshuller and his collaborators identified repeated patterns of innovation and underlying innovative principles within these documents. By inductively analyzing these patterns, they proposed a comprehensive problem-solving framework, applying selected inventive principles for ideation. Since then, the TRIZ has been developed continually and some modern TRIZ databases rely on analysis of over 2 million patents. It has been widely applied in industries, research, and education with notable influence in many fields, such as energy, electrical, automotive industries, and mechanical engineering [ 20 ] .

The TRIZ toolkit contains a series of theories and tools that cover all aspects of problem understanding and solving, including trimming method, evolution trends, and 76 standard solutions [ 4 ] . In this paper, we focus on the best-known tool, the Method of Inventive Principles, which represents the basic reasoning logic in TRIZ. Figure 1 shows the overview of its framework (adapted from [ 21 ] ), which contains four steps:

Identify the specific problem.

Transform the specific problem into a general problem by identifying physical contradictions. The contradictions involve an improving feature and a worsening feature. These features are from Altshuller’s 39 engineering parameters.

Search for selected inventive principles from the contradiction matrix using identified contradictions. The contradiction matrix is organized in the form of 39-improving features and 39-worsening features (a 39 by 39 matrix) with each cell entry giving the most often used principles (from TRIZ 40 inventive principles) that may be used to solve the problem.

Use the selected principles to generate solutions to the problem.

Although TRIZ has demonstrated its effectiveness, it still suffers drawbacks that hinder its practical applications. For instance, the complexity of TRIZ resources and concepts poses cognitive challenges to effectively learning and applying it, particularly for non-experts. Additionally, the efficacy of TRIZ is heavily constrained by the users’ reasoning capabilities and prior knowledge acquired.

Recent advancements in machine learning and natural language processing, have been applied in conjunction with TRIZ [ 5 , 7 , 22 ] . These efforts aim to intellectualize the TRIZ reasoning process, thereby reducing the difficulty of use. For instance, Cascini and Russo [ 5 ] developed the PAT-ANALYZER system which can analyze patent texts and automatically extract the contradictory information underlying the innovation for the use of TRIZ. Similarly, Guarino et al. [ 7 ] proposed the PaTRIZ, combining the Bidirectional Encoder Representations from Transformers (BERT) and Conditional Random Field (CRF) for word-level patent analysis and TRIZ contradiction mining. Li et al. [ 22 ] proposed an approach that leverages natural language processing techniques to assess patent innovations according to the level of invention as defined in TRIZ. Berdyugina and Cavallucci [ 23 ] proposed a methodology for the automatic extraction of inventive information from texts for formulating an inventive problem into TRIZ engineering parameters. Their method combined a series of text-mining techniques, including topic modeling, word embedding, and clustering. Hall et al. [ 6 ] proposed an approach that uses topic modeling and unsupervised machine learning to map TRIZ inventive principles to individual patents and detect the novelty.

However, most of these works focus on utilizing algorithms to improve specific steps of the TRIZ process. They still require innovators to dedicate much time and effort to extensive reasoning. Employing these methods does not directly assist users throughout the entire process from analyzing a problem to creating practical solutions. In this paper, we aim to harness LLMs to automate the entire TRIZ reasoning process and minimize the cognitive requirements of users during its application.

2.2 Large Language Models for Design and Innovation

Over the past years, many data-driven approaches have utilized machine learning and deep learning techniques to augment design and innovation [ 24 , 25 ] . Rooted in deep learning, LLMs represent a class of transformer-based algorithms designed for processing and generating natural language text. They are trained on extremely large-scale corpora, enabling them to acquire a wide range of knowledge and capabilities, including understanding context, generating coherent text, and step-by-step reasoning [ 10 ] . Some research has already explored the application of LLMs in engineering design and innovation within specific fields, including microfluidic devices [ 26 ] , robotics [ 27 ] and the user interface of webpages [ 28 ] . However, most of these early efforts primarily utilize conversational interactions, such as those facilitated by ChatGPT, to engage in the innovation process. Meanwhile, with the development of LLMs, there has been an increase in efforts to create LLM-driven methods and tools to offer more generalized innovation assistance and directly support users in rapid ideation.

For instance, several studies have harnessed LLMs for processing vast amounts of design documentation, representing designs in specific forms, and identifying user needs for product development [ 16 , 17 , 29 ] . Han et al. [ 17 ] introduced an LLM-based attribute-sentiment-guided summarization model to extract user needs from online product reviews. Qiu et al. [ 29 ] applied a transformer-based language model to distill design-related knowledge from extensive reports and documents. Moreover, Wang et al. [ 16 ] utilized LLMs to decompose conceptual design tasks into Function-Behavior-Structure (FBS) formats, assisting users in ideation across different aspects.

Recent studies have developed tools and methodologies utilizing LLMs to aid the design process, enhance human-computer collaborative innovation, or directly produce innovative concepts for users [ 18 , 19 , 30 , 31 ] . Ding et al. [ 30 ] conducted a systematic exploration of LLMs’ potential to boost cross-domain analogical creativity. Huang et al. [ 31 ] proposed CausalMapper, a system that combines LLMs with causal mapping to reason about the connections between problems and solutions. Zhu and Luo [ 19 ] presented GPT-based models with domain-specific tuning and task-specific learning, to generate original and useful design concepts. Notably, they applied their approach to automating bio-inspired design concept generation [ 18 ] .

Although these recent idea-generation methods directly leverage the reasoning capabilities of LLMs, the lack of control over LLMs may hinder their effectiveness when assisting ideation. These approaches often lead to solutions that are too divergent to meet specific needs. Managing the problem-solving process to ensure that solutions are both innovative and practical, as well as understanding the reasoning process behind generated innovative solutions, remains a challenge. In this study, we address this issue by integrating TRIZ with LLMs, presenting AutoTRIZ as a tool that follows the TRIZ reasoning steps to generate inventive solutions with interpretability.

In this section, we introduce AutoTRIZ, an artificial ideation tool that automates TRIZ with LLMs. The architecture of AutoTRIZ is depicted in Figure 2. At the core of AutoTRIZ is the utilization of LLMs to learn the reasoning process of the TRIZ methodology, which engineers often find it challenging to learn and excel in.

Overall, AutoTRIZ takes a problem statement prompt from the user as its initial input, and automatically generates a solution report after the reasoning process. The report includes detailed information about the reasoning process based on TRIZ and the resulting solutions to the problem. Within AutoTRIZ, we have defined a four-step reasoning flow based on the classic TRIZ workflow. The system includes an inner fixed knowledge base which consists of three segments related to TRIZ details, enabling controlled reasoning. It is noteworthy that our focus is on controlling the entire problem-solving reasoning process, while remaining open to the knowledge used in ideation. The problem-related knowledge applied during the problem-solving process is drawn from the knowledge base that the LLM has acquired through pre-training on the large-scale corpora.

3.1 Controlling the TRIZ Reasoning Flow

To ensure that the system strictly follows the TRIZ thinking flow and reasoning process, we have configured AutoTRIZ with four modules, corresponding to the four steps in TRIZ. As depicted in Figure 2, Modules 1, 2, and 4, outlined by solid-line frames, are driven by LLMs, whereas Module 3, outlined by a dashed-line frame, is controlled by pre-defined functions without using LLMs. Specifically, we exploit the instruction-following capabilities of LLMs for backend reasoning control. In each module that incorporates LLMs, relevant instructions are engineered into the input as system and assistant prompts.

Specifically, in Module 1, AutoTRIZ identifies the problem to be solved from user input and converts it into descriptive text. Ideally, we hope that the content entered by the user is a clear problem statement. However, user inputs may include additional information such as scenario descriptions, background details, and even some redundant information. Therefore, in this module, AutoTRIZ is designed to identify and extract information related to the problem and then reorganize it into clear and concise text.

In Module 2, AutoTRIZ receives the processed problem description and detects its engineering contradiction, which is represented by a space constructed from two out of the 39 engineering parameters. At this stage, AutoTRIZ learns all the engineering parameters based on the inner knowledge base. The outputs of this module are presented in a structured format (i.e., the indexes of the improving and worsening features). It is important to note that for the same problem statement, the identified contradiction may differ with each execution of this module. On the one hand, a single problem may encompass multiple contradictory pairs, yet our system is designed to identify only one contradiction. On the other hand, there is an inherent randomness in the content generation by LLMs. In the next section, we will conduct experimental investigations to examine the efficacy of contradiction identification and the consistency of the outputs.

Once the contradiction is identified, Module 3 searches the contradiction matrix to find the indexes of relevant inventive principles and returns their descriptions. Following this, Module 4 synthesizes the original problem description, the identified engineering contradiction, and the inventive principles recommended by the system through TRIZ, to generate the final solutions.

LLMs can generate complex structured data, such as in HTML and L A T E X formats [ 32 ] . In AutoTRIZ, we harness this capability to integrate all generated content and directly produce a reader-friendly problem-solving report in a structured format. We have engineered the format template directly into module 4, enabling it to output documents formatted in L A T E X . In practice, the template for the report generation can be adjusted as needed to suit specific requirements.

3.2 Learning from the Fixed Knowledge Base

AutoTRIZ acquires the necessary information to learn the prior knowledge of TRIZ, enabling it to handle various types of problems. We have curated a static knowledge base, which interacts with the modules we described above, thereby empowering AutoTRIZ to master and apply the relevant knowledge. In AutoTRIZ, the internal fixed knowledge base includes three main components: (1) the TRIZ 39 Engineering Parameters [ 4 ] , (2) the TRIZ Contradiction Matrix [ 4 ] , and (3) the TRIZ 40 Inventive Principles [ 4 ] . Notably, the contradiction matrix here is identical to the traditional TRIZ contradiction matrix. The knowledge about engineering parameters and inventive principles includes titles and detailed descriptions for each entry.

For example, for the first engineering parameter: [INDEX] 1 [TITLE] Weight of moving object [DESCRIPTION] The mass of the object in a gravitational field, essentially the force that the body exerts on its support or suspension.

Similarly, for the first inventive principle: [INDEX] 1 [TITLE] Segmentation [DESCRIPTION] The Segmentation principle suggests contemplating the division of an object or system into smaller, independent parts…

All engineering parameters are configured into Module 2 as assistant information. The backend LLMs learn instructions and the output parameter space through in-context learning, enabling zero-shot reasoning. Regarding inventive principles, only selected contents are delivered to the system based on the position in the contradiction matrix. This process is very similar to LLMs’ Retrieval Augmented Generation (RAG). Whereas in our system, the problem-solving process involves precise searching augmented generation, effectively bridging the gap between the prior TRIZ knowledge from experts and the reasoning capabilities of LLMs derived from large-scale pre-training. Simultaneously, all solutions generated are interpretable because each solution is derived from the application of selected inventive principles.

3.3 System Implementation

We developed a web-based tool for public users to test use AutoTRIZ, available at: https://www.autotriz.ai/ . Figure 3 shows the user interface of the tool. Throughout the deployment of this tool and all experiments conducted in this study, we utilized GPT-4-Turbo (Version: 20231106) as the backend LLM. However, it is important to note that since the proposed AutoTRIZ is a general framework, the backend LLM can be replaced with any other closed-source LLM (e.g., Claude) or open-source LLM (e.g., Llama) with minimal effort required for adapting the corresponding prompts. For the TRIZ knowledge base in AutoTRIZ, we adopt the TRIZ definitions and descriptions in an engineering design textbook [ 33 ] .

4 Experimental Evaluation

In this section, we evaluate the effectiveness of the proposed AutoTRIZ through quantitative experiments and comparative studies. Specifically, we collected several case studies analyzed by human experts from TRIZ textbooks, constructing a case base. Then, we explored the consistency of the system in identifying engineering contradictions, as well as its overlap with human analysis. Finally, we selected a specific problem from the case base, and compared and discussed the solutions generated by AutoTRIZ against the results of human experts.

4.1 Constructing the TRIZ Case Base

To evaluate the performance of AutoTRIZ, we first constructed a case base containing TRIZ problem-solving cases developed by human experts. Initially, we gathered several TRIZ-related textbooks, some of which are focused on general design innovation, while others are specifically about TRIZ. From 7 of these textbooks [ 4 , 33 , 34 , 35 , 36 , 21 , 37 ] , we collected 10 initial cases. The selection criteria include: (1) the content of the case contains all elements of the TRIZ reasoning process, including problem description, contradiction identification, inventive principle positioning, and solutions; (2) the problem is defined clearly and comprehensively; (3) the cases do not contain similar problems. All cases are stored in JSON format.

The initial 10 cases cover various domains, including environmental engineering, transportation, manufacturing and material science, aerospace technology, and so on 1 1 1 For further details on all collected cases, please refer to this GitHub repository: https://github.com/shuojiangcn/AutoTRIZ-DETC24 . Beyond serving experimental purposes in this study, the curated case base can also store the results generated by users with AutoTRIZ. In the future, as the size of the base expands, we can explore the interaction between the reasoning module and the existing case base, enabling AutoTRIZ’s innovative capabilities to be scalable.

4.2 Assessing the Contradiction Identification

Detecting contradictions is an essential step in the entire TRIZ problem-solving process. Accurate identification of the contradictions within a problem can effectively assist the system in recommending the appropriate inventive principles for the next step. Sometimes, LLMs may suffer from instability during inference. As a result, some LLM-based agents adopt self-consistency techniques that create several reasoning paths and then perform an ensemble on all generated answers, selecting the most consistent one through majority voting [ 38 ] . However, in our system, analyzing the same problem from different perspectives can yield different possible contradictions. Such inconsistency can sometimes increase diversity, thereby enhancing the novelty. Based on this, we retain the setting of producing a single contradiction in each entry. To assess the performance and consistency of this setting, we conducted the following experiments.

For each given problem statement, we performed the analysis 100 times, resulting in 100 pairs of identified parameters (contradictions). Then, we counted all results and calculated their respective proportions. In cases with high consistency, a particular contradiction could be dominant. In some cases, one parameter in the contradiction may have higher certainty than the other, leading to more dispersed results. Information entropy is utilized to assess the consistency of the results:

where P ⁢ ( x i ) 𝑃 subscript 𝑥 𝑖 P(x_{i}) italic_P ( italic_x start_POSTSUBSCRIPT italic_i end_POSTSUBSCRIPT ) represents the probability of occurrence of the outcome, and n 𝑛 n italic_n is the number of different possible outcomes of X 𝑋 X italic_X . Since the number of runs is 100, the entropy value ranges from 0 to 6.64, where a higher value indicates lower consistency.

Furthermore, we examined the overlap between AutoTRIZ’s detection and the analysis results of human experts from textbooks, categorizing them into three scenarios: complete match, half match, and no match. It is important to note that since human expert analysis also includes subjectivity and bias, it cannot be considered a golden standard. The main purpose of this experiment is to showcase and quantitatively compare AutoTRIZ against human uses of TRIZ.

Figure 4 shows the experimental results, where the bar chart of each case illustrates the top 3 detections by proportion. In the chart, green bars represent complete match , blue bars indicate half match , and yellow bars denote not match . The table in the bottom right corner shows the entropy of each case and whether the top 3 detections hit the reference from textbooks, with symbols ( ✓ ✓ \checkmark ✓ , ✓ ✓ \checkmark ✓ , ✗) indicating complete match , half match , and not match , respectively.

Overall, 7 out of 10 cases match or half-match the textbook’s analysis within the top 3 detections, indicating that AutoTRIZ’s inference overlaps with the human experts’ results to a certain degree. A minority of the cases show relatively higher consistency (cases 5, 6, 7, 8), where the proportion of the top 1 detection is significantly higher than the other detections, including two complete match detections. For these cases, utilizing self-consistency may be beneficial to enhance performance. For other cases, the experimental results show greater diversity, indicated by higher information entropy. By examining the content of the top 3 detections of contradiction for each case, we observe that for almost all cases, one parameter is fixed while the other varies. Moreover, when using the textbook’s analysis as a reference, a pattern emerges across all cases where outputs with higher probabilities (within the top 3 detections) show a better match in alignment. These findings can serve as the initial benchmark for assessing the performance of AutoTRIZ’s contradiction identification. As the case base expands in the future, we can explore these patterns in a more fine-grained way with greater statistical significance. For example, we can examine the differences between various themes, leveraging techniques such as self-consistency reasoning in conjunction with the identified patterns to improve overall performance.

4.3 Comparing AutoTRIZ and Human Expertise

In this section, we select one of the collected cases (case 7) to compare AutoTRIZ’s generated report with humans’ analysis results from the textbook. The reasons for choosing case 7 are two-fold: (1) This case exhibits relatively high consistency in identifying engineering contradictions, with one dominant outcome (refer to Figure 4); (2) The top 3 detections of contradiction are all half-match with the reference. This ensures a certain degree of reliability while allowing the distinction between the subsequent reasoning paths of AutoTRIZ and humans.

The problem of case 7 is about the pneumatic transportation of metal shots through a system of plastic piping. Here is the original problem statement: We are faced with a challenge involving the pneumatic transportation of metal shots through a system of plastic piping originally intended for plastic pellets. The transition to metal shots, despite their advantages for production purposes, has led to significant wear and damage, particularly at the pipe’s elbows. This issue arises from the incompatibility between the metal shots and the existing plastic elbow design. The task is to identify and implement a solution that resolves this conflict, ensuring the system’s durability and effectiveness for transporting metal shots.

In the textbook, the identified improving parameter is "speed" (Parameter 9), and the worsening parameter is "stability of the object’s composition" (Parameter 13). According to the contradiction matrix, the author selects "Mechanical Substitution" (Principle 28) from the obtained inventive principles. Applying this principle, the author describes the solution as placing a magnet at the elbow to bind the metal shots to a plastic material, thereby creating a blanket of shots that absorb the energy.

Figure 5 shows the problem-solving report generated by AutoTRIZ, containing the reasoning process and solutions. The same problem statement is used as the input. Firstly, we can see that AutoTRIZ simplifies the original problem statement, identifying the main issue that needs to be addressed. Regarding the identification of contradictions, AutoTRIZ diverges from human expertise. Both AutoTRIZ and the textbook’s analysis consistently recognize the "stability of the object’s composition" (Parameter 13) as the worsening feature. However, concerning the improving feature, AutoTRIZ detects "Area of stationary object" (Parameter 6), while the textbook’s analysis considers it to be "speed" (Parameter 9). From the original problem statement, we understand that the key issue is to avoid wear on the plastic elbows by the metal shots to ensure durability, which clearly indicates that one of the contradictory parameters involves stability. Whereas the identification of the other parameter is not directly mentioned, leading to a variety of possible interpretations. AutoTRIZ reasons that the surface area needs improvement to withstand the impact and wear of the metal shot, while the expert asserts speed as the system’s top priority. These two analyses highlight different needs, thereby guiding subsequent innovative directions differently.

In the textbook’s analysis, the author selected a single inventive principle (28, ’Mechanical Substitution’) and created a solution by positioning a magnet at the piping’s elbow, which magnetically attaches metal shots to the plastic, forming an energy-absorbing layer. This approach represents a direct and effective innovation. However, based on the identified parameter pair, the contradiction matrix could yield four inventive principles (i.e., (28, ’Mechanical substitution’), (33, ’Homogeneity’), (1, ’Segmentation’), (18, ’Mechanical vibration’) ). Some principles may be challenging to apply, as the outcomes are directly influenced by the users’ reasoning ability, experience, and familiarity with TRIZ materials. This step also requires the most human effort in TRIZ. By comparison, AutoTRIZ can effectively overcome this issue. After identifying the contradiction (Parameter 6 vs. Parameter 13), AutoTRIZ identifies two inventive principles from the contradiction matrix (i.e., (2, ’Extraction’), (39, ’Strong oxidants’) ). For each principle, AutoTRIZ applies it and generates a corresponding solution. Both proposed solutions demonstrate feasibility and innovation. Solution 1 implements a physical alteration to prevent direct contact between the metal shots and the piping. Solution 2, integrating ’Strong oxidants’, involves a surface treatment to improve the piping’s durability against metal shots through a protective coating.

In summary, both the textbook’s solution and the solutions automatically generated by AutoTRIZ are practical, originating from different inventive principles and leading to different approaches. It is important to note that these solutions are relatively preliminary and can serve as foundational directions for innovators to further develop and refine their designs. On this basis, we will continue to develop AutoTRIZ to produce more detailed solutions for the given problem.

5 Discussion

By far, we have presented a new methodology that integrates LLMs and the systematic innovation method, TRIZ, to automatically generate inventive solutions for any given problem in an interpretable way. This methodology has been implemented into a web-based tool, AutoTRIZ. We have demonstrated its effectiveness and practicality through experiments and case studies.

Prior studies [ 14 , 15 ] have assessed LLMs’ capabilities across a broad range of engineering-related tasks, revealing that these models (especially GPT-series models) hold extensive engineering knowledge, such as design and manufacturing. Therefore, in our framework, we only control the reasoning flow, without limiting the knowledge involved in the ideation process, to fully leverage the general knowledge and capabilities of LLMs. In this study, our case base of 10 problems spans multiple distinct domains, and AutoTRIZ has effectively generated inventive solutions in each case.

The proposed method significantly reduces the entry barrier to TRIZ. AutoTRIZ can generate a multitude of solutions in a short period of time because it leverages the computational power and vast knowledge base of LLMs. This efficiency is further enhanced by its user-friendly interface, allowing for easy configuration and use, significantly reducing the time needed to ideate and refine problem-solving strategies. In contrast, mastering the traditional TRIZ method for professional use typically requires months of training and substantial intellectual and cognitive efforts [ 39 ] .

In the comparative study of case 7, we observed that the problem statement contains information related to the desired direction of improvement, which is relevant to the contradiction. Such information aids in aligning AutoTRIZ’s detections with humans’. Accordingly, as demonstrated in Figure 6, we can incorporate multi-input configurations into the system, enabling AutoTRIZ to produce solutions that better meet user expectations.

Although this study focuses on automating the TRIZ reasoning process using LLMs, the proposed framework can be extended to automate other knowledge-based innovation methods. For instance, Yilmaz et al. [ 40 ] identified 77 design heuristics from over 3,000 design process outcomes, and suggested a subset of heuristics to designers to be selected at random has produced improved design outcomes [ 41 ] . By applying our framework to this research, one could treat the identified heuristics as an internal knowledge base for the LLM-based agent, determining how to utilize these heuristics at the backend. Moreover, to develop a more powerful tool, one could also integrate various knowledge-based idea generation methods into the reasoning modules behind LLMs, such as SCAMPER [ 42 ] , IDEO Method Cards [ 43 ] , Bio-inspired Design [ 44 ] , and Design-by-Analogy [ 45 , 46 , 47 ] .

The proposed AutoTRIZ framework has several limitations. Firstly, the solutions generated by the LLMs may contain hallucinations or erroneous information. We plan to include fact-checking modules to ensure the accuracy of the solutions. Also, there is no objective mechanism to evaluate the effectiveness of generated solutions. Users must independently assess solution quality and rank them for practical use. Moreover, this study is demonstrated on a limited set of problem cases, providing only an initial insight into AutoTRIZ that might introduce some bias. In future research, we aim to apply this method to a broader and more diverse range of problems, systematically evaluating the AutoTRIZ’s performance.

6 Conclusion

In this paper, we propose AutoTRIZ, an artificial ideation workflow and tool that leverages LLMs to automate the TRIZ methodology and enhance its applications. AutoTRIZ is constructed by 3 LLM-based reasoning modules and a pre-defined function module, interacting with the inner fixed knowledge base. It takes problem statements from users as initial inputs and automatically produces an interpretable solution report by following the step-by-step TRIZ reasoning process. The efficacy of this method is demonstrated and evaluated through quantitative and comparative experiments, as well as case studies involving human uses of TRIZ from TRIZ textbooks. Although this paper primarily focuses on integrating LLMs with TRIZ, the proposed framework holds the potential to be extended to other knowledge-based ideation methods, including SCAMPER, Design Heuristics, and Design-by-Analogy. Despite its current limitations, we invite interested innovators to test use AutoTRIZ at: https://www.autotriz.ai/ .

Disclosure statement

No potential conflict of interest was reported by the author(s).

• Zwicky [1967] F Zwicky. The morphological approach to discovery, invention, research and construction. New Methods of Thought and Procedure , pages 273–297, 1967.
• White et al. [2012] Christina K White, Kristin L Wood, and Dan Jensen. From brainstorming to c-sketch to principles of historical innovators: ideation techniques to enhance student creativity. Journal of STEM Education: Innovations and Research , 13, 2012.
• Camburn et al. [2020] Bradley Camburn, Ryan Arlitt, David Anderson, Roozbeh Sanaei, Sujithra Raviselam, Daniel Jensen, and Kristin L Wood. Computer-aided mind map generation via crowdsourcing and machine learning. Research in Engineering Design , 31:383–409, 2020.
• Altshuller [1999] Genrikh Saulovich Altshuller. The innovation algorithm: TRIZ, systematic innovation and technical creativity . Technical innovation center Inc., 1999.
• Cascini and Russo [2007] Gaetano Cascini and Davide Russo. Computer-aided analysis of patents and search for triz contradictions. International Journal of Product Development , 4:52–67, 2007.
• Hall et al. [2022] Sawyer Hall, Calahan Mollan, Vijitashwa Pandey, and Zissimos Mourelatos. Triz mapping and novelty detection of engineering design patents using machine learning. International Design Engineering Technical Conferences and Computers and Information in Engineering Conference , 86267:V006T06A044, 2022.
• Guarino et al. [2022] Guillaume Guarino, Ahmed Samet, and Denis Cavallucci. Patriz: A framework for mining triz contradictions in patents. Expert Systems with Applications , 207:117942, 2022.
• Achiam et al. [2023] Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. Gpt-4 technical report. arXiv preprint arXiv:2303.08774 , 2023.
• Touvron et al. [2023] Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al. Llama: Open and efficient foundation language models. arXiv preprint arXiv:2302.13971 , 2023.
• Wei et al. [2022] Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, et al. Emergent abilities of large language models. Transactions on Machine Learning Research , 2022.
• Singhal et al. [2023] Karan Singhal, Shekoofeh Azizi, Tao Tu, S Sara Mahdavi, Jason Wei, Hyung Won Chung, Nathan Scales, Ajay Tanwani, Heather Cole-Lewis, Stephen Pfohl, et al. Large language models encode clinical knowledge. Nature , pages 1–9, 2023.
• Boiko et al. [2023] Daniil A Boiko, Robert MacKnight, Ben Kline, and Gabe Gomes. Autonomous chemical research with large language models. Nature , 624:570–578, 2023.
• Romera-Paredes et al. [2024] Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Matej Balog, M Pawan Kumar, Emilien Dupont, Francisco J R Ruiz, Jordan S Ellenberg, Pengming Wang, Omar Fawzi, et al. Mathematical discoveries from program search with large language models. Nature , 625:468–475, 2024.
• Makatura et al. [2023] Liane Makatura, Michael Foshey, Bohan Wang, Felix HähnLein, Pingchuan Ma, Bolei Deng, Megan Tjandrasuwita, Andrew Spielberg, Crystal Elaine Owens, Peter Yichen Chen, et al. How can large language models help humans in design and manufacturing? arXiv preprint arXiv:2307.14377 , 2023.
• Picard et al. [2023] Cyril Picard, Kristen M Edwards, Anna C Doris, Brandon Man, Giorgio Giannone, Md Ferdous Alam, and Faez Ahmed. From concept to manufacturing: Evaluating vision-language models for engineering design. arXiv preprint arXiv:2311.12668 , 2023.
• Wang et al. [2023a] Boheng Wang, Haoyu Zuo, Zebin Cai, Yuan Yin, Peter Childs, Lingyun Sun, and Liuqing Chen. A task-decomposed ai-aided approach for generative conceptual design. International Design Engineering Technical Conferences and Computers and Information in Engineering Conference , 87349:V006T06A009, 2023a.
• Han et al. [2023] Yi Han, Gaurav Nanda, and Mohsen Moghaddam. Attribute-sentiment-guided summarization of user opinions from online reviews. Journal of Mechanical Design , 145:41402, 2023.
• Zhu et al. [2023] Qihao Zhu, Xinyu Zhang, and Jianxi Luo. Biologically inspired design concept generation using generative pre-trained transformers. Journal of Mechanical Design , 145:41409, 2023.
• Zhu and Luo [2023] Qihao Zhu and Jianxi Luo. Generative transformers for design concept generation. Journal of Computing and Information Science in Engineering , 23:41003, 2023.
• Spreafico and Russo [2016] Christian Spreafico and Davide Russo. Triz industrial case studies: a critical survey. Procedia Cirp , 39:51–56, 2016.
• Silverstein et al. [2008] D Silverstein, N DeCarlo, and M Slocum. How to achieve competitive excellence using triz. NW: Taylor&Francis Group , 2008.
• Li et al. [2012] Zhen Li, Derrick Tate, Christopher Lane, and Christopher Adams. A framework for automatic triz level of invention estimation of patents using natural language processing, knowledge-transfer and patent citation metrics. Computer-aided design , 44:987–1010, 2012.
• Berdyugina and Cavallucci [2023] Daria Berdyugina and Denis Cavallucci. Automatic extraction of inventive information out of patent texts in support of manufacturing design studies using natural languages processing. Journal of Intelligent Manufacturing , 34:2495–2509, 2023.
• Luo [2022] Jianxi Luo. Data-driven innovation : What is it ? IEEE Transactions on Engineering Management , pages 1–19, 2022.
• Jiang et al. [2022a] Shuo Jiang, Serhad Sarica, Binyang Song, Jie Hu, and Jianxi Luo. Patent data for engineering design: A critical review and future directions. Journal of Computing and Information Science in Engineering , 22:060902, 2022a.
• Nelson et al. [2023] Matt D Nelson, Brady L Goenner, and Bruce K Gale. Utilizing chatgpt to assist cad design for microfluidic devices. Lab on a Chip , 23:3778–3784, 2023.
• Stella et al. [2023] Francesco Stella, Cosimo Della Santina, and Josie Hughes. How can llms transform the robotic design process? Nature Machine Intelligence , pages 1–4, 2023.
• Li et al. [2023] Amanda Li, Jason Wu, and Jeffrey P Bigham. Using llms to customize the ui of webpages. Adjunct Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology , pages 1–3, 2023.
• Qiu and Jin [2023] Yunjian Qiu and Yan Jin. Document understanding-based design support: Application of language model for design knowledge extraction. Journal of Mechanical Design , 145:121401, 2023.
• Ding et al. [2023] Zijian Ding, Arvind Srinivasan, Stephen MacNeil, and Joel Chan. Fluid transformers and creative analogies: Exploring large language models’ capacity for augmenting cross-domain analogical creativity. Proceedings of the 15th Conference on Creativity and Cognition , pages 489–505, 2023.
• Huang et al. [2023] Ziheng Huang, Kexin Quan, Joel Chan, and Stephen MacNeil. Causalmapper: Challenging designers to think in systems with causal maps and large language model. Proceedings of the 15th Conference on Creativity and Cognition , pages 325–329, 2023.
• Tang et al. [2023] Xiangru Tang, Yiming Zong, Yilun Zhao, Arman Cohan, and Mark Gerstein. Struc-bench: Are large language models really good at generating complex structured data? arXiv preprint arXiv:2309.08963 , 2023.
• Childs [2013] Peter Childs. Mechanical design engineering handbook . Butterworth-Heinemann, 2013.
• Orloff [2006] Michael A Orloff. Inventive thinking through TRIZ: a practical guide . Springer Berlin, Heidelberg, 2006.
• Orloff [2012] Michael A Orloff. Modern TRIZ: A practical course with easytriz technology . Springer Science & Business Media, 2012.
• Savransky [2000] Semyon D Savransky. Engineering of creativity: Introduction to TRIZ methodology of inventive problem solving . CRC press, 2000.
• Fey and Rivin [2005] Victor Fey and Eugene Rivin. Innovation on demand: new product development using TRIZ . Cambridge University Press, 2005.
• Wang et al. [2023b] Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. Self-consistency improves chain of thought reasoning in language models. The Eleventh International Conference on Learning Representations , 5 2023b.
• Ilevbare et al. [2013] Imoh M Ilevbare, David Probert, and Robert Phaal. A review of triz, and its benefits and challenges in practice. Technovation , 33:30–37, 2013.
• Yilmaz et al. [2016] Seda Yilmaz, Shanna R. Daly, Colleen M. Seifert, and Richard Gonzalez. Evidence-based design heuristics for idea generation. Design Studies , 46:95–124, 2016. ISSN 0142694X. doi: 10.1016/j.destud.2016.05.001 .
• Daly et al. [2012] Shanna Daly, Seda Yilmaz, James L. Christian, Colleen M. Seifert, and Richard Gonzalez. Design heuristics in engineering concept generation. Journal of Engineering Education , 101:602–628, 2012.
• Eberle [1996] Bob Eberle. Scamper on: Games for imagination development . Prufrock Press Inc., 1996.
• IDEO. [2003] IDEO. IDEO method cards: 51 ways to inspire design . William Stout, 2003.
• Fu et al. [2014] Katherine Fu, Diana Moreno, Maria Yang, and Kristin L Wood. Bio-inspired design: An overview investigating open questions from the broader field of design-by-analogy. ASME Journal of Mechanical Design , 136:111102, 11 2014. ISSN 1050-0472. doi: 10.1115/1.4028289 .
• Jiang et al. [2022b] Shuo Jiang, Jie Hu, Kristin L Wood, and Jianxi Luo. Data-driven design-by-analogy: State-of-the-art and future directions. ASME Journal of Mechanical Design , 144:020801, 2022b.
• Murphy et al. [2014] Jeremy Murphy, Katherine Fu, Kevin Otto, Maria Yang, Dan Jensen, and Kristin Wood. Function based design-by-analogy: a functional vector approach to analogical search. ASME Journal of Mechanical Design , 136(10):101102, 2014.
• Hey et al. [2008] Jonathan Hey, Julie Linsey, Alice M Agogino, and Kristin L Wood. Analogies and metaphors in creative design. International Journal of Engineering Education , 24(2):283, 2008.

Integration of inventive problem solving in project based learning for building construction program through module development

[email protected]

• Article contents
• Figures & tables
• Supplementary Data
• Peer Review
• Reprints and Permissions
• Cite Icon Cite
• Search Site

Karen Sharmini Michael , Yee Mei Heong , Tee Tze Kiong , Kok Boon Ching , Nurulwahida Azid , Andika Bagus Nur Rahma Putra , Mohd Azli Salim , Marniati Marniati; Integration of inventive problem solving in project based learning for building construction program through module development. AIP Conf. Proc. 21 March 2024; 2750 (1): 050041. https://doi.org/10.1063/5.0149402

Download citation file:

• Ris (Zotero)
• Reference Manager

Cooperative learning and hands-on techniques are important dimensions for Building Construction students to build skills and gain knowledge. Therefore, the appropriate approach that needs to be given to Building Construction students is Project-Based Learning (PBL). PBL is meaningful question-based learning, encourages Building Construction students to think deeply and increase their curiosity. The problems that need to be solved are close to the real-world context. Accordingly, to increase students’ knowledge to think more creatively and innovatively, a theory can help Building Construction students solve problems that is the Theory of Inventive Problem Solving (TRIZ) has been integrated into PBL. This study aims to develop the TRIZ Integration module in PBL by analyzing the format appropriateness feedback, content, and usability of the module from lecturers and students. This study uses a quantitative approach involving five lecturers and 30 students from the field of Building Construction. Data were analyzed descriptively and presented in terms of frequency and percentage. The study’s findings show that 100% of Building Construction lecturers, and students agree with this module format’s suitability. Besides, 97.3% of lecturers and 100% of students also agreed with the suitability of the content of this module developed. As for the module’s usability, 90% of lecturers and 100% of students agree that Building Construction students can use this developed module. In conclusion, this module successfully helps Building Construction lecturers and students solve inventive problems in PBL effectively.

Sign in via your Institution

Citing articles via, publish with us - request a quote.

Sign up for alerts

• Online ISSN 1551-7616
• Print ISSN 0094-243X
• For Researchers
• For Librarians
• For Advertisers
• Our Publishing Partners  
• Physics Today
• Conference Proceedings
• Special Topics

pubs.aip.org

• Privacy Policy
• Terms of Use

Connect with AIP Publishing

This feature is available to subscribers only.

Sign In or Create an Account