7 qc tools for problem solving

7 Basic Tools of Quality for Process Improvement

Japan is known worldwide for its quality products and services. One of the many reasons for this is its excellent quality management. How did it become so? Japan has Dr. Kaoru Ishikawa to thank for that.

Postwar Japan underwent a major quality revolution. Companies were focused on training their employees in statistical quality control. But soon they realized that the complexity of the subject itself could intimidate most of the workers; so they wanted more basic tools.

Dr. Kaoru Ishikawa, a member of the Japanese Union of Scientists and Engineers (JUSE), took it to his hands to make quality control easier for everyone – even those with little knowledge of statistics – to understand. He introduced the 7 basic tools of quality. They were soon adopted by most companies and became the foundation of Japan’s astonishing industrial resurgence after World War 2.

This post will describe the 7 basic quality tools, how to use them and give you access to templates that you can use right away.

Quality Tools: What Are They?

How can teams and organizations use the 7 basic quality tools, cause and effect diagram, scatter diagram, check sheets.

Control chart
Pareto chart

The 7 basic tools of quality, sometimes also referred to as 7 QC tools – represent a fixed set of graphical tools used for troubleshooting issues that are related to quality.

They are called basic quality tools because they can be easily learned by anyone even without any formal training in statistics. Dr. Kaoru Ishikawa played the leading role in the development and advocacy of using the 7 quality tools in organizations for problem-solving and process improvement.

The 7 basic quality tools include;

Cause-and-effect diagram
Scatter diagram
Check sheet

The 7 quality tools were first emphasized by Kaoru Ishikawa a professor of engineering at the University of Tokyo, who is also known as the father of “Quality Circles” for the role he played in launching Japan’s quality movement in the 1960s. During this time, companies were focused on training their employees in statistical quality control realized that the complexity of the subject could intimidate most of the workers; hence they opted for simpler methods that are easy to learn and use. 7 basic tools of quality were thus incorporated company-wide.

Quality tools are used to collect data, analyze data, identify root causes, and measure results in problem-solving and process improvement. The use of these tools helps people involved easily generate new ideas, solve problems, and do proper planning.

Structured approach: They provide a systematic approach to problem-solving and process improvement, ensuring that efforts are well-organized and focused.
Data-driven decision making: The tools enable data collection, analysis, and visualization, empowering teams to make informed decisions based on evidence.
Improved communication and collaboration: Visual representations and structured tools facilitate effective communication and collaboration among team members, leading to shared understanding and alignment.
Problem identification and prioritization: The tools help identify and prioritize problems or improvement opportunities, enabling teams to allocate resources efficiently and address critical issues first.
Continuous improvement: By using these tools, teams can establish a culture of continuous improvement, as they provide a framework for ongoing monitoring, analysis, and refinement of processes.

7 Basic Quality Tools Explained with Templates

The 7 quality tools can be applied across any industry. They help teams and individuals analyze and interpret the data they gather and derive maximum information from it.

Flowcharts are perhaps the most popular out of the 7 quality tools. This tool is used to visualize the sequence of steps in a process, event, workflow, system, etc. In addition to showing the process as a whole, a flowchart also highlights the relationship between steps and the process boundaries (start and end).

Flowcharts use a standard set of symbols, and it’s important to standardize the use of these symbols so anyone can understand and use them easily. Here’s a roundup of all the key flowchart symbols .

To build a common understanding of a process.
To analyze processes and discover areas of issues, inefficiencies, blockers, etc.
To standardize processes by leading everyone to follow the same steps.

Real-world examples of usage

Documenting and analyzing the steps involved in a customer order fulfillment process.
Mapping out the workflow of a software development lifecycle.
Visualizing the process flow of patient admissions in a hospital.

Enhances process understanding, highlights bottlenecks or inefficiencies, and supports process optimization and standardization efforts.

How to use a flowchart

Gather a team of employees involved in carrying out the process for analyzing it.
List down the steps involved in the process from its start to end.
If you are using an online tool like Creately , you can first write down the process steps and rearrange them later on the canvas as you identify the flow.
Identify the sequence of steps; when representing the flow with your flowchart, show it from left to write or from top to bottom.
Connect the shapes with arrows to indicate the flow.

Who can use it?

Process improvement teams mapping and documenting existing processes for analysis.
Business analysts or consultants analyzing workflow and process optimization opportunities.
Software developers or system designers documenting the flow of information or interactions in a system.

To learn more about flowcharts, refer to our Ultimate Flowchart Tutorial .

Flowchart Template 7 Basic Quality Tools

A histogram is a type of bar chart that visualizes the distribution of numerical data. It groups numbers into ranges and the height of the bar indicates how many fall into each range.

It’s a powerful quality planning and control tool that helps you understand preventive and corrective actions.

To easily interpret a large amount of data and identify patterns.
To make predictions of process performance.
To identify the different causes of a quality problem.
Analyzing the distribution of call wait times in a call center.
Assessing the distribution of product weights in a manufacturing process.
Examining the variation in delivery times for an e-commerce business.

Provides insights into process performance and variation, enabling teams to target areas for improvement and make data-driven decisions.

How to make a histogram

Collect data for analysis. Record occurrences of specific ranges using a tally chart.
Analyze the data at hand and split the data into intervals or bins.
Count how many values fall into each bin.
On the graph, indicate the frequency of occurrences for each bin with the area (height) of the bar.
Process engineers or data analysts examining process performance metrics.
Financial analysts analyzing expenditure patterns or budget variances.
Supply chain managers assessing supplier performance or delivery times.

Here’s a useful article to learn more about using a histogram for quality improvement in more detail.

This tool is devised by Kaoru Ishikawa himself and is also known as the fishbone diagram (for it’s shaped like the skeleton of a fish) and Ishikawa diagram.

They are used for identifying the various factors (causes) leading to an issue (effect). It ultimately helps discover the root cause of the problem allowing you to find the correct solution effectively.

Problem-solving; finding root causes of a problem.
Uncovering the relationships between different causes leading to a problem.
During group brainstorming sessions to gather different perspectives on the matter.
Investigating the potential causes of low employee morale or high turnover rates.
Analyzing the factors contributing to product defects in a manufacturing process.
Identifying the root causes of customer complaints in a service industry.

Enhances problem-solving by systematically identifying and organizing possible causes, allowing teams to address root causes rather than symptoms.

How to use the cause and effect diagram

Identify the problem area that needs to be analyzed and write it down at the head of the diagram.
Identify the main causes of the problem. These are the labels for the main branches of the fishbone diagram. These main categories can include methods, material, machinery, people, policies, procedures, etc.
Identify plausible sub-causes of the main causes and attach them as sub-branches to the main branches.
Referring to the diagram you have created, do a deeper investigation of the major and minor causes.
Once you have identified the root cause, create an action plan outlining your strategy to overcome the problem.
Cross-functional improvement teams working on complex problems or process improvement projects.
Quality engineers investigating the root causes of quality issues.
Product designers or engineers seeking to understand the factors affecting product performance.

Fishbone Diagram 7 Basic Tools of Quality

The scatter diagram (scatter charts, scatter plots, scattergrams, scatter graphs) is a chart that helps you identify how two variables are related.

The scatter diagram shows the values of the two variables plotted along the two axes of the graph. The pattern of the resulting points will reveal the correlation.

To validate the relationship between causes and effects.
To understand the causes of poor performance.
To understand the influence of the independent variable over the dependent variable.
Exploring the relationship between advertising expenditure and sales revenue.
Analyzing the correlation between employee training hours and performance metrics.
Investigating the connection between temperature and product quality in a production line.

Helps identify correlations or patterns between variables, facilitating the understanding of cause-and-effect relationships and aiding in decision-making.

How to make a scatter diagram

Start with collecting data needed for validation. Understand the cause and effect relationship between the two variables.
Identify dependent and independent variables. The dependent variable plotted along the vertical axis is called the measures parameter. The independent variable plotted along the horizontal axis is called the control parameter.
Draw the graph based on the collected data. Add horizontal axis and vertical axis name and draw the trend line.
Based on the trend line, analyze the diagram to understand the correlation which can be categorized as Strong, Moderate and No Relation.
Data analysts exploring relationships between variables in research or analytics projects.
Manufacturing engineers investigating the correlation between process parameters and product quality.
Sales or marketing teams analyzing the relationship between marketing efforts and sales performance.

Check sheets provide a systematic way to collect, record and present quantitative and qualitative data about quality problems. A check sheet used to collect quantitative data is known as a tally sheet.

It is one of the most popular QC tools and it makes data gathering much simpler.

To check the shape of the probability distribution of a process
To quantify defects by type, by location or by cause
To keep track of the completion of steps in a multistep procedure (as a checklist )
Tracking the number of defects or errors in a manufacturing process.
Recording customer complaints or inquiries to identify common issues.
Monitoring the frequency of equipment breakdowns or maintenance needs.

Provides a structured approach for data collection, making it easier to identify trends, patterns, and areas for improvement.

How to make a checksheet

Identify the needed information.
Why do you need to collect the data?
What type of information should you collect?
Where should you collect the data from?
Who should collect the data?
When should you collect the data?
How should you measure the data?
How much data is essential?

Construct your sheet based on the title, source information and content information (refer to the example below).

Test the sheets. Make sure that all the rows and columns in it are required and relevant and that the sheet is easy to refer to and use. Test it with other collectors and make adjustments based on feedback.

Quality inspectors or auditors who need to collect data on defects or issues.
Process operators or technicians responsible for tracking process parameters or measurements.
Customer service representatives who record customer complaints or inquiries.

Control Chart

The control chart is a type of run chart used to observe and study process variation resulting from a common or special cause over a period of time.

The chart helps measure the variations and visualize it to show whether the change is within an acceptable limit or not. It helps track metrics such as defects, cost per unit, production time, inventory on hand , etc.

Control charts are generally used in manufacturing, process improvement methodologies like Six Sigma and stock trading algorithms.

To determine whether a process is stable.
To monitor processes and learn how to improve poor performance.
To recognize abnormal changes in a process.
Monitoring the variation in product dimensions during a manufacturing process.
Tracking the number of customer complaints received per day.
Monitoring the average response time of a customer support team.

Enables real-time monitoring of process stability, early detection of deviations or abnormalities, and prompt corrective actions to maintain consistent quality.

How to create a control chart

Gather data on the characteristic of interest.
Calculate mean and upper/lower control limits.
Create a graph and plot the collected data.
Add lines representing the mean and control limits to the graph.
Look for patterns, trends, or points beyond control limits.
Determine if the process is in control or out of control.
Investigate and address causes of out-of-control points.
Regularly update the chart with new data and analyze for ongoing improvement.
Production supervisors or operators monitoring process performance on the shop floor.
Quality control or assurance personnel tracking variation in product quality over time.
Service managers observing customer satisfaction levels and service performance metrics.

Pareto Chart

The Pareto chart is a combination of a bar graph and a line graph. It helps identify the facts needed to set priorities.

The Pareto chart organizes and presents information in such a way that makes it easier to understand the relative importance of various problems or causes of problems. It comes in the shape of a vertical bar chart and displays the defects in order (from the highest to the lowest) while the line graph shows the cumulative percentage of the defect.

To identify the relative importance of the causes of a problem.
To help teams identify the causes that will have the highest impact when solved.
To easily calculate the impact of a defect on the production.
Analyzing customer feedback to identify the most common product or service issues.
Prioritizing improvement efforts based on the frequency of quality incidents.
Identifying the major causes of delays in project management.

Helps focus improvement efforts on the most significant factors or problems, leading to effective allocation of resources and improved outcomes.

How to create a Pareto chart

Select the problem for investigation. Also, select a method and time for collecting information. If necessary create a check sheet for recording information.
Once you have collected the data, go through them and sort them out to calculate the cumulative percentage.
Draw the graph, bars, cumulative percentage line and add labels (refer to the example below).
Analyze the chart to identify the vital few problems from the trivial many by using the 80/20 rule . Plan further actions to eliminate the identified defects by finding their root causes.
Quality managers or improvement teams looking to prioritize improvement initiatives.
Project managers seeking to identify and address the most critical project risks.
Sales or marketing teams analyzing customer feedback or product issues.

Pareto Chart 7 Quality ToolsControl Chart Seven Basic Quality Tools

What’s Your Favorite Out of the 7 Basic Quality Tools?

You can use these 7 basic quality tools individually or together to effectively investigate processes and identify areas for improvement. According to Ishikawa, it’s important that all employees learn how to use these tools to ensure the achievement of excellent performance throughout the organization.

Got anything to add to our guide? Let us know in the comments section below.

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FAQs about 7 Basic Quality Tools

Quality problems in an organization can manifest in various forms and affect different areas of operations.

Product defects: Products may have defects or non-conformities that deviate from quality specifications, leading to customer dissatisfaction, returns, or warranty claims.
Service errors: Service errors can occur when services do not meet customer expectations, such as incorrect billing, delays in delivery, or inadequate customer support.
Process inefficiencies: Inefficient processes can lead to delays, errors, or rework, resulting in increased costs, decreased productivity, and customer dissatisfaction.
Poor design or innovation: Inadequate product design or lack of innovation can lead to products that do not meet customer needs, lack competitive features, or have usability issues.
Supplier quality issues: Poor quality materials or components from suppliers can affect the overall quality of the final product or service.
Ineffective quality management systems: Inadequate quality management systems, such as lack of quality standards, processes, or documentation, can contribute to quality problems throughout the organization.

The basic quality improvement steps typically follow a systematic approach to identify, analyze, implement, and monitor improvements in processes or products.

Clearly articulate the problem or identify the area for improvement.
Collect relevant data and information related to the problem.
Analyze the collected data to identify patterns, root causes, and opportunities for improvement.
Brainstorm and generate potential improvement ideas or solutions.
Assess the feasibility, impact, and effectiveness of the generated improvement ideas.
Develop an action plan to implement the chosen solution.
Continuously monitor and measure the results of the implemented solution.
Based on the monitoring results, evaluate the effectiveness of the implemented solution.
Once the improvement is successful, document the new processes, best practices, or standard operating procedures (SOPs).
Iterate through the steps to continuously improve processes and products.

7 QC Tools: Your Ultimate Guide To Quality Improvement

Introduction to 7 QC tools

Quality management is an important aspect of any organization, and achieving it requires effective problem-solving strategies. In this regard, the 7 QC tools offer a comprehensive approach to problem-solving and quality improvement. These tools are designed to help organizations identify the root cause of problems, make data-driven decisions, and ultimately improve the quality of their products or services. In this post, we will explore the importance of the 7 QC tools, their history and evolution, how to select the right tool for quality control, and detailed explanations of each of the 7 QC tools.

Importance of 7 QC tools in quality management

The importance of 7 QC tools in quality management cannot be overstated. These tools help organizations to improve quality by providing a systematic approach to problem-solving. They enable organizations to analyze data, identify problem areas, and make data-driven decisions. By using these tools, organizations can reduce costs, increase productivity, and improve customer satisfaction. The 7 QC tools are widely used in various industries, including manufacturing, healthcare, and service sector. They are easy to use, cost-effective, and can be applied to various types of problems.

History and evolution of 7 QC tools

The history and evolution of the 7 QC tools can be traced back to the early 1920s when Dr. Walter A. Shewhart introduced the concept of statistical process control (SPC). Over time, additional techniques were added to the original seven, and the tools evolved to include Pareto charts, cause-and-effect diagrams, check sheets, histograms, scatter diagrams, and control charts. Today, the 7 QC tools are widely used in quality management and have become an integral part of Lean and Six Sigma methodologies.

How to select the right tool for quality control

Here are some points to consider when selecting the right tool for quality control:

Identify the problem: Before selecting a tool, it is important to clearly identify the problem at hand. This will help determine which tool is best suited for the job.
Understand the data: Understanding the data available is crucial for selecting the right tool. Some tools are better suited for qualitative data, while others work best with quantitative data.
Determine the scope: Consider the scope of the problem and the level of detail required to solve it. Some tools are better suited for analyzing specific details, while others provide a more holistic view of the problem.
Consider the complexity: Some problems are more complex than others, and require more sophisticated tools to solve. Consider the level of complexity and choose a tool that is appropriate for the problem at hand.
Evaluate the strengths and limitations: Each tool has its own strengths and limitations. It is important to understand these before selecting a tool, so that you can choose one that is best suited for the problem at hand.
Seek expert advice: If you are unsure which tool to use, seek advice from experts in the field. They can provide valuable insights and help you select the right tool for the job.

By considering these factors, you can select the right tool for quality control and ensure that your problem-solving efforts are effective and efficient.

7 QC Tools Explained

1. Pareto Chart

A Pareto chart is a graph that displays the relative frequency or size of problems in descending order of importance. It is a tool for identifying the most significant causes of a problem or the largest sources of variation in a process. The chart uses a vertical bar graph to show the frequency or size of each problem, with the bars arranged in order of decreasing importance. The chart also includes a cumulative percentage line that shows the cumulative percentage of problems accounted for by each cause. Pareto charts are useful for prioritizing problems and identifying the root causes that should be addressed to have the most significant impact on process improvement.

2. Cause-and-effect diagram

A cause-and-effect diagram, also known as a fishbone diagram or Ishikawa diagram, is a tool used to identify the root causes of a problem. It is a structured approach that helps to identify and categorize the possible causes of a problem, based on the various factors that could contribute to it. The diagram starts with a problem statement at the head of the diagram and uses a structured approach to identify the possible causes, grouping them into categories such as people, process, equipment, materials, and environment. Cause-and-effect diagrams are useful for identifying the root causes of a problem and for organizing and structuring the potential causes in a way that can be easily analyzed and addressed.

3. Check sheet

A check sheet is a tool used to collect data in a structured way. It is a simple form that is used to record data in a standardized format, making it easy to collect and analyze data across different processes or situations. Check sheets can be used to track defects or errors, record the frequency of events, or collect other types of data. They are useful for identifying patterns and trends in data, as well as for tracking progress and improvement over time.

4. Histogram

A histogram is a graph that shows the distribution of data. It is a visual representation of how frequently certain values occur within a set of data, using a series of vertical bars. The bars are grouped into categories or ranges of values, with the height of each bar representing the number of data points that fall within that category. Histograms are useful for identifying the shape of the distribution, including the mean and standard deviation, and for identifying outliers or unusual data points.

5. Scatter diagram

A scatter diagram also known as a scatter plot, is a graph that shows the relationship between two variables. It is a visual representation of how one variable changes in response to changes in the other variable. Each data point is plotted on the graph as a point, with one variable represented on the x-axis and the other variable represented on the y-axis. Scatter diagrams are useful for identifying correlations or patterns in data, and for identifying outliers or unusual data points. They are commonly used in quality control and process improvement to identify relationships between process variables and product quality or performance.

6. Control Charts

A control chart is a tool used to monitor and control a process over time. It is a graphical representation of data collected from a process, plotted against established control limits. The chart shows how the process is performing and alerts the user to any changes or variations that may occur. Control charts are useful for identifying trends, detecting shifts or changes in the process, and for identifying the sources of variation that may be causing problems. They can be used to monitor any process that produces data, from manufacturing to healthcare to financial services.

7. Flow Charts

A flow chart is a diagram that shows the steps in a process or system. It is a visual representation of the sequence of activities involved in a process, from start to finish. Flow charts are used to help understand a process, identify bottlenecks or inefficiencies, and to design or improve a process. The chart consists of boxes, symbols, and arrows that indicate the flow of the process. Boxes represent steps or actions in the process, while arrows represent the flow of materials or information between steps. Flow charts are useful for analyzing and improving any process, from simple to complex, and can be used in a variety of industries, including manufacturing, healthcare, and software development.

7 QC Tools: A Summary Table

These 7 QC tools are often used in combination with each other and with other quality management tools to improve quality and productivity, reduce costs and waste, and enhance customer satisfaction. The 7 QC Tools can be applied across various industries, including manufacturing, healthcare, finance, and service industries. These tools help to identify problems, analyze data, and improve processes, leading to better quality control and customer satisfaction. Knowing how and when to use each tool is essential to their effectiveness and achieving process improvement.

7 QC Tools Limitations:

While the 7 QC tools are widely used and effective for quality management, there are some limitations to their application. Here are some of the common limitations:

Limited scope: The 7 QC tools are primarily focused on identifying and analyzing data related to quality issues and do not address other important aspects of quality management such as customer satisfaction, process improvement, and strategic planning.
Lack of guidance: While the 7 QC tools provide a structured approach to data analysis, they do not provide guidance on how to implement solutions or make improvements based on the results.
Data interpretation: The accuracy and usefulness of the data analyzed using the 7 QC tools depend on the quality and reliability of the data collected. Incorrect data or incomplete data can lead to incorrect conclusions and ineffective solutions.
Limited application: The 7 QC tools are designed for use in manufacturing and industrial settings, and may not be as relevant or applicable in service industries or other non-manufacturing settings.
Insufficient for complex problems: The 7 QC tools are useful for identifying and analyzing simple quality problems with a single cause or factor, but may be insufficient for more complex problems that have multiple causes and variables.
Overreliance on data: The 7 QC tools rely heavily on data analysis and may overlook other important factors that contribute to quality, such as employee involvement, leadership, and culture.

Alternative Approach to 7QC Tools:

There are several other quality management tools and methodologies that organizations can use in addition to or instead of the 7 QC tools. Some of these alternatives include:

Six Sigma: A data-driven approach to quality management that aims to minimize defects and variability in processes and products by using statistical methods and tools.
Lean Manufacturing: A methodology focused on reducing waste and improving efficiency in manufacturing processes by eliminating non-value-added activities, streamlining production flows, and increasing responsiveness to customer demands.
Root Cause Analysis (RCA): A problem-solving technique used to identify the underlying causes of a problem or failure, and develop solutions to prevent recurrence.
Failure Mode and Effects Analysis (FMEA): A proactive risk management tool that helps identify and mitigate potential failures and defects in products or processes before they occur.
Statistical Process Control (SPC): A method for monitoring and controlling a process by using statistical techniques to identify and correct deviations and abnormalities in the process.
Kaizen: A continuous improvement philosophy that emphasizes small, incremental changes in processes and systems, and encourages employee involvement and empowerment.

These tools and methodologies can be used alone or in combination with each other, depending on the specific needs and goals of the organization.

In conclusion, the 7 QC tools offer a comprehensive approach to problem-solving and quality improvement. They are data-driven, cost-effective, and provide a systematic approach to quality management. By using these tools, organizations can reduce costs, increase productivity, and improve customer satisfaction. However, it is important to select the right tool for the problem at hand, and to understand the strengths and limitations of each tool. The 7 QC tools have a rich history and have become an integral part of Lean and Six Sigma methodologies, making them an essential tool for any organization that wants to improve the quality of its products or services.

References:

Goetsch, D. L., & Davis, S. B. (2014). Quality management for organizational excellence. Upper Saddle River, NJ: Pearson.

Ishikawa, K. (1985). What is Total Quality Control? The Japanese Way. Englewood Cliffs, NJ: Prentice Hall.

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Streamlining Six Sigma Projects with The 7 QC Tools

Updated: September 26, 2023 by Ken Feldman

As in any tool chest, you can have dozens, if not hundreds, of different tools for all types of specialized tasks. Such is the case with Six Sigma. There are many tools available for your use depending on what you want to accomplish. However, like your home tool chest, there are a small set of basic tools that are your go-to tools you will use most often and on most projects.

Let’s review the 7 QC tools that are most commonly used in Six Sigma , the benefits of those tools, and some best practices for using them.

Overview: What are the 7 QC tools?

It is believed that the 7 QC tools were introduced by Kaoru Ishikawa in postwar Japan, inspired by the seven famous weapons of Benkei. Benkei was a Japanese warrior monk who armed himself with seven weapons and was on a personal quest to take 1,000 swords from samurai warriors who he believed were arrogant and unworthy.

Ishikawa was influenced by a series of lectures on statistical quality control given by Dr. W. Edwards Deming in 1950 to a group of Japanese scientists and engineers. Unfortunately, the complexity of the subject intimidated most workers, so Ishikawa focused primarily on a reduced set of tools that would suffice for most quality-related issues.

The 7 QC tools are:

Check sheet
Fishbone diagram (cause and effect diagram, or Ishikawa diagram)
Pareto chart
Control chart
Scatter diagram
Stratification

Let’s explore each in a little more detail.

Check sheet: A form to collect and tally data for further analysis.

Image source: techqualitypedia.com .

Fishbone diagram: Fishbone diagrams are used to drill down to find the root cause of a problem. As the name implies, the diagram looks like the bones of a fish, where each main bone represents a specific category of possible root cause, and the subsequent drilling down is shown as smaller and smaller bones.

Image source: asq.org .

Histogram: This is a bar graph showing the frequency of a set of data, usually continuous data. The histogram allows you to see the center of the data, the range of the data, and the distribution of the data. It is a very useful snapshot. The downside is that you can’t see the sequence or order of the data.

Image source: statisticsbyjim.com .

Pareto chart: This chart is based on the 80/20 principle that says 80% of your effect is caused by 20% of your causes. For example, 80% of your sales comes from 20% of your customers. Dr. Joseph Juran, who developed this chart, often referred to this principle as the vital few and trivial many . He later revised that to the vital few and useful many . The Pareto chart lists the causes in descending order of frequency or magnitude. It is used to prioritize what you should look at first to improve your process.

Image source: www.automateexcel.com .

Control chart: A control chart is a statistical tool that looks at your process data over time for the purpose of distinguishing between special cause and common cause variation.

Image source: www.spcforexcel.com .

Scatter diagram: These are also known as scatter plots. They’re used to show a graphical correlation between a set of paired data on an X and Y axis. It is the graphical representation of what you would use for regression analysis.

Image source: www.spcforexcel.com .

Stratification: This is a graph that shows data that has been stratified when the data comes from different sources. It is useful to view the data by certain strata such as shift, gender, geographic location, machines, or suppliers.

Image source: www.systems2win.com .

3 benefits of the 7 QC tools

These seven tools are easy to understand and apply and will help you understand what is going on in your process.

1. Easy

These 7 QC tools are easy to understand and implement yet powerful in identifying root causes, in discriminating between types of variation, and as a visual description of your data. A picture is truly worth 10,000 words (or statistical calculations).

2. Software-driven

Gone are the days when you had to draw all of your graphs by hand. There are many simple and cost-effective software packages that will take your data and quickly produce graphs.

3. 80/20

The Pareto principle applies to the 7 QC tools as well. 80% of your quality issues can be addressed by using 20% of the most common tools.

Why are the 7 QC tools important to understand?

The key thing to understand is when to use each tool — which one is appropriate for your specific situation?

Tools address different issues

The more familiar you are with these common tools, the quicker you’ll be able to select the right one to help you solve your problem or answer your question. The Fishbone diagram is used to search for root causes of your problem. A control chart is used to distinguish between common and special cause variation. A scatter diagram is used to look for correlation or relationship between an X and Y variable.

Graphs don’t tell the whole story

Graphs and diagrams are useful for providing an overview and directional indicator of your process, but statistical analysis will provide greater confidence than a graph alone.

Flexibility

These seven tools can be used for different types of data and across any type of function. Their flexibility makes them useful in myriad situations and industries, so becoming familiar with them can be a wise investment.

3 best practices when thinking about the 7 QC tools

Use these tools for as many applications as is feasible. Keep it simple, and only use the more sophisticated and complex tools if you need the additional information and analysis.

1. Have a clear idea of what question you’re trying to answer

Since each of the tools can be used to answer different data and process questions, be sure you’ve clearly defined the question you’re trying to answer.

2. Use them as your primary presentation

Use the 7 QC tools and their accompanying graphs and diagrams as your primary presentation format. Reserve the statistical analysis for questions that go beyond what’s answered in the graphs.

3. Make sure they’re self-explanatory

Be sure your graphs are succinct and self-explanatory so people can understand what you’re trying to tell them without the need for a long-winded explanation.

Frequently Asked Questions (FAQ) about the 7 QC tools

What is meant by stratification .

If you collected production data throughout the day across all three shifts and five machines, you might want to stratify or separate your data and look at it by shift and by machine. This would allow you to understand whether there were any differences between the strata. This might indicate the source of a root cause or an opportunity to improve the other shifts if one is found to be doing better than the others.

What are the 7 basic QC tools?

Scatter diagrams, Pareto charts, control charts, histograms, stratification, fishbone diagrams and check sheets.

Do I have to draw the graphs and diagrams for the 7 QC tools by hand?

With the use of current software and computer technology, you will rarely be required to create the graphs by hand. Still, it might be interesting to do it by hand once to fully appreciate the tools and software available to us.

Let’s review what’s in your tool belt

The 7 QC tools are basic graphical representations of your data. They can be used to answer a wide variety of questions about your data and your process. Use them as your primary presentation format when talking about what your data is telling you. While they are not a complete list of tools, they should be robust enough to address many of your improvement issues.

The 7 QC tools, while basic, are foundational to the Six Sigma methodology and have stood the test of time. Their simplicity and versatility make them indispensable for professionals across industries. As businesses evolve and data becomes more integral to decision-making, the importance of these tools only grows. They bridge the gap between raw data and actionable insights, allowing teams to make informed decisions. Moreover, in today’s digital age, with the integration of AI and machine learning, these tools can be further enhanced to provide even deeper insights. However, the essence remains the same: understanding and improving processes through data visualization.

Key Points About The 7 QC Tools:

Origin and Influence: Introduced by Kaoru Ishikawa, inspired by Benkei’s seven weapons and influenced by Dr. W. Edwards Deming’s lectures on statistical quality control.

List of 7 QC Tools: Check sheet, Fishbone diagram, Histogram, Pareto chart, Control chart, Scatter diagram, and Stratification.

Benefits: These tools are easy to understand, software-driven, and adhere to the 80/20 principle, addressing 80% of quality issues with 20% of the most common tools.

Importance: They address different issues, provide an overview of processes, and offer flexibility across data types and functions.

Best Practices: Clearly define the question, use the tools as the primary presentation format, and ensure graphs are self-explanatory.

About the Author

Ken Feldman

INDUSTRIAL TRAINER

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7qc tools: Significance, How to use?, How to Create

Table of Contents

What are 7QC Tools?

In today’s competitive business world, quality is one of the most important factors that determine the success of a company. Quality Control (QC) is a process that ensures that a company’s products or services meet the required standards. The 7QC tools are a set of techniques used to identify, measure, analyze, and solve quality problems. These tools were first introduced by Dr. Kaoru Ishikawa in the 1950s and have since been widely adopted in quality management systems.

Types of 7QC Tools

Check Sheet
Cause & Effect Diagram (Ishikawa or Fishbone Diagram)
Pareto Chart
Control Diagram
Scatter Chart

1. Check sheet

In quality management, a check sheet is a tool that helps to collect and organize data. It is a simple and effective tool that can be used in a variety of settings to gather information and identify trends. In this blog post, we will explore what a check sheet is, how to use it, and its benefits and drawbacks.

What is a Check Sheet?

A check sheet is a type of document that is used to collect and record data. It is a form that typically contains a list of items or categories that need to be checked or observed. As data is collected, marks or symbols are added to the appropriate category to indicate that the item has been observed or checked.

Benefits of Check Sheets

The following are the benefits of using a check sheet:

E asy to Use : Check sheets are easy to create and use, making them a convenient tool for collecting and organizing data.
Cost-Effective : Check sheets are a low-cost tool that can be used in a variety of settings to gather information and identify trends.
Increased Accuracy : Check sheets help to ensure that data is collected accurately and consistently, reducing the risk of errors or inconsistencies.
Improved Decision-Making : By providing a visual representation of the data, check sheets help to identify trends and patterns that can inform decision-making.
Standardization : Check sheets can be used to standardize data collection processes, ensuring that all data is collected in a consistent and uniform manner.

Disadvantages of Check Sheets

The following are the disadvantages of using a check sheet:

Limited Scope : Check sheets are designed to collect a specific type of data and may not be suitable for collecting more complex data.
Manual Analysis : Analyzing data collected on a check sheet may require manual analysis, which can be time-consuming and may be prone to errors.
Limited Flexibility : Check sheets may not be suitable for collecting data in dynamic or changing environments.
Subjectivity : The accuracy and reliability of data collected on a check sheet may be affected by the subjectivity of the person collecting the data.

2. Cause and Effect Diagram

The cause-and-effect diagram, also known as the fishbone diagram or Ishikawa diagram, is a tool used to identify the root cause of a problem. It is a visual representation of the factors that contribute to a problem.

What is Cause and Effect Diagram?

A Cause and Effect Diagram is a visual tool used to identify and analyze the root causes of a problem or issue. It is a structured approach to problem-solving that allows teams to identify and organize the factors that contribute to a problem or issue. The diagram is called a “fishbone” because of its appearance, which resembles the skeleton of a fish. The diagram is organized into several categories, which represent different areas of the process being analyzed. These categories are typically referred to as the “bones” of the fishbone diagram.

Components of a Cause and Effect Diagram

A Cause and Effect Diagram consists of four primary components: the problem statement, the main “bone,” the sub-bones, and the causes. Each of these components is essential in creating an effective diagram that accurately reflects the problem or issue being analyzed.

Problem Statement : The problem statement is the starting point for the Cause and Effect Diagram. It is a brief description of the problem or issue being analyzed. The problem statement should be concise and clear, so that everyone on the team can understand it.

Main Bone : The main bone is the primary category of the problem or issue being analyzed. It is typically represented by the horizontal line on the diagram, which serves as the backbone of the fishbone. The main bone is the broadest category, and it should be broad enough to encompass all of the contributing factors.

Sub-Bones : The sub-bones are the categories that support the main bone. They are typically represented by diagonal lines extending from the main bone. The sub-bones should be more specific than the main bone, but still broad enough to encompass all of the contributing factors.

Causes : The causes are the specific factors that contribute to the problem or issue being analyzed. They are typically represented by smaller lines extending from the sub-bones. The causes should be specific and actionable so that the team can develop effective solutions to address them.

How does Cause and Effect Diagram work?

The Cause and Effect Diagram works by organizing the various factors that contribute to a problem or issue into a visual format. By doing this, the team can identify and analyze the root causes of the problem, rather than just addressing the symptoms. The diagram helps to structure the problem-solving process and ensure that all of the relevant factors are considered.

To create a Cause and Effect Diagram, the team should follow these steps:

Define the problem or issue being analyzed.
Identify the main bone, which represents the primary category of the problem or issue.
Identify the sub-bones, which represent the categories that support the main bone.
Identify the causes, which are the specific factors that contribute to the problem or issue.
Analyze the causes to determine the root cause of the problem or issue.
Develop solutions to address the root cause of the problem or issue.

Advantages of Cause and Effect Diagram

The Cause and Effect Diagram has several advantages, which make it a powerful tool for problem-solving and process improvement:

Provides a visual representation of the problem or issue, making it easier for teams to understand and analyze.
Allows teams to identify the root causes of a problem or issue, rather than just addressing the symptoms.
Organizes the problem-solving process, ensuring that all of the

Tips for Using a Cause and Effect Diagram:

Involve a team : Use a cross-functional team to create the diagram. This ensures that all relevant factors are considered and different perspectives are included.
Use brainstorming : Use brainstorming to identify all the potential causes. Encourage team members to share their ideas freely, without judgment.
Be Specific : Write specific causes on the diagram rather than general categories. This helps to focus the analysis and identify the root cause more accurately.
Test assumptions : Check your assumptions by verifying them with data. Use data to validate or invalidate potential causes.
Iterate : Use the diagram to develop solutions, then test and refine them. Iterate the process until the problem is solved.

3. Pareto Chart

Pareto Chart is a quality control tool that helps in identifying the most significant factors responsible for quality problems in a process. It is a graphical representation of the 80/20 rule, which states that 80% of the problems arise from 20% of the causes. A Pareto Chart is often used in conjunction with other quality control tools to determine the root cause of a problem and to prioritize improvement efforts.

How to Create a Pareto Chart?

The following are the steps to create a Pareto Chart:

Define the problem : Define the problem you want to address and collect data related to it.
Categorize the data: Categorize the data into different categories or factors that contribute to the problem.
Collect frequency data : Collect frequency data for each category or factor. The frequency data can be in the form of counts, percentages, or any other appropriate measure.
Rank the categories : Rank the categories or factors in descending order of frequency. The category with the highest frequency should be placed at the top of the chart.
Plot the data : Plot the frequency data for each category on a bar graph. The height of each bar represents the frequency or percentage of the category.
Draw a cumulative percentage line : Draw a cumulative percentage line on the chart. This line represents the cumulative percentage of the total frequency. It is calculated by adding the percentage of each category in descending order.
Analyze the chart : Analyze the chart to identify the most significant factors that contribute to the problem. The Pareto Chart helps to identify the 20% of the factors that are responsible for 80% of the problems.

Advantages of Using Pareto Chart

Prioritization : A Pareto Chart helps in identifying the most significant factors responsible for quality problems in a process. It helps to prioritize improvement efforts by focusing on the factors that contribute the most to the problem.
Visualization : A Pareto Chart provides a visual representation of the data, which makes it easier to understand and analyze. It helps to identify patterns, trends, and outliers in the data.
Easy to use : Pareto Chart is simple and easy to use. It does not require any special software or tools. It can be created using a spreadsheet or graph paper.
Cost-effective : Pareto Chart is a cost-effective tool for quality control. It requires minimal resources and can be created using the data already available.

Disadvantages of Using Pareto Chart

Limited to Categorical Data : Pareto Chart can only be used for categorical data. It cannot be used for continuous data.
Subjective Ranking : The ranking of categories is subjective and may vary from person to person. It is important to have a consensus among the team members on the ranking of categories.
Ignoring Small Factors : Pareto Chart focuses only on the significant factors that contribute to the problem. It may ignore small factors that may be contributing to the problem.
Simplistic Approach : Pareto Chart provides a simplistic approach to quality control. It may not be effective in solving complex problems that require a more in-depth analysis.

4. Control Chart

Control charts are an essential tool for monitoring and controlling the quality of a process. They help in identifying the sources of variation in a process and determining whether the process is in control or out of control. Control charts provide a graphical representation of the data, which makes it easier to understand and analyze.

How to Create a Control Chart?

The following are the steps to create a control chart:

Collect data : Collect data related to the process you want to monitor. The data can be in the form of measurements, counts, or percentages.
Determine the sample size : Determine the sample size for the data collection. The sample size should be large enough to provide an accurate representation of the process.
Calculate the mean and standard deviation : Calculate the mean and standard deviation of the data. The mean represents the central tendency of the data, and the standard deviation represents the variation of the data.
Plot the data : Plot the data on a control chart. The chart should have two horizontal lines representing the upper and lower control limits, and a central line representing the mean.
Analyze the chart : Analyze the control chart to determine whether the process is in control or out of control. If the data points are within the control limits and show random variation, the process is in control. If the data points are outside the control limits or show non-random variation, the process is out of control.

Types of Control Charts

X-Bar and R Chart : X-Bar and R Chart is used to monitor the process mean and the variation of the process. It is used for continuous data.
X-Bar and S Chart : X-Bar and S Chart is used to monitor the process mean and the variation of the process. It is used for continuous data.
Individual and Moving Range (I-MR) Chart : I-MR Chart is used to monitor the process mean and the variation of the process. It is used for continuous and discrete data.
P Chart : P Chart is used to monitor the proportion of defective items in a process. It is used for attribute data.
C Chart : C Chart is used to monitor the number of defects per unit in a process. It is used for attribute data.

Advantages of Using Control Charts

Continuous monitoring : Control charts provide continuous monitoring of the process, which helps in identifying any changes in the process.
Early detection of problems : Control charts help in detecting problems early, which allows for timely corrective action.
Statistical analysis : Control charts use statistical analysis to determine whether the process is in control or out of control. This helps in making data-driven decisions.
Standardization : Control charts provide a standardized approach to monitoring and controlling the quality of a process.

Disadvantages of Using Control Charts

Limited to process data : Control charts are limited to process data and cannot be used for other types of data.
Data collection : Control charts require the collection of data, which can be time-consuming and costly.
Expertise : Control charts require expertise in statistical analysis, which may not be available in all organizations.
Not foolproof : Control charts are not foolproof and may fail to detect certain types of problems in a process.

5. Scatter Diagram

A scatter diagram is a tool used in quality management to investigate the relationship between two variables. It is a graphical representation of the data, where one variable is plotted on the x-axis and the other variable is plotted on the y-axis. The purpose of a scatter diagram is to identify any correlation or patterns between the two variables and to help in the decision-making process.

How to Create a Scatter Diagram?

The following are the steps to create a scatter diagram:

Collect Data : Collect data for the two variables that you want to investigate.
Determine the Relationship : Determine the type of relationship that exists between the two variables. The relationship can be positive, negative, or neutral.
Plot the Data : Plot the data on the scatter diagram, with the independent variable (x-axis) on the horizontal axis and the dependent variable (y-axis) on the vertical axis.
Analyze the Data : Analyze the scatter diagram to identify any patterns or trends that exist between the two variables.

Types of Scatter Diagrams

Positive Correlation : A positive correlation exists when an increase in one variable results in an increase in the other variable.
Negative Correlation : A negative correlation exists when an increase in one variable results in a decrease in the other variable.
No Correlation : No correlation exists when there is no relationship between the two variables.

Advantages of Using Scatter Diagrams

Identify Trends : Scatter diagrams help in identifying any trends or patterns that exist between the two variables. This can help in predicting future behavior or outcomes.
Visual Representation : Scatter diagrams provide a visual representation of the data, which makes it easier to understand and analyze.
Decision Making : Scatter diagrams help in the decision-making process by providing a clear understanding of the relationship between the two variables.
Quality Improvement : Scatter diagrams can be used in quality improvement projects to identify the root cause of problems and to monitor the effectiveness of solutions.

Disadvantages of Using Scatter Diagrams

Limited to Two Variables : Scatter diagrams are limited to investigating the relationship between two variables only.
Interpretation : Interpretation of the scatter diagram requires expertise in statistical analysis.
Causation : A scatter diagram only shows the relationship between two variables and cannot prove causation.
Outliers : Outliers can distort the data and affect the accuracy of the scatter diagram.

6. Histogram

The histogram is a bar graph that shows the distribution of data. It is used to identify whether data is normally distributed or skewed. The histogram can be used for various types of data collection, including qualitative and quantitative data.

Benefits of Histogram

Histograms are graphical representation of data that allows us to see the distribution of a dataset. A histogram consists of a series of bars, where the height of each bar represents the frequency or proportion of values within a specific range. Histograms are widely used in quality management to identify patterns, trends, and outliers in a dataset.

How to Create a Histogram?

The following are the steps to create a histogram:

Collect Data : Collect the data that you want to analyze.
Determine the Number of Bins : Decide on the number of bins you want to use. A bin is a range of values that the data is divided into. The number of bins depends on the size of the dataset and the desired level of detail.
Determine the Bin Width : Calculate the bin width by dividing the range of the data by the number of bins.
Plot the Data : Plot the data on the histogram, with the range of values on the x-axis and the frequency or proportion on the y-axis.
Analyze the Histogram : Analyze the histogram to identify any patterns, trends, or outliers in the data.

Types of Histograms

Normal Distribution : A normal distribution has a bell-shaped curve and is symmetrical around the mean. Most of the values fall near the mean, with fewer values at the extremes.
Skewed Distribution : A skewed distribution has a long tail on one side of the curve. Skewed distributions can be either positively skewed or negatively skewed.
Bimodal Distribution : A bimodal distribution has two peaks or modes, indicating that there are two distinct groups within the data.

Advantages of Using Histograms

Visual Representation : Histograms provide a visual representation of the data, which makes it easier to understand and analyze.
Identify Patterns : Histograms help in identifying patterns, trends, and outliers in the data.
Quality Improvement : Histograms can be used in quality improvement projects to monitor process performance, identify defects, and measure the effectiveness of process improvements.
Statistical Analysis : Histograms can be used in statistical analysis to determine the distribution of a dataset and to calculate the mean, median, mode, and standard deviation.

Disadvantages of Using Histograms

Bin Size : The accuracy of a histogram depends on the size and width of the bins used. Choosing the wrong bin size can result in inaccurate analysis.
Interpretation : Interpretation of a histogram requires expertise in statistical analysis.
Data Quality : Histograms are only as good as the data that is collected. If the data is inaccurate or incomplete, the histogram will not provide accurate analysis.
Limited to One Variable : Histograms are limited to analyzing one variable at a time.

7. Flowchart

A flowchart is a graphical representation of a process that shows the steps involved in completing a task. Flowcharts are widely used in quality management to identify process inefficiencies and to improve the quality of a product or service. A flowchart consists of various symbols that represent different process steps, decision points, and branching paths.

How to Create a Flowchart?

The following are the steps to create a flowchart:

Identify the Process : Identify the process you want to represent in the flowchart.
Determine the Symbols : Determine the symbols you want to use to represent the process steps, decision points, and branching paths.
Draw the Flowchart : Draw the flowchart by placing the symbols in the correct order and connecting them with arrows that show the flow of the process.
Test the Flowchart : Test the flowchart by following the process steps and checking to see if the flowchart accurately represents the process.

Types of Flowcharts

Basic Flowchart : A basic flowchart is the most commonly used type of flowchart. It consists of a set of symbols that represent different process steps and decision points.
Swimlane Flowchart : A swimlane flowchart is used to show the flow of a process across different departments or teams. Each department or team is represented by a separate lane or swim lane.
Data Flow Diagram : A data flow diagram is used to show the flow of data within a system or process. It consists of a set of symbols that represent different data sources, processes, and outputs.

Advantages of Using Flowcharts

Visual Representation : Flowcharts provide a visual representation of a process, which makes it easier to understand and analyze.
Identify Inefficiencies : Flowcharts help identify inefficiencies in a process, which can then be corrected to improve the quality of a product or service.
Standardization : Flowcharts can be used to standardize a process across different teams or departments.
Communication : Flowcharts are an effective communication tool, helping to convey complex processes in a simple and understandable way.

Disadvantages of Using Flowcharts

Time-Consuming : Creating a flowchart can be time-consuming, especially for complex processes.
Limited Scope : Flowcharts are limited to representing a single process, which may not capture all the complexities of a system.
Interpretation : Interpretation of a flowchart requires expertise in process analysis.
Complexity : Flowcharts can become complex and difficult to understand if there are too many symbols or if the process being represented is overly complex.

How to use 7QC Tools

7QC tools, also known as quality control tools, are used to identify and analyze problems in a process and to find solutions to improve the quality of a product or service. Here are some general steps for using 7QC tools:

Identify the Problem : Identify the problem or issue that needs to be addressed. This could be a defect in a product, a bottleneck in a process, or a customer complaint.
Gather Data : Gather data related to the problem. This could include customer feedback, production data, or performance metrics.
Choose the Right Tool : Choose the appropriate QC tool to analyze the data. Different tools are used to analyze different types of data, such as cause-and-effect diagrams for identifying root causes or histograms for analyzing data distribution.
Analyze the Data : Use the chosen tool to analyze the data and identify patterns or trends that may be contributing to the problem.
Develop Solutions : Once the root causes have been identified, brainstorm possible solutions to address the problem.
Implement Solutions : Choose the best solution(s) and implement them. Monitor the process to ensure that the solutions are effective and to make adjustments as needed.
Track Progress : Track progress by monitoring key performance indicators (KPIs) and continue to use QC tools to analyze data and identify opportunities for improvement.

What are 7QC tools?

7QC tools refer to seven quality control tools that are used for problem-solving and continuous improvement in the manufacturing industry. These tools are also known as the 7 basic tools of quality control.

What are the seven basic tools of quality control?

The seven basic tools of quality control are: Flow Charts Check Sheets Pareto Charts Histograms Scatter Diagrams Control Charts Stratification

What is the purpose of 7QC tools?

The purpose of 7QC tools is to provide a structured and systematic approach to identify and eliminate the root cause of problems and improve processes. These tools help to monitor, analyze and control the quality of products and processes.

How are 7QC tools used in the manufacturing industry?

7QC tools are used in the manufacturing industry to continuously monitor and improve the quality of products and processes. These tools are used in a wide range of applications such as quality control, process improvement, and root cause analysis.

What are the benefits of using 7QC tools?

The benefits of using 7QC tools include: Improved quality and efficiency Increased customer satisfaction Reduced costs Improved decision-making Better problem-solving skills

Can 7QC tools be used in non-manufacturing industries?

Yes, 7QC tools can be used in non-manufacturing industries such as healthcare, service, and retail. These tools can be used to identify and eliminate problems in any process that involves the flow of information or goods.

How are 7QC tools different from other quality control methods?

7QC tools are different from other quality control methods in that they provide a structured and systematic approach to problem-solving and continuous improvement. Other quality control methods may not have a systematic approach and may not cover all aspects of quality control.

Best Practice

3G PRINCIPLE 3K PRINCIPLE 3M PRINCIPLE 3R 4M PRINCIPLE Avoid These Common Mistakes on a Job Interview Benefits of Kaizen Business Analysis capacity management Continual improvement Cybersecurity Cycle Time daily work management Examples gemba gembutsu genjitsu Industrial Trainer KAIZEN Kaizen continuous improvement Kaizen principles Kanban Lead Time Lean meaning Muda Mura Muri Objectives philosophy Process Process Analysis Quality Circle R&D RECYCLE Reduce Research and Development REUSE Rockwell hardness Significance Six Sigma Supply Chain Optimization The Secret of Standardization The Toyota 3M Model Total Productive Maintenance What is Capacity Management?

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Quality Control Tools

“A man and his tools make a man and his trade” – Vita Sackville-West

As a Quality Engineer one of the most important skills you need is the ability to solve a problem or improve a process .

To do this successfully, you need the proper tools. In fact, there are 7 specific tool that you must know.

Kaoru Ishikawa once said “ As much as 95% of quality problems can be solved with seven fundamental quantitative tools ”.

These tools were first categorized as Quality Control Tools by Ishikawa in his book Introduction to Quality Control .

Does it seem odd that we’re in the Continuous Improvement section talking about Quality Control & Problem Solving ?

It shouldn’t – problem solving is continuous improvement .

Improvements happen when we solve problems.

So, what are these 7 fundamental tools for problem solving & continuous improvement:

Flow Charts

Check sheets, pareto charts, cause & effect diagrams, control charts, scatter diagrams.

Within this chapter, we will discuss when to use each tool along with how to construct and analyze them.

So why are these seven tools so effective?

They all share two characteristics that make them very effective in problem solving (and continuous improvement).

First – they are all visual tools . You’ve heard the saying – a picture is worth a thousand words . These tools prove that point.

Second – they all deal with facts or data , not opinions or conjecture.

Problems are solved with facts and data .

Improvements are made with facts and data .

When we combine a fact-based approach with a visual tool we are able to solve problems more easily .

The other comment I’ll make about these tools is that they are often used in combination with each other, and I’ll provide examples of that as we go through each tool.

Lastly, I wanted to provide a link to a Youtube Playlist for the 7 QC Tools .

Let’s get started with the flow diagram.

A Flow Chart is a visual tool that depicts the flow or sequence of a process . This can include the flow of information, tasks, people, material or decision .

The Flow Chart’s value lies in its ability to visually communicate the steps and sequence of a process.

The Flow Chart makes the complex become simple, and promotes a common understanding of a process, which is the foundation for improvement.

The Flowchart is an excellent starting point in the Problem-Solving Process , as it allows your problem-solving team to see the entire process and identify improvements.

Flow Charts are also powerful in their application. You can make them super detailed, or you can stay at a high level, depending on the goal of the flow chart.

One common mistake with flow charts is that they are often created in a conference room, away from where the process actually occurs.

There will always be a difference between the “theoretical” process that you believe is occurring, and the actual process that’s occurring.

You must go and see for yourself (Gemba), to truly understand the actual process. Go and talk with the folks who actually work the process to truly understand the process.

Common Flow Chart Symbols

To facilitate the communication process, it’s generally acceptable to use standard symbols with your flow charts. This will ensure consistency and reduce miss-communication.

Flow Chart Example

Let’s say we’re a manufacturer of toasters, and we’ve been asked to put together a high-level flow diagram of the entire manufacturing process.

Remember, each of these steps in the process could have its own more detailed flow chart.

Solving problems and making improvements requires data . Period.

The check sheet is a simple tool for collecting, organizing and analyzing data .

I would argue that when you combine the simplicity of the check sheet with the potential value associated with the collected data that the check sheet is the most powerful QC tool.

A Check Sheet is normally a table with defined rows and columns where the data collected is usually 1 check mark within each category. However, you can modify this concept of a data collection tool to meet a variety of different needs.

The example above is very simply. Almost too simple.

The best check sheets contain something more than data, they contain meta data .

Meta data is data about the data – like who collected the data, when (date, shift or time) the data was collected, and where (location, line, equipment number) there data collection took place.

Without this meta data, the actual data can become ambiguous and lose its integrity ( think data integrity ).

A good check sheet is designed to have clear, unique & unambiguous data collection categories . If necessary , standard work (work instructions) can be created and distributed with the check sheet to ensure data is collected appropriately.

This can include illustrations to go along with the check sheet.

Let’s say we go back to our toaster example and see what a check sheet for final assembly rejects might look like. This also includes the meta data and illustrations to go along with it.

This data can then be fed into a pareto chart to identify the “critical few” defects (Hint, it’s the electrical defect).

The Pareto Chart is a bar chart that allows for analysis of data in search of the Pareto Principle or the 80/20 rule .

The 80/20 rule was first identified by an Italian researcher, Vilfredo Pareto , who was studying wealth and land ownership in Europe, and found that 80% of the land in Europe was owned by 20% of the population.

What Pareto did not realize is that this 80/20 rule is a universal principle , and can be applied to a lot more than wealth distribution.

The 80/20 rule was popularized by Joseph Juran , who names the Pareto Chart after Vilfredo Pareto.

Juran went on to say that the Pareto Chart helps us separate the vital few from the trivial many .

Essentially, the pareto chart is a prioritization tool that allows us to focus on the issues that are causing the biggest problem, and thus maximize our impact.

Mechanically, the Pareto Chart is simply a bar chart that displays data that from various discrete categories . This data might come from a check sheet .

The categories of data are typically arranged from greatest to least on the X-axis.

The Y-axis is a count of defects , but this number can be cost , or any other variable. Pareto Charts also frequently include a cumulative frequency line to assist in the analysis.

Let’s analyze this our Pareto Chart quickly. There are 15 total defect conditions (A-N).

The top 3 defects (Defects A, B & C) make up only 20% (3 out of 15) of the defect conditions, however they contribute to 72% of the total number defects .

IF we could eliminate just these 3 defect conditions, we could eliminate 72% of the defects.

That’s the Pareto Chart and the 80/20 Rule at work.

The Cause and Effect diagram is a visual tool to explore all the potential factors that may be causing or contributing to a particular problem (effect).

This tool was popularized by Kaoru Ishikawa and allows you to graphically capture all the potential causes of a problem , then select those which require further investigation.

The Cause & Effect Diagram is also commonly referred to as the Fishbone Diagram, the Ishikawa Diagram, Cause & Effect Matrix, C&E Diagram or the C-E Diagram.

The cause and effect diagram can be completed as part of a 3-step process.

Step 1 is to agree on the problem statement, this is the negative “effect” you’re experiencing. This might seem simple, but it’s important to align on the problem statement prior to continuing.

Step 2 is the brainstorming process which is facilitated by the 8M’s of the fishbone process (below) , and should be used with a process flow chart and 5-Why technique to truly identify causes, and not simply stop at symptoms.

The Ishikawa diagram has 8 major categories (The 8M’s) that might contribute to your problem which include:

Man – How do Humans interact with your product/process/equipment and how could that contribute to your problem.
Machine – What type of equipment or machinery are used in your process and how could a deviation here contribute to your problem.
Method – What type of process/procedure do you follow and what potential issues might contribute to your problem.
Materials – What type of material is used and how could any material deviations contribute to your problem.
Mother Nature – How does the environment interact with your product/process in a way that might contribute to your problem.
Measurements – What type of measurements and measurement equipment do you use and how might this relate to the problem.
Management – What are the attitudes, outlooks & priorities of management and how could this be contributing to your problem.
Maintenance – What type of maintenance/calibration activities are being performed on your machines or measurement equipment that could be contributing to your problem.

Once you’ve brainstormed and created a list of potential causes and contributing factors , you can move on to Step 3.

Step 3 is to prioritize an action plan of investigation steps that will help confirm or exclude the potential causes and factors.

Another underrated characteristic of the Cause & Effect Diagram is its effectiveness as a communication aid . Especially when you’re dealing with a very complex issue.

Let’s go through a quick example

Cause & Effect Example

Let’s say you’re a Toaster Manufacturer and you received a customer complaint for a toaster that is not toasting.

Step 1 in the Cause and Effect process is to agree on a problem statement : The Toaster is not toasting.

With more data we could refine this problem statement to improve the brainstorming, but for now we will leave it generic.

We can always refine the problem statement as the investigation progresses.

Then we can go through the brainstorming process using the 8M’s to identify potential causes and contributing factors that require further investigation.

You can see here we’ve excluded maintenance, machines and Management, and identified potential causes and contributing factors in other areas.

We can also prioritize the most likely contributing factors which should give the investigation actions to conclude the root cause of the problem.

For example, we agree that the most likely root cause is a faulty heating element, and we will focus our investigation here first.

A control chart is a statistically based tool that analyzes the variation of a process .

A control chart is a time-based line graph that reflects the behavior of a process over time including normal variation and any special cause variation.

A control chart can also be described as a visual communication tool that graphs analyzed data in real-time and reflects the stability of a process .

Remember – A good process is a stable process – we want stability.

An unstable process is unpredictable and results in both problems, and is a clear opportunity for improvement.

The details of the control chart, including the various kinds, how to create them, and how to analyze them can be found in the Statistical Process Control chapter.

This section is a high-level summary of the control chart , along with how it can be used to solve problems and improve processes.

Control Chart with control limits and variation

The control chart contains upper and lower control limits that are statistically based, which allow the user to identifying instances where the process appears to be behaving abnormally.

These control limits and centerline represent the “voice of the process” and are simply a reflection of the process – both the average value of your process and the natural variation of the process.

The primary benefit of a control chart is its unique ability to separate the normal variation within your process from the special cause variation.

Special cause variation causes problems . It represents an opportunity for improvement .

Normal cause variation can also be an opportunity for improvement, however reducing normal cause variation can be difficult because it can often require making substantial changes to the process itself.

Using control charts allows you to proactively monitor your process , detect when a problem is occurring (or has occurred), which is the starting point for an improvement project.

A control chart is like a scoreboard . It can be used at the end of an improvement project to indicate if an improvement was successful or not.

A Scatter diagram is a visual analysis tool that is meant to reflect the possible relationship between two variables .

The Scatter Plot visually plots pairs of data on an X-Y graph in order to reveal the relationship between the data sets.

This section will summarize the scatter diagram at a high level, and the Relationship Between Variables Chapter in Statistics will cover this topic in detail.

The relationship between the two variables can be positive, negative or non-existent. The strength of the relationship can also be analyzed visually by how closely the points fall on the line of best fit.

The strength of that relationship can be expressed mathematically using the Pearson Correlation Coefficient , which is a number that ranges from a strong positive correlation (+1) to a strong negative correlation (-1).

Scatter Plots require pairs of data , one set of data in the pair is normally referred to as the Independent Variable (X) with the second half of the data set being your observed measurement also known as the Dependent Variable (Y).

When a Positive Correlation exists between two variables a positive increase can be expected from the dependent variable (Y) when the intendent variable (X) increases.

The opposite is true for the Negative correlation . A negative correlation means that when the independent variable (X) increases, the dependent variable (Y) will decrease.

No Correlation results when the two variables have no measurable effect on each other. That is a change in X, does not impact Y.

The scatter plot is often used in the problem-solving process when we’re studying a process to understand which input variables (independent variables) are contributing to a negative outcome in a response variable (dependent variable).

This chart is fairly easy to create using tools like excel or other statistical analysis packages, we can collect data using a check sheet, and we’re specifically collecting paired data.

Let’s take a look at an example of how we could use a scatter diagram to analyze two variables and assess the relationship between them.

Scatter Diagram Example

FYI – below is a hypothetical situation. I’ve created this data as an example, however I believe the conclusions are likely accurate 😊.

Let’s say that I’m studying the various factors that affect performance on the CQE Exam .

I hypothesis that there is a relationship between quiz scores and the ultimate exam score.

So I run an experiment where I work with 14 people and have them take a quiz before the exam to determine if a relationship exists between these two variables .

Ultimately, I’d like to be able to predict their exam score based on the quiz score .

So I’ve taken these pairs of data, with the Quiz Score as the Independent Variable (X), and the Exam Score as the Dependent Variable and analyzed them using a Scatter Diagram.

Each pair of data represents a dot on the Scatter Plot, and I’ve included a linear regression line to reflect the relationship between these variables.

This scatter diagram indicates that a strong positive correlation exists between these two variables (r = 0.8).

If you do well on the quiz, you’re likely going to do well on the exam.

But can doing well on a quiz CAUSE you to do well on the exam. No.

This is a good opportunity to warn you about the difference between correlation and causation.

This is an example of correlation without causation.

These two variables highly correlate with each other because there are other factors like study time, study habits, or job performance that are CAUSING you to do well on both variables.

So, if you really want to do well on the exam, create healthy study habits, invest your time to study, reflect on what you’ve learned, put that into action and you will do well on the exam (and the quiz).

It’s not to say that this quiz is without value though. The quiz is an indicator of potential success on the exam .

You might have indicators like this in your process that perhaps do not relate back to quality or cost, but they can indicate if a problem exists.

The Histogram is a tool used to visualize the distribution of continuous data .

More specifically, a Histogram is a type of Bar Chart that graphs the frequency of occurrence of continuous data and is a useful tool for displaying, summarizing and analyzing data .

Variation is all around us.

Every process or product has some level of variation.

Every data set you collect will have variation in it, and this variation will exist in a “Pattern”.

And the best way to see or understand this Pattern of variation is to graph your data using a Histogram.

There are different patterns of variation that may be revealed in a Histogram. The most common distributions, and their analysis, are discussed within the Probability Distribution section of Statistics , and 3 examples are shown below.

Typically, a distribution can be characterized by the central tendency of the data (Mean, Median Mode), and the “ variation ” ( range, standard deviation, etc ) within the data.

Within the next section on Statistics , you’ll learn that many concepts and tools assume that data is normally distributed .

The histogram is a visual tool you can use as a gut check to see if your data set is approximately normal .

Lastly, in terms of creating a histogram, this can be done in excel, and many statistical software packages will create histograms for you, so I won’t go into that detail here.

As a Quality Engineer one of the most important skills you can have, is the ability to solve a problem or improve a process .

To do this successfully, you need to be able to apply the 7 QC Tools.

These 7 tools combine a fact-based approach with a visual tool that makes solving problems easier.

Below is a quick and simple review of the definition for each of the 7 tools discussed within this chapter.

A Flow Chart is a visual tool that depicts the flow or sequence of a process . This can include the flow of information, tasks, people, parts, material , etc.

A Histogram is a type of Bar Chart that graphs the frequency of occurrence of continuous data and is a useful tool for displaying, summarizing and analyzing data .

Next Chapter: Continuous Improvement Techniques

Green Belt Academy

Helping You become a Certified Six Sigma Green Belt as Quickly and Painlessly as Possible!!

“A man and his tools make a man and his trade” – Vita Sackville-West

As a Six Sigma Green Belt, one of the most important skills you need is the ability to solve a problem or improve a process .

To do this successfully, you need the proper tools. In fact, there are 7 specific tools that you must know.

Kaoru Ishikawa once said “ As much as 95% of quality problems can be solved with seven fundamental quantitative tools ”.

These tools were first categorized as Quality Control Tools by Ishikawa in his book Introduction to Quality Control .

Improvements happen when we solve problems.

So, what are these 7 fundamental tools for problem solving & continuous improvement? Flow Chart

Check Sheet
Pareto Chart
Cause & Effect Diagram
Control Chart
Scatter Diagram

Get The Free Quiz For The 7 QC Tools

So why are these seven tools so effective?

They all share two characteristics that make them very effective in problem solving (and continuous improvement).

First – they are all visual tools . You’ve heard the saying – a picture is worth a thousand words . These tools prove that point.

Second – they all deal with facts or data , not opinions or conjecture.

Problems are solved with facts and data .

Improvements are made with facts and data .

When we combine a fact-based approach with a visual tool, we are able to solve problems more easily .

The other comment I’ll make about these tools is that they are often used in combination with each other, and I’ll provide examples of that as we go through each tool.

Let’s get started with the flow diagram.

1. Flow Chart

A Flow Chart is a visual tool that depicts the flow or sequence of a process . This can include the flow of information, tasks, people, material or decision .

The Flow Chart’s value lies in its ability to visually communicate the steps and sequence of a process.

The Flow Chart makes the complex become simple, and promotes a common understanding of a process, which is the foundation for improvement.

The Flowchart is an excellent starting point in the Problem-Solving Process , as it allows your problem-solving team to see the entire process and identify improvements.

Flow Chart Example:

Let’s say we’re a manufacturer of toasters, and we’ve been asked to put together a high-level flow diagram of the entire manufacturing process.

Remember, each of these steps in the process could have its own more detailed flow chart.

2. Check Sheet

Solving problems and making improvements requires data . Period.

The check sheet is a simple tool for collecting, organizing and analyzing data .

The best check sheets contain something more than data, they contain meta data .

Meta data is data about the data – like who collected the data, when (date, shift or time) the data was collected, and where (location, line, equipment number) there data collection took place.

Without this meta data, the actual data can become ambiguous and lose its integrity ( think data integrity ).

Let’s say we go back to our toaster example and see what a check sheet for final assembly rejects might look like. This also includes the meta data and illustrations to go along with it.

This data can then be fed into a pareto chart to identify the “critical few” defects (Hint, it’s the electrical defect).

3. Pareto Chart

The Pareto Chart is a bar chart that allows for analysis of data in search of the Pareto Principle or the 80/20 rule .

The 80/20 rule was popularized by Joseph Juran , who names the Pareto Chart after Vilfredo Pareto.

Juran went on to say that the Pareto Chart helps us separate the vital few from the trivial many .

Mechanically, the Pareto Chart is simply a bar chart and the categories of data are typically arranged from greatest to least on the X-axis.

The Y-axis is a count of defects , but this number can be cost , or any other variable. Pareto Charts also frequently include a cumulative frequency line to assist in the analysis.

In this example , the top 3 defects (Defects A, B & C) make up only 20% (3 out of 15) of the defect conditions, however they contribute to 72% of the total number defects . If we could eliminate just these 3 defect conditions, we could eliminate 72% of the defects. That’s the Pareto Chart and the 80/20 Rule at work.

4. Cause & Effect Diagram

The Cause and Effect diagram is a visual tool to explore all the potential factors that may be causing or contributing to a particular problem .

This tool was popularized by Kaoru Ishikawa and allows you to graphically capture all the potential causes of a problem , then select those which require further investigation.

The Cause & Effect Diagram is also commonly referred to as the Fishbone Diagram, the Ishikawa Diagram, Cause & Effect Matrix, C&E Diagram or the C-E Diagram.

The Ishikawa diagram has 8 major categories (The 8M s) that might contribute to your problem which include:

Mother Nature
Measurements
Maintenance

Cause & Effect Example:

Let’s say you’re a Toaster Manufacturer and you received a customer complaint for a toaster that is not toasting.

We can go through the brainstorming process using the 8M’s to identify potential causes and contributing factors that require further investigation.

You can see here we’ve excluded maintenance, machines and Management, and identified potential causes and contributing factors in other areas.

We can also prioritize the most likely contributing factors which should give the investigation actions to conclude the root cause of the problem.

5. Control Chart

A control chart is a statistically based tool that analyzes the variation of a process .

A control chart is a time-based line graph that reflects the behavior of a process over time including normal variation and any special cause variation.

A control chart can also be described as a visual communication tool that graphs analyzed data in real-time and reflects the stability of a process .

Remember: A good process is a stable process; we want stability.

The details of the control chart, including the various kinds, how to create them, and how to analyze them can be found in the Statistical Process Control (SPC) chapter.

The control chart contains upper and lower control limits that are statistically based, which allow the user to identifying instances where the process appears to be behaving abnormally.

Using control charts allows you to proactively monitor your process , detect when a problem is occurring (or has occurred), which is the starting point for an improvement project.

A control chart is like a scoreboard . It can be used at the end of an improvement project to indicate if an improvement was successful or not.

6. Scatter Diagram

A Scatter diagram is a visual analysis tool that is meant to reflect the possible relationship between two variables .

The Scatter Plot visually plots pairs of data on an X-Y graph in order to reveal the relationship between the data sets.

FYI – below is a hypothetical situation. I’ve created this data as an example, however I believe the conclusions are likely accurate 😊.

Let’s say that I’m studying the various factors that affect performance on the CSSGB Exam .

I propose a hypothesis that there is a relationship between quiz scores and the ultimate exam score.

So I run an experiment where I work with 14 people and have them take a quiz before the exam to determine if a relationship exists between these two variables .

Ultimately, I’d like to be able to predict their exam score based on the quiz score .

So I’ve taken these pairs of data, with the Quiz Score as the Independent Variable (X), and the Exam Score as the Dependent Variable and analyzed them using a Scatter Diagram.

This scatter diagram indicates that a strong positive correlation exists between these two variables (r = 0.8).

If you do well on the quiz, you’re likely going to do well on the exam.

But can doing well on a quiz CAUSE you to do well on the exam. No.

This is a good opportunity to warn you about the difference between correlation and causation.

This is an example of correlation without causation.

These two variables highly correlate with each other because there are other factors like study time, study habits, or job performance that are CAUSING you to do well on both variables.

It’s not to say that this quiz is without value though. The quiz is an indicator of potential success on the exam .

7. Histogram

The Histogram is a tool used to visualize the distribution of continuous data .

More specifically, a Histogram is a type of Bar Chart that graphs the frequency of occurrence of continuous data and is a useful tool for displaying, summarizing and analyzing data .

Variation is all around us. Every process or product has some level of variation.

Every data set you collect will have variation in it, and this variation will exist in a “Pattern”.

And the best way to see or understand this Pattern of variation is to graph your data using a Histogram.

There are different patterns of variation that may be revealed in a Histogram. The most common distributions, and their analysis, are discussed within the Probability Statistical Distributions (Chapter 12) of the Green Belt Master Class .

Typically, a distribution can be characterized by the central tendency of the data (Mean, Median Mode), and the “ variation ” ( range, standard deviation, etc ) within the data.

The Normal Distribution is the most common type of statistical distributions.

The histogram is a visual tool you can use as a gut check to see if your data set is approximately normal .

As a Six Sigma Green Belt, one of the most important skills you can have, is the ability to solve a problem or improve a process .

To do this successfully, you need to be able to apply the 7 QC Tools.

These 7 tools combine a fact-based approach with a visual tool that makes solving problems easier.

Below is a quick and simple review of the definition for each of the 7 tools discussed within this chapter.

1. A Flow Chart is a visual tool that depicts the flow or sequence of a process . This can include the flow of information, tasks, people, parts, material , etc.

2. The check sheet is a simple tool for collecting, organizing and analyzing data .

3. The Pareto Chart is a bar chart that allows for analysis of data in search of the Pareto Principle or the 80/20 rule .

4. The Cause and Effect diagram is a visual tool to explore all the potential factors that may be causing or contributing to a particular problem (effect).

5. A control chart is a time-based line graph that reflects the behavior of a process over time including normal variation and any special cause variation.

6. A Scatter diagram is a visual analysis tool that is meant to reflect the possible relationship between two variables .

7. A Histogram is a type of Bar Chart that graphs the frequency of occurrence of continuous data and is a useful tool for displaying, summarizing and analyzing data .

Next: Kano Model

TECHIEQUALITY

7qc tools for problem solving | what are 7 qc tools.

7QC Tools for Problem Solving techniques are generally used in manufacturing, Non-manufacturing industries, and service sectors to resolve problems.

Download 7-QC Tools Template/ Format

Definition and History:-

The 7QC Tools (Also Known as “Seven Basic Tools of Quality”) originated in Japan. First emphasized by Kaoru Ishikawa, a professor of engineering at Tokyo University and the father of “quality circles”. These tools are used to solve critical quality-related issues. You can use the 7 basic tools of quality to help understand and solve problems or defects in any industry. With the help of Excel, you can plot the graphs / Diagrams to resolve the daily quality problems. I will help you to understand the basic ideas and knowledge of 7QC Tools and their usage.

For solving problems seven QC tools are used Pareto Chart, Cause & Effect Diagram, Histogram, Control Charts, Scatter Diagrams, Graphs/Process Flow Diagram, and Check Sheets. All these tools are important tools used widely in the manufacturing field to monitor the overall operation and continuous process improvement. seven QC tools are used to find out the Root cause of the problem and implement the action plan to improve the process efficiency.

7QC tools are:-

Pareto Chart
Cause and effects diagram
Scatter Diagram
Control Chart
Check Sheet
PFD(Process Flow diagram)/Graphs

Benefits of 7QC Tools:-

Improve management decisions.
Simple and easy for implementation
Continuous quality improvement
Quick results
Enhances customer satisfaction through improved quality product
Reduce cycle time and improve efficiency
Control cost of poor quality / Cost of quality
Reduce defects and optimize the production
Reduce variations and improve the quality of Products
Encouragement of teamwork and confidence
Enhancement of customer focus.

Pareto Chart:-

A Pareto Chart is named after the Italian Economist Vilfredo Pareto. It is a type of chart that contains both bars and a line graph, where the individual values are represented in the bar graph in descending order (largest to smallest value) and the cumulative percentage is represented in the line graph.

Click here to learn “How to Plot Pareto Chart In Excel”.

Understanding the Pareto Chart principle (The 80/20 rule):

The Pareto principle is also known as the 80/20 rule derived from the Italian Economist Vilfredo,

The principle is understood as –

20% of the input creates 80% of the results

80 % of the effects come from 20% of the causes.

In the above Pareto Chart[Figure-1], we can see the cumulative% in the line graph, According to the Pareto Chart principle 80/20 rule, the 80% cumulative in the line graph is filling under the low hardness, which means BH, Damage, SH and Low hardness defers are coving the 80% of contribution over total types of defects. And those 80 % of contributions were due to the 20% caused.

Histogram:-

The histogram is one of the 7QC tools, which is the most commonly used graph to show frequency distribution.

Helps summarize data from a process that has been collected over a period of time.

Click here to know the “How to Plot Histogram in Excel:

Fish-bone Diagram/Cause and Effects /Ishikawa Diagram:-

The cause and Effects Diagram looks like a fish that’s why it’s called Fish-bone Diagram, also called the Ishikawa diagram.

It’s a visualization tool for categorizing the potential causes of a problem in order to identify its root causes.

CFT members are identifying the potential cause through the Brainstorming process of individuals and together.

The Potential cause is related w.r.t below as

Environment
Measurement

Scatter diagram:-

The scatter diagram graphs pairs of variable data, with one variable on each axis, to look for a relationship between them. If the variables correlate, the points will fall along a line or curve. The better the correlation, the more points will strongly cluster to the line. It generally gives the idea of the correlation between the variables.

In the above figure-4, the positive and Negative correlation is only due to the direction, and in both the correlation, points are clustered to the line but in the last figure in figure-4, Points are not clustered to the line but spread over the X and Y-axis.

Control Chart:-

A line on a control chart is used as a basis for judging the stability of a process. If the observed points are beyond a control limit then it is evidence that special causes are affecting the process.

Control Charts can be used to monitor or evaluate a process.

There are basically two types of control charts, those for variable data and those for attributes data.

Click here to learn more about the Control Chart and Statistical Process Control.

Benefits: -Higher Quality, Lower Unit Cost, Higher effective Capability, etc.

Selection of Control Charts based on Attribute / Variable Type Data:-

Calculation of Average and Range Charts-

Click here to know the details.

The formula of the Attributes Control Chart:-

Click here to learn the formula and calculation.

Nomenclature of Control Chart:-

Check Sheet:-

Check Sheet is a simple document used for collecting data in real time. Variable or Attribute type data is collected through a Check sheet. A check sheet generally helps to make the decision on the basis of a fact and to collect the data for analysis and evaluation.

Sample check Sheet:-

Process Flow diagram/Graphs:-

A process flow diagram is a diagram used to indicate the general flow of plant processes and equipment.

The 7QC tools are the most commonly used tool in the industry for improvement, With the help of the 7QC tools you can understand the process/activities, analyze the data, and interpret the result/graph/output.

Which are the 7 QC tools?

The seven QC tools are

Fishbone diagram
PFD(Process Flow diagram)/Graphs /Stratification

Useful Article:

why why analysis methodology | 5-why analysis step by step guide

Rework vs Repair |IATF Requirement for Control of Reworked/ Repaired Product

How to plot the Run Chart in Minitab

Run Chart Example | Concept & Interpretation of Result with Case Study | Industrial Example:

Thank you for reading..keep visiting Techiequality.Com

I hope the above article “7QC Tools for Problem Solving” is useful to you…

7QCs: An Introduction to the Seven Basic Tools of Quality Control

Sample pareto chart, one of the seven basic tools of quality control.

Quality control. Of course it is important. When producing parts or products, the ability to monitor, troubleshoot, and adjust manufacturing processes is necessary for companies to remain efficient and competitive. If products are to be made consistently to a required standard, the methods of manufacturing must be measurable, adjustable, and repeatable.

In order to achieve these standards, logical, data driven approaches to finding acceptable solutions can be used, such as the 7QC tools, or the Seven Basic Tools of Quality Control. The 7QC tools are statistical tools that help individuals, organizations, and businesses resolve quality issues for products and processes. They are called basic tools because they are suitable for people with little formal training in statistics and because they can be used to solve the vast majority of quality-related issues.

7QC tools include:

Check Sheets

Check sheets are used to collect data in order to understand the qualitative and quantitative variables that can affect a process. When recording data on a check sheet, check marks or tally marks are used to indicate the amount of what is being collected, which helps in understanding the progress, defect patterns, and even causes for defects.

Control Charts

Control charts are graphs used to represent process performance over time. Subgroups of data points are collected and compiled together within a short interval of time. The average of the data points within a subgroup is represented as a single dot in the control chart. The amount of variation that exists within a sample data set is the standard deviation, which is used to determine the control limits. When the subgroups exist beyond the control limits or exhibit specific patterns or trends, then the process is said to be “out-of-control.”

Fishbone Diagrams

Fishbone diagrams, also referred to as cause and effect diagrams, are a quality control brainstorming tool used to help identify the root cause or causes of an issue by looking at all possible variables.

When using these diagrams, a central issue or focal point, such as a defect or quality problem, is placed at the head of the “fish.” The “bones of the fish” serve as a way to visually organize all possible variables, or causes, that may have caused the central issue, and sort ideas into categories to investigate further.

Histograms are a type of bar graph used to represent the frequency distribution, or how often each different value in a set of data occurs. It is created by grouping the data you collect into “cells” or “bins.” The histogram is the most commonly used graph to assess process behavior and demonstrate if the data follow a normal distribution, or bell-shaped curve.

Pareto Charts

Pareto charts are a combination of bar and line graphs that provide a visual representation of how often the various issues affecting a process are occurring. Pareto chart derives its name from the use of the Pareto Principle, which states “80% of the effect comes from 20% of the causes.” Using this chart, professionals can decide where to place priority and focus.

Scatter Diagrams

Scatter diagrams, also called scatter plots, are graphs used to visually represent the relationship between two variables in order to quickly identify the correlation between them.

This tool is used to determine the type of relationship that exists between the inputs to the process, or process characteristics, and the outputs from a process, or product characteristics.

Stratification

Stratification is a method of dividing data into subcategories and classifying data based on group, division, class, or levels that helps in deriving meaningful information to understand an existing problem.

To learn more about these Seven Basic Tools of Quality Control, and to learn how to apply these tools to solving quality problems by viewing examples, check out the online 7QC courses in the THORS Academy Library , brought to you by THORS eLearning Solutions.

Sample fishbone diagram, used to brainstorm probable root causes of manufacturing problems.

Fishbone diagrams help solve manufacturing problems

There can be many opinions as to what the root cause of a problem is, especially when there is a team tasked with solving an issue. A cause…

Diagram depicting stratified sampling where data is collected and sorted from a population into smaller logical segments

Essential Quality Terms Used in 7QC Tools

The 7QC tools are statistical tools that help individuals, organizations, and businesses resolve quality issues for products and processes. To utilize the 7QC tools it…

CMM Measurement Optimization: Best Practices for Accurate Results

Throughout the years, Coordinate Measuring Machines (CMMs) have earned a reputation for delivering accurate measurement results better than many other traditional metrologies. Implementing some best…

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Productivity

7 qc tools for quality improvement.

*Optional training delivery method for this course: Remote Online Training (ROT) or Face-to-Face (F2F) !

COURSE DESCRIPTION

7 QC Tools For Quality Improvement course provides an in-depth study of the 7 Basic QC (Quality Control) Tools. They are scientific management tools, used worldwide by almost every organizations to collect and analyze data/facts for the purpose of quality improvements. The 7 QC Tools are simple tools, low-cost and easy-to-use; but they are powerful tools that forms the critical foundation for all problem solving and quality improvement activities. Once mastered, these tools will serve as the solid foundation for individuals’ and team’s root cause analyses, problem solving sessions, and continuous improvement projects.

Manufacturing and service industry professionals, quality technicians and auditors, and industrial engineers will all benefit from understanding these tools. In addition to the foundational principles and concepts, this training examines practical real-world applications of the 7 QC Tools in the workplace. Participants will be provided with value-added MS Excel templates. These templates will help construct those QC Tools fast, easy and accurately.

This course is a MUST for all Quality Assurance staff such as Quality Engineers, Technicians, QC Leaders and also serve as a foundational course for Data Analysis & Lean Six Sigma practitioners.

CERTIFICATION

No certification.

Certificate of Achievement (for those who scored 80% and above for post-test) or Certificate of Attendance.

LEARNING OUTCOMES

At the end of the course, participants will be able to:

Describe the benefits and power of each of the 7 QC Tools and its applications.
Construct the QC tools accurately and fast using Microsoft Excel templates.
Interpret , analyze and make accurate quality improvement decisions using the correct tools
Perform data analysis and process monitoring using the QC tools
Solve problems systematically and effectively.
Experience the Quality Control Circle (QCC) team dynamics in solving problems.
Make convincing presentations with the data collected from their workplace.

COURSE OUTLINE

Please see eBrochure above for more information.

To register, please Whatsapp : +60-19-502 2718 or email us at [email protected]

Course Features

Skill level All level
Language English
Students 1632
Assessments Yes

Quality Control Circle (QCC) / Innovative & Creative Circle (ICC)

KAIZEN Strategies for Quality and Productivity Improvement

Measurement System Analysis (MSA)

Statistical Process Control -Level 1 (SPC1)

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7 Powerful Problem-Solving Root Cause Analysis Tools

The first step to solving a problem is to define the problem precisely. It is the heart of problem-solving.

Root cause analysis is the second important element of problem-solving in quality management. The reason is if you don't know what the problem is, you can never solve the exact problem that is hurting the quality.

Sustainable Compliance for Out of Specifications (OOS) Results, Deviations, and Corrective and Preventive Actions (CAPA)

Manufacturers have a variety of problem-solving tools at hand. However, they need to know when to use which tool in a manner that is appropriate for the situation. In this article, we discuss 7 tools including:

The Ishikawa Fishbone Diagram (IFD)
Pareto Chart
Failure Mode and Effects Analysis (FMEA)
Scatter Diagram
Affinity Diagram
Fault Tree Analysis (FTA)

1. The Ishikawa Fishbone Diagram IFD

The model introduced by Ishikawa (also known as the fishbone diagram) is considered one of the most robust methods for conducting root cause analysis. This model uses the assessment of the 6Ms as a methodology for identifying the true or most probable root cause to determine corrective and preventive actions. The 6Ms include:

Measurement,
Mother Nature- i.e., Environment

Related Training: Fishbone Diagramming

2. Pareto Chart

The Pareto Chart is a series of bars whose heights reflect the frequency or impact of problems. On the Chart, bars are arranged in descending order of height from left to right, which means the categories represented by the tall bars on the left are relatively more frequent than those on the right.

Related Training: EFFECTIVE INVESTIGATIONS AND CORRECTIVE ACTIONS (CAPA) Establishing and resolving the root causes of deviations, problems and failures

This model uses the 5 Why by asking why 5 times to find the root cause of the problem. It generally takes five iterations of the questioning process to arrive at the root cause of the problem and that's why this model got its name as 5 Whys. But it is perfectly fine for a facilitator to ask less or more questions depending on the needs.

Related training: Accident/Incident Investigation and Root Cause Analysis

4. Failure Mode and Effects Analysis (FMEA)

FMEA is a technique used to identify process and product problems before they occur. It focuses on how and when a system will fail, not if it will fail. In this model, each failure mode is assessed for:

Severity (S)
Occurrence (O)
Detection (D)

A combination of the three scores produces a risk priority number (RPN). The RPN is then provided a ranking system to prioritize which problem must gain more attention first.

Related Training: Failure Mode Effects Analysis

5. Scatter Diagram

A scatter diagram also known as a scatter plot is a graph in which the values of two variables are plotted along two axes, the pattern of the resulting points revealing any correlation present.

To use scatter plots in root cause analysis, an independent variable or suspected cause is plotted on the x-axis and the dependent variable (the effect) is plotted on the y-axis. If the pattern reflects a clear curve or line, it means they are correlated. If required, more sophisticated correlation analyses can be continued.

Related Training: Excel Charting Basics - Produce Professional-Looking Excel Charts

6. Affinity Diagram

Also known as KJ Diagram, this model is used to represent the structure of big and complex factors that impact a problem or a situation. It divides these factors into small classifications according to their similarity to assist in identifying the major causes of the problem.

7. Fault Tree Analysis (FTA)

The Fault Tree Analysis uses Boolean logic to arrive at the cause of a problem. It begins with a defined problem and works backward to identify what factors contributed to the problem using a graphical representation called the Fault Tree. It takes a top-down approach starting with the problem and evaluating the factors that caused the problem.

Finding the root cause isn't an easy because there is not always one root cause. You may have to repeat your experiment several times to arrive at it to eliminate the encountered problem. Using a scientific approach to solving problem works. So, its important to learn the several problem-solving tools and techniques at your fingertips so you can use the ones appropriate for different situations.

ComplianceOnline Trainings on Root Cause Analysis

P&PC, SPC/6Sigma, Failure Investigation, Root Cause Analysis, PDCA, DMAIC, A3 This webinar will define what are the US FDA's expectation for Production and Process Control / Product Realization, the use of statistical tehniques, 6 sigma, SPC, for establishing, controlling , and verifying the acceptability of process capability and product characteristics, product acceptance or validation and other studies. Non-conformance, OOS, deviations Failure Investigations, and Root Cause Analysis, PDCA, DMAIC, and similar project drivers to improvement, A# and similar dash boards.

Accident/Incident Investigation and Root Cause Analysis If a major workplace injury or illness occurred, what would you do? How would you properly investigate it? What could be done to prevent it from happening again? A properly executed accident/incident investigation drives to the root causes of the workplace accident to prevent a repeat occurrence. A good accident/incident investigation process includes identifying the investigation team, establishing/reviewing written procedures, identifying root causes and tracking of all safety hazards found to completion.

Root Cause Analysis - The Heart of Corrective Action This presentation will explain the importance of root cause analysis and how it fits into an effective corrective and preventive action system. It will cover where else in your quality management system root cause analysis can be used and will give examples of some of the techniques for doing an effective root cause analysis. Attendees will learn how root cause analysis can be used in process control.

Addressing Non-Conformances using Root Cause Analysis (RCA) RCA assumes that systems and events are interrelated. An action in one area triggers an action in another, and another, and so on. By tracing back these actions, you can discover where the issue started and how it grew into the problem you're now facing.

Introduction to Root Cause Investigation for CAPA If you have reoccurring problems showing up in your quality systems, your CAPA system is not effective and you have not performed an in-depth root cause analysis to be able to detect through proper problem solving tools and quality data sources, the true root cause of your problem. Unless you can get to the true root cause of a failure, nonconformity, defect or other undesirable situation, your CAPA system will not be successful.

Root Cause Analysis and CAPA Controls for a Compliant Quality System In this CAPA webinar, learn various regulations governing Corrective and Preventive Actions (CAPA) and how organization should collect information, analyze information, identify, investigate product and quality problems, and take appropriate and effective corrective and/or preventive action to prevent their recurrence.

Root Cause Analysis for CAPA Management (Shutting Down the Alligator Farm) Emphasis will be placed on realizing system interactions and cultural environment that often lies at the root of the problem and prevents true root cause analysis. This webinar will benefit any organization that wants to improve the effectiveness of their CAPA and failure investigation processes.

Root Cause Analysis for Corrective and Preventive Action (CAPA) The Quality Systems Regulation (21 CFR 820) and the Quality Management Standard for Medical Devices (ISO 13485:2003), require medical device companies to establish and maintain procedures for implementing corrective and preventive action (CAPA) as an integral part of the quality system.

Strategies for an Effective Root Cause Analysis and CAPA Program This webinar will provide valuable assistance to all regulated companies, a CAPA program is a requirement across the Medical Device, Diagnostic, Pharmaceutical, and Biologics fields. This session will discuss the importance, requirements, and elements of a root cause-based CAPA program, as well as detailing the most effective ways to determine root cause and describing the uses of CAPA data.

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7 QC Tools Training

The 7 QC Tools are essential tools that help businesses identify, analyze, and effectively address quality-related issues. From increasing process effectiveness to decreasing defects, these tools give organizations the power to consistently enhance and deliver top-notch products and services. At Swades QMS, we strive to help organizations reach greatness in their quality management endeavors. As an industry leader, we provide intensive training sessions, including our extremely popular 7 QC Tools Training. Our program furnishes learners with the knowledge, capabilities, and practical insights needed to make these tools work effectively in their sector.

Our Training Methodology

We follow a dynamic training methodology that focuses on active participation, experiential learning, and knowledge application. Our experienced trainers employ a variety of techniques to create a stimulating and immersive training environment.

Interactive and Practical Sessions:

Our training sessions are far from passive lectures. We foster an atmosphere of collaboration and engagement, encouraging participants to actively contribute and learn from one another. Through group discussions, workshops, and hands-on exercises, participants gain practical experience in using the 7 QC Tools.

Hands-On Exercises, Case Studies, and Real-World Examples:

We firmly believe in learning by doing. Our training program incorporates hands-on exercises that simulate real-life quality scenarios, allowing participants to practice applying the 7 QC Tools in a controlled environment. We also utilize relevant case studies and real-world examples to illustrate the application of these tools across different industries.

Industry Best Practices and Relevant Standards:

Our training is grounded in industry best practices and the latest quality management standards. We provide insights into how the 7 QC Tools align with internationally recognized quality frameworks, such as ISO 9001. By integrating these practices and standards into the training, participants gain a comprehensive understanding of how the tools can be effectively utilized within their organization.

Training Content

1. introduction to quality control and the 7 qc tools.

Overview of quality control principles and importance in organizations
Introduction to the concept of the 7 QC Tools and their significance
Explanation of how the 7 QC Tools contribute to quality improvement initiatives

2. Pareto Chart

Understanding the Pareto principle and its application in quality control
Steps to create a Pareto chart for identifying and prioritizing quality issues
Analyzing and interpreting Pareto charts to focus improvement efforts

3. Cause-and-Effect Diagram (Fishbone Diagram)

Introduction to cause-and-effect diagrams and their purpose in problem-solving
Steps to construct a cause-and-effect diagram to identify root causes
Using the fishbone diagram to facilitate team brainstorming and analysis

4. Check Sheet

Understanding the purpose and benefits of check sheets in data collection
Designing and utilizing check sheets for collecting quality-related data
Analyzing check sheet data to identify trends, patterns, and areas for improvement

5. Scatter Diagram

Introduction to scatter diagrams and their role in analyzing relationships between variables
Creating scatter diagrams to visualize correlations and potential cause-and-effect relationships
Interpreting scatter diagrams and making data-driven decisions based on the analysis

6. Histogram

Explanation of histograms and their application in data analysis
Constructing histograms to understand distribution patterns and variations
Interpreting histograms to identify process performance and areas for improvement

7. Control Chart

Overview of control charts and their significance in monitoring process stability
Steps to create and interpret control charts for tracking process performance
Utilizing control charts to identify and respond to process variations and out-of-control situations

8. Scatter Diagram

9. data collection and analysis techniques.

Best practices for effective data collection and management
Techniques for analyzing and interpreting data using the 7 QC Tools
Integrating the 7 QC Tools into a comprehensive quality control system

10. Application and Case Studies

Applying the 7 QC Tools to real-world quality issues and challenges
Analyzing case studies to understand practical implementation of the tools
Discussion and sharing of success stories and lessons learned

11. Q&A and Wrap-Up

Addressing participant questions and concerns
Summarizing key takeaways from the training program
Closing remarks and next steps for participants to apply the acquired knowledge

Who Should Attend

Managers, Executives, Engineers and Other Staff
Students or any Professionals requiring an overview of 7 QC Tools

About Swades QMS

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7 QC Tools | Seven Basic Quality Tools of “Problem Solving”: Quality and Productivity Improvement Tools Kindle Edition

Print length 33 pages
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Sticky notes On Kindle Scribe
Publication date June 3, 2020
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ASIN ‏ : ‎ B089NLZFS2
Publication date ‏ : ‎ June 3, 2020
Language ‏ : ‎ English
File size ‏ : ‎ 1212 KB
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COMMENTS

7 Basic Quality Tools: Quality Management Tools
7 Basic Quality Tool Templates. These templates will help you get started using the seven basic quality tools. Just download the spreadsheets and begin entering your own data. Cause-and-effect diagram template (Excel) Check sheet template (Excel) Control chart template (Excel) Histogram template (Excel)
7 QC Tools
The 7 Quality Tools are widely applied by many industries for product and process improvements, and to solve critical quality problems. 7QC tools are extensively used in various Problem Solving Techniques which are listed below: 8D Problem Solving Methodology. PDCA Deming Cycle for Continuous improvement in product and processes.
7 Basic Tools of Quality for Process Improvement
Kaoru Ishikawa played the leading role in the development and advocacy of using the 7 quality tools in organizations for problem-solving and process improvement. The 7 basic quality tools include; Flowchart. Histogram.
7 QC Tools: Your Ultimate Guide To Quality Improvement
Introduction to 7 QC tools Quality management is an important aspect of any organization, and achieving it requires effective problem-solving strategies. In this regard, the 7 QC tools offer a comprehensive approach to problem-solving and quality improvement. These tools are designed to help organizations identify the root cause of problems, make data-driven decisions, and ultimately
What are the 7 Basic Quality Tools?
The 7 basic Quality Tools, often known as the 7 QC, are graphical techniques proven effective for troubleshooting quality-related issues. These techniques are predominantly employed in continuous improvement initiatives such as Six Sigma, Lean, and Total Quality Management. Quality Tools: Enhancing Your Problem-Solving Capabilities
What Are the 7 Basic Quality Tools?
4. Cause-and-effect diagram (also known as a fishbone or Ishikawa diagram) Introduced by Kaoru Ishikawa, the fishbone diagram helps users identify the various factors (or causes) leading to an effect, usually depicted as a problem to be solved. Named for its resemblance to a fishbone, this quality management tool works by defining a quality-related problem on the right-hand side of the diagram ...
Streamlining Six Sigma Projects with The 7 QC Tools
Unfortunately, the complexity of the subject intimidated most workers, so Ishikawa focused primarily on a reduced set of tools that would suffice for most quality-related issues. The 7 QC tools are: Check sheet. Fishbone diagram (cause and effect diagram, or Ishikawa diagram) Histogram. Pareto chart. Control chart.
7qc tools: Significance, How to use?, How to Create
7QC tools, also known as quality control tools, are used to identify and analyze problems in a process and to find solutions to improve the quality of a product or service. Here are some general steps for using 7QC tools: Identify the Problem: Identify the problem or issue that needs to be addressed.
The 7 QC Tools (Effective Problem Solving)
Description. Welcome to this course on the "7 QC Tools". These are simple yet powerful and effective tools for problem solving, with a wide applicability across different sectors, whether it is manufacturing or service sector. I believe that every member of your team, who is involved in problem solving of any nature, should have a good insight ...
Quality Control Tools for the Certified Quality Engineer
As a Quality Engineer one of the most important skills you can have, is the ability to solve a problem or improve a process. To do this successfully, you need to be able to apply the 7 QC Tools. These 7 tools combine a fact-based approach with a visual tool that makes solving problems easier. Below is a quick and simple review of the definition ...
PDF Seven Basic Tools of Quality Control: The Appropriate ...
seven quality control (QC) tools in the organizations for problem solving and process improvements. Seven old quality control tools are a set of the QC tools that can be used for improving the performance of the production processes, from the first step of producing a product or service to the last stage of production. So, the general purpose ...
Mastering the 7QC Tools: Techniques for Effective Problem-Solving and
The 7QC tools, also known as the Seven Quality Control Tools, are a set of problem-solving techniques that were first introduced by Dr. Kaoru Ishikawa in the 1960s.
Seven basic tools of quality
Histogram. Pareto chart. Scatter diagram. Flow chart. Run chart. The seven basic tools of quality are a fixed set of visual exercises identified as being most helpful in troubleshooting issues related to quality. [1] They are called basic because they are suitable for people with little formal training in statistics and because they can be used ...
7 QC Tools
These 7 tools combine a fact-based approach with a visual tool that makes solving problems easier. Below is a quick and simple review of the definition for each of the 7 tools discussed within this chapter. 1. A Flow Chart is a visual tool that depicts the flow or sequence of a process.
7QC Tools for Problem Solving
For solving problems seven QC tools are used Pareto Chart, Cause & Effect Diagram, Histogram, Control Charts, Scatter Diagrams, Graphs/Process Flow Diagram, and Check Sheets. All these tools are important tools used widely in the manufacturing field to monitor the overall operation and continuous process improvement. seven QC tools are used to ...
7QCs: An Introduction to the Seven Basic Tools of Quality Control
Fishbone diagrams, also referred to as cause and effect diagrams, are a quality control brainstorming tool used to help identify the root cause or causes of an issue by looking at all possible variables. When using these diagrams, a central issue or focal point, such as a defect or quality problem, is placed at the head of the "fish.".
7 QC Tools
The 7 QC tools help to analyze the data and are most helpful in problem-solving methods. It is the fundamental tool to improve our product and process quality by identifying and analyzing the problems. As per the Deming chain to achieve the organizational goal, we must tackle the product & process-related problems, and analyze these problems we ...
Exploring the NEW 7 QC Tools
Revolutionizing Quality Control: Exploring the NEW 7 QC Tools. In the ever-evolving landscape of quality management, ... They are particularly useful in brainstorming sessions and problem-solving, ...
The 7QC Tools Overview: How to Quickly and Easily Solve Quality Control
The 7 QC tools work by inspecting and measuring product or process quality characteristics. The tools are used to identify and correct problems so that the product or process meets requirements ...
7 QC Tools For Quality Improvement
The 7 QC Tools are simple tools, low-cost and easy-to-use; but they are powerful tools that forms the critical foundation for all problem solving and quality improvement activities. Our online training method is logical, systematic, and proven effective. This 7QC tools course provides solid foundation for individuals' and team's root cause analyses, problem solving sessions, and continuous ...
7 Powerful Problem-Solving Root Cause Analysis Tools
The reason is if you don't know what the problem is, you can never solve the exact problem that is hurting the quality. Manufacturers have a variety of problem-solving tools at hand. However, they need to know when to use which tool in a manner that is appropriate for the situation. In this article, we discuss 7 tools including:
7 QC Tools Training
The 7 QC Tools are essential tools that help businesses identify, analyze, and effectively address quality-related issues. From increasing process effectiveness to decreasing defects, these tools give organizations the power to consistently enhance and deliver top-notch products and services.
7 QC Tools
These statistical tools are very easy to understand and can be implemented without any complex analytical competence/skills. 7 QC tools are extensively used in various Problem Solving Techniques like 8D, Six sigma-DMAIC and PDCA approach etc. Key Features •All QC tools are explained in brief and in simple language for better understanding of ...
Boeing Slows Production of Its 787 Jet. Relax, It's Not a Quality Problem
BA. Boeing is set to slow production of its twin-aisle 787 Dreamliner jets. Shares are unaffected. Investors appear to be giving the company a pass since it isn't a quality problem—and because ...

7 Basic Tools of Quality for Process Improvement

Quality Tools: What Are They?

7 Basic Quality Tools Explained with Templates

Real-world examples of usage

How to use a flowchart

Who can use it?

How to make a histogram

How to use the cause and effect diagram

How to make a scatter diagram

How to make a checksheet

Control Chart

How to create a control chart

Pareto Chart

How to create a Pareto chart

What’s Your Favorite Out of the 7 Basic Quality Tools?

FAQs about 7 Basic Quality Tools

More Related Articles

7 QC Tools: Your Ultimate Guide To Quality Improvement

Introduction to 7 QC tools

Importance of 7 QC tools in quality management

History and evolution of 7 QC tools

How to select the right tool for quality control

7 QC Tools Explained

7 QC Tools Limitations:

Alternative Approach to 7QC Tools:

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Streamlining Six Sigma Projects with The 7 QC Tools

Overview: What are the 7 QC tools?

3 benefits of the 7 QC tools

1. Easy

2. Software-driven

3. 80/20

Why are the 7 QC tools important to understand?

Tools address different issues

Graphs don’t tell the whole story

Flexibility

3 best practices when thinking about the 7 QC tools

1. Have a clear idea of what question you’re trying to answer

2. Use them as your primary presentation

3. Make sure they’re self-explanatory

Frequently Asked Questions (FAQ) about the 7 QC tools

What are the 7 basic QC tools?

Do I have to draw the graphs and diagrams for the 7 QC tools by hand?

Let’s review what’s in your tool belt

Key Points About The 7 QC Tools:

About the Author

Ken Feldman

7qc tools: Significance, How to use?, How to Create

What are 7QC Tools?

Types of 7QC Tools

1. Check sheet

What is a Check Sheet?

Benefits of Check Sheets

Disadvantages of Check Sheets

2. Cause and Effect Diagram

What is Cause and Effect Diagram?

Components of a Cause and Effect Diagram

How does Cause and Effect Diagram work?

Advantages of Cause and Effect Diagram

Tips for Using a Cause and Effect Diagram:

3. Pareto Chart

How to Create a Pareto Chart?

Advantages of Using Pareto Chart

Disadvantages of Using Pareto Chart

4. Control Chart

How to Create a Control Chart?

Types of Control Charts

Advantages of Using Control Charts

Disadvantages of Using Control Charts

5. Scatter Diagram

How to Create a Scatter Diagram?

Types of Scatter Diagrams

Advantages of Using Scatter Diagrams

Disadvantages of Using Scatter Diagrams

6. Histogram

Benefits of Histogram

How to Create a Histogram?

Types of Histograms

Advantages of Using Histograms