1. What are 7 quality management tools (7QC tools)?

After the second world war, Japan faced many difficulties, the association of Japanese scientists and engineers (JUSE, Japanese Union Of Scientists and Engineers) decided to choose and apply the  tools. Statistics  in quality management methods for all classes of Japanese officials. Since then, their application has become more and more widespread and popular around the world, especially in Europe, and is called   Seven Tools for short .

It can be affirmed that the quality improvement will not have the desired effect without the application of statistical tools. However, there are hundreds of statistical tools available, so it's up to you to decide which tool is the most appropriate and effective for your own operations.

Through the sharing of experienced Japanese experts in the support consulting industry, we found that: just applying the  following 7 statistical tools  can solve most of the quality management problems. commonly encountered in production activities as well as customer service of enterprises. Those tools include:

Out of 7 statistical tools, only the Cause & Effect Diagram was invented by Mr. Ishikawa in the 1950s. Check sheets have been used since the 2nd world war. Charts. Pareto and Control Chart are from the early 20th century, the rest of the tools are unknown since when, they just gathered to research and apply them.

2. CONTENT OF TOOLS

2.1. Check sheets

Check sheets are a means of storing data, which can be a record of past activities, or a tracking medium that allows you to objectively see trends or patterns. This is a simple form of storing some of the statistical data needed to determine event precedence.

Check sheets are commonly used to:

– Check the data distribution of an indicator of the production process

– Check for defects

– Check the location of defects

– Check the source of product defects

– Check job confirmation

Typically, Checklists will track events over time, but can also be used to track event counts by location. This data can then be used as input to a Focus Graph, a Pareto Chart… Examples of issues to watch for might be: spills/month, service and repair calls /week, hazardous waste collected/working hour, etc...

2.2. Charts 

A graph is a drawing that shows the relationship between data or quantities.

Charts are used to visualize data so that the problem can be easily grasped with the naked eye.

There are many chart types: Line chart, column and line chart, pie chart, bar chart, Gantt chart, spider web chart.

2.3. Cause & Effect Diagram

A cause-and-effect diagram is simply a list of possible causes that lead to an effect. This tool was built in 1953 at the University of Tokyo led by Professor Kaoru Ishikawa. He used this chart to explain to engineers at the Kawasaki steel plant how the various elements are arranged and shown in relation to each other. Therefore, cause-and-effect diagrams are also called Ishikawa diagrams or fishbone diagrams.

Purpose:  A method for finding the cause of a problem and taking corrective action to ensure quality. This is the most used tool in finding the causes and defects in the manufacturing process.

This tool is used to study and prevent potential hazards that cause poor performance related to a certain phenomenon, such as defective products, quality characteristics, and at the same time help us understand the whole picture. relationships in a systematic way. This chart is also known as fishbone diagram, Ishikawa diagram, or Tokuzei Yoin in Japanese - characteristic chart...

The feature of this chart is that it helps us to list and categorize potential causes, not to give us a way to eliminate them.

2.4. Pareto diagram 

Pareto diagram (Pareto diagram) is a bar chart used to classify causes/effects taking into account their importance to the product. Using this chart helps managers know the causes that need to be focused on.

Note that it is necessary to use a Pareto chart to analyze the causes and costs caused by those causes.

Purpose:  To separate the most important causes from the trivial causes of a problem. Also, identify and prioritize the most important issues. In addition, the Pareto chart is also used to evaluate the effectiveness of improvements.

Apply when: Analyze the data related to the problem to decide which factors are most important influencing the problem.

Pareto analysis is also important in the improvement process. Therefore, the improvement implementation needs to be used with a variety of statistical tools.

In quality management, it is also often found that:

• 80% of quality loss is caused by 20% of causes.

• 20% of the causes cause 80% of the times a bad condition occurs.

2.5. Histogram 

The density distribution plot is a simple bar chart. It aggregates data points to represent the frequency of events.

Purpose:  Used to monitor the distribution of product/process parameters. From there, evaluate the capacity of that process (Does the process meet the requirements of product production?). Is a bar chart showing the frequency of occurrence of the problem (collected through the check sheet).

Apply: Prevent before problems can occur.

2.6. Scatter Diagram

Scatter Diagram is a graphical representation of data in which the observed values ​​of one variable are plotted against the values ​​of the other variable without connecting the points. each other by a connection. The scatter plot shows the relationship between two factors.

Purpose:  To solve problems and determine optimal conditions by quantitatively analyzing the causal relationship between the variables of these two factors.

Based on the analysis of the graph, it can be seen how one factor depends on another and the degree of dependence between them.

2.7. Control Chart 

Is a chart with the limit lines calculated by statistical methods used for the purpose of monitoring the fluctuations of the parameters of the quality characteristics of the product, monitoring the changes of the process. to control all abnormal signs that occur when there is an up or down sign of the chart.

Purpose:  Detect abnormal situations occurring in the production process.