The full text has a total of 5011 words and takes 12 minutes to read. The following is the main text: Introduction: What are the seven QC techniques: The seven QC techniques are also called the seven QC tools. They generally refer to the old QC seven techniques, namely checklist,

has a total of 5011 words and takes 12 minutes to read. The following is the main text:

Introduction: What are the Seven QC Techniques: QC Seven Techniques are also called QC Seven Tools. They generally refer to the old QC Seven Techniques, namely Checklist, Hierarchy Method, Plato, Cause and Effect Diagram, Scatter Diagram, Histogram and Control Chart. It is an effective tool for quality management and improvement application.

Seven techniques

-1-Checklist

A checklist is a method of listing the contents or items that need to be checked one by one, and then checking them one by one regularly or irregularly, and recording the problem points. It is sometimes called a checklist or a point inspection list. For example: inspection form, diagnosis form, work improvement checklist, satisfaction survey form, assessment form, audit form, 5S activity checklist, engineering anomaly analysis form, etc.

components:

① Determine the inspection items;

② Determine the frequency of inspection;

③ Determine the inspection personnel.

implementation steps:

① Determine the inspection objects;

② Develop a checklist;

③ Conduct inspections and records according to the items in the checklist;

④ Request the responsible unit to improve the problems detected in a timely manner;

⑤ The inspectors will confirm the improvement effect within the specified time;

⑥ Regular summary and continuous improvement.

-2-

layer classification method

layer classification method is to classify a large number of views, opinions or ideas about a specific topic into groups, and to group and classify a large amount of collected data or information according to their interrelationships. The layering method is generally used in combination with other seven techniques such as Plato, histogram , etc., or can be used alone. For example: sampling statistics table, bad category statistics table, ranking list, etc.

Implementation steps:

① Determine the research topic;

② Make forms and collect data;

③ Classify the collected data;

④ Comparative analysis, analyze these data, find out the underlying reasons, and determine improvement projects.

—3—

Plato

The use of Plato should be based on the hierarchical method, and the items determined by the hierarchical method should be arranged from large to small, plus a graph of cumulative values. It can help us identify key issues, grasp the important few and useful majority, and is suitable for counting numerical statistics. Some people call it the ABC chart, and because Plato's ordering is from large to small, it is also called the arrangement chart .

classification:

① Use Plato to analyze phenomena: related to undesirable results, used to find main problems.

A Quality: non-conformity, failure, customer complaints, returns, repairs, etc.;

B Cost: total loss, expenses, etc.;

C Delivery time: inventory shortage, payment default, delivery delay, etc.;

D Safety: accidents, errors, etc.

② Use Plato to analyze the reasons: related to process factors, used to find main problems.

A Operator: shift, group, age, experience, proficiency, etc.;

B Machine: equipment, tools, molds, instruments, etc.;

C Raw material: manufacturer, factory, batch, type, etc.;

D Operation method: operation environment, process sequence, operation arrangement, etc.

The role of Plato:

① Reduce bad basis;

② Determine improvement goals and identify problem points;

③ Can confirm the effect of improvement.

implementation steps:

① Collect data, classify it using the hierarchical method, and calculate the percentage of items at each level in the overall project;

② Summarize the classified data, arrange it from most to least, and calculate the cumulative percentage;

③ Draw the horizontal and vertical axis scales;

④ Draw a histogram;

⑤ Draw a cumulative curve;

⑥ Record necessary matters

⑦ Analysis of Plato

⑧ Key points:

A Plato has two ordinates. The left ordinate generally represents the quantity or amount, and the right ordinate generally represents the cumulative percentage of the quantity or amount;

B Plato's abscissa generally represents inspection items, arranged in order from left to right according to the degree of influence;

C When drawing Plato, draw a rectangle according to the frequency of the number or amount of each item corresponding to the ordinate on the left, draw points according to the cumulative frequency of each item corresponding to the ordinate on the right, and connect these points in order to form lines.

application points and precautions:

① To retain Plato, arrange the pre-improvement and post-improvement Plato together to evaluate the improvement effect;

② To analyze Plato, you only need to grasp the first 2~3 items nine;

③ Don’t set too few classification items in Plato. 5 to 9 items are appropriate. If there are too many classification items, more than 9 items, they can be classified into other categories. If there are too few classification items, less than 4 items, there is no practical meaning in doing Plato;

④ If the completed Plato is found to be about the same distribution ratio of each item, the Plato will lose its meaning and is inconsistent with Plato's law. Data should be collected from other angles and then analyzed;

⑤ Y Plato is a means of management improvement rather than an end. If the data items are already clear, there is no need to waste time making a Plato;

⑥ If other items are larger than the previous ones, they must be analyzed at different levels to review whether there are reasons;

⑦ The main purpose of Plato analysis is to obtain information to show the focus of the problem and take countermeasures. However, if the first project is difficult to solve based on existing conditions, or even if it is solved, it will cost a lot and the gain outweighs the gains, then the first project can be avoided and started with the second project.

-4-

Cause-and-effect diagram

The so-called cause-and-effect diagram, also known as the characteristic factor diagram, is mainly used to analyze the causal relationship between quality characteristics and possible causes that affect quality characteristics. It promotes problem solving by grasping the current situation, analyzing causes, and finding measures. It is a tool used to analyze quality characteristics (results) and factors that may affect characteristics (causes) . Also known as fishbone diagram .

Category:

① Pursuing cause type: pursuing the cause of the problem and looking for its impact, using a cause and effect diagram to represent the relationship between the result (characteristic) and the cause (factor) ;

② Pursuing countermeasure type: pursuing how to prevent the problem and how to achieve the goal, and using a cause and effect diagram to represent the relationship between the expected effect and countermeasures.

implementation steps:

① Set up a cause-and-effect diagram analysis team, preferably 3 to 6 people, preferably representatives of each department;

② Determine problem points;

③ Draw the main bones, middle bones, and small bones of the main line and determine the major reasons (generally find out the reasons comprehensively from the six aspects of 5M1E: Man, Machine, Material, Method, Measure, and Environment);

④ The participants discussed heatedly, analyzed the major causes, found the medium or small causes, and drew them into the cause-and-effect diagram;

⑤ The cause-and-effect diagram group should reach a consensus and mark the items that are most likely to be the source of the problem with red pens or special marks;

⑥ Record the necessary matters

Application points and precautions:

① Determining the cause requires gathering the knowledge and experience of all employees and brainstorming to avoid omissions;

② The more detailed the cause analysis, the better. The more detailed the analysis, the better the key reasons or solutions to the problem can be found;

③ How many quality characteristics are there, how many cause and effect diagrams should be drawn;

④ If no measures can be taken for the analyzed reasons, it means that the problem has not been solved. If improvements are to be effective, the reasons must be subdivided until measures can be taken;

⑤ Objectively evaluate the importance of each factor on the basis of data;

⑥ Put the focus on solving the problem and list it item by item according to the 5W2H method. When drawing a cause-and-effect diagram, the focus is first on "why this kind of cause and result happened", and when proposing countermeasures after analysis, focus on "how to solve it";

Why - Why do we do it? (Object)

What - What to do? (purpose)

Where - where to do it? (place)

When - when to do it? (sequence)

Who - who will do it? (person)

How - how to do it? (means)

How much - how much does it cost? (cost)

⑦ The cause-and-effect diagram should be considered based on the problems that occurred on site;

⑧ After the cause-and-effect diagram is drawn, a consensus must be formed to determine the factors, and marked with a red pen or special mark;

⑨ The cause-and-effect diagram must be continuously improved when used.

-5-

scatter diagram

plots the data corresponding to the causal relationship on the X-Y axis coordinate system to grasp whether and how much the two variables are correlated. This graph is called " scatter diagram ", also known as " correlation diagram ".

Category:

① Positive correlation: When variable X increases, another variable Y also increases;

② Negative correlation: When variable X increases, another variable Y decreases;

③ Irrelevant: When variable X (or Y) changes, the other variable does not change;

④ Curve correlation: When variable

implementation steps:

① Determine the two variables to be investigated and collect relevant latest data, at least 30 sets;

② Find the maximum and minimum values of the two variables, and plot the two variables into the X-axis and Y-axis;

③ Mark the corresponding two variables on the coordinate system in the form of points;

④ include the picture title, producer, production time and other items;

⑤ judge the correlation and degree of correlation of the scatter diagram.

application points and precautions:

① The corresponding number of the two sets of variables should be at least 30, preferably 50 to 100. When the data is too small, it is easy to cause misjudgment;

② Usually the abscissa is used to represent the cause or independent variable , and the ordinate represents the effect or dependent variable;

③ Since data acquisition is often affected by changes in 5M1E, the correlation of the data is affected. In this case, the conditions for data acquisition need to be stratified, otherwise the scatter diagram cannot truly reflect the relationship between the two variables;

④ When an abnormal point appears, the cause should be found immediately instead of deleting the abnormal point;

⑤ When the correlation of the scatter diagram does not match the technical experience, further examination should be carried out to see if there is any reason for the artifact.

-6-

histogram

histogram is for the characteristic value of a certain product or process, using the principle of normal distribution (also called normal distribution ) , to group more than 50 data, and calculate the number of occurrences of each group, and then use a similar histogram to depict it on the horizontal axis.

implementation steps:

① Collect the same type of data;

② Calculate the range (full range) R=Xmax-Xmin;

③ Set the number of groups K: K=1+3.23logN

④ Determine the minimum unit of measurement, that is, when the number of decimal places is n, the minimum unit is 10-n;

⑤ Calculate the group distance h, group distance h = range R/number of groups K;

⑥ Find the upper and lower limit values ​​of each group

The first group lower limit value = Calculate the center value of each group, group center value = (group lower limit value + group upper limit value)/2;

⑧ Make frequency table ;

⑨ Draw a histogram according to the frequency table. Common shapes and judgments of

histograms:

① Normal type: is a normal distribution, obeys statistical laws, and the process is normal;

② Missing tooth type: is not a normal distribution, does not obey statistical laws;

③ skewed type: is not normally distributed and does not obey statistical laws;

④ Island type: is not normally distributed and does not obey statistical laws;

⑤ Plateau type: is not normally distributed and does not obey statistical laws;

⑥ Bimodal type: is not normally distributed and does not obey statistical laws;

⑦ Irregular type: is not normally distributed and does not obey statistical laws.

—7—

control chart

There are many factors that affect product quality. There are static factors and dynamic factors. Is there a way to monitor the production process of the product in real time and discover quality hazards in a timely manner so as to improve the production process and reduce waste and defective products? The output?

The control chart method is such a prevention-oriented quality control method . It uses the quality characteristic values collected on site to draw a control chart and judge the quality status of the product's production process by observing the graphics. control chart can provide a lot of useful information and is one of the important methods of quality management.

The meaning of the control chart method:

Control chart is also called a management chart. It is a quality management chart with control limits. One of the purposes of using control charts is to analyze and judge whether an abnormality has occurred in the production process by observing the distribution of product quality characteristics values ​​on the control chart. Once an abnormality is discovered, necessary measures must be taken in time to eliminate it and restore the production process to a stable state. Control charts can also be applied to bring the production process to a state of statistical control. The distribution of product quality characteristic values ​​is a statistical distribution. Therefore, drawing a control chart requires the application of relevant theories and knowledge of probability theory.

control chart is a recording graphic of the quality of the production process. There is a center line and upper and lower control limits on the chart, and there are numerical points that reflect the statistics of each sample extracted in chronological order. The center line is the average of the controlled statistic, and the upper and lower control limits are several times the standard deviation away from the center line. Most manufacturing industries use three standard deviation control limits, but other control limits may be used if there is sufficient evidence.

Commonly used control charts include two categories: measurement value and counting value, which are suitable for different production processes; each type can be subdivided into specific control charts. For example, the measurement value control chart can be specifically divided into mean-range control chart, single value-moving range control chart, etc. Drawing of

control chart:

① The basic style of the control chart is as shown in the figure. Making a control chart generally goes through the following steps:

A Select samples according to the specified sampling interval and sample size;

B Measure the quality characteristic value of the sample and calculate its statistical value;

C Draw points on the control chart;

D to determine whether the production process is parallel.

② Control charts provide managers with a lot of useful production process information. The following issues should be noted:

A According to the quality of the process, rationally select management points. Management points generally refer to key parts, critical dimensions, key points with special requirements for the process itself, and key points that have an impact on the start of work. For example, you can choose parts with unstable quality and more defective products as management points;

B According to the quality problems at the management points, reasonably select the type of control chart:

C When using control charts for process management, you should first determine the reasonable control limits

D If the points on the control chart are abnormal, the cause should be found immediately and measures should be taken before production is started. This is the primary prerequisite for the control chart to work;

E The control line is not equal to the tolerance line. The tolerance line is used to judge whether the product is qualified, while the control line is used to judge whether the quality of the process has changed;

F If an abnormality occurs in the control chart, responsibilities must be clearly defined and resolved or reported in a timely manner.

On-site sampling method:

When making control charts, control limits are not calculated every time, so how are the initial control lines determined? If the current production conditions are similar to those in the past, you can follow past experience data, that is, continue to use the control limits of stable production in the past. The following introduces a method for determining control limits, namely the on-site sampling method.

The steps are as follows:

① Randomly select more than 50 samples, measure the data of the samples, calculate the control limits, and make a control chart;

② Observe whether the control chart is in a control state, that is, a stable situation, if all points are within the control limits. If there is no abnormality in the arrangement of points, you can go to the next step;

③ If there is an abnormal state, or if there is an abnormality in the arrangement although it does not exceed the control limit, you need to find out the cause of the abnormality and take appropriate measures to make it in the control state, and then re-fetch the data to calculate the control limit and go to the next step;

④ Make a cube plot of the above-mentioned data, and compare the cube plot with the standard limits (upper and lower limits of tolerance) to see whether it is in the ideal state or a more ideal state. If the requirements are not met, measures must be taken to reduce the average bit shift or the standard deviation of and . After taking measures, repeat the above steps to re-take the data and make control limits until the standards are met.

How to use control charts to determine abnormal phenomena:

uses control charts to identify the status of the production process, mainly analyzing and judging based on the sample point locations and changing trends formed by sample data. The out-of-control state of

mainly manifests itself in the following two situations:

sample points exceed the control limits;

sample points are within the control limits, but are arranged abnormally.

When data points exceed management boundaries, it is generally believed that there is an abnormality in the production process. At this time, the cause should be investigated and countermeasures taken. Abnormal arrangement mainly refers to the following situations:

A More than seven consecutive points are all deviated above or below the center line. At this time, you should check whether the production conditions have changed.

B Two of the three consecutive points enter the area near the management limit (referring to the area from the center line to more than two-thirds of the management limit). At this time, attention should be paid to whether the fluctuation of production is too large.

C points have an upward or downward trend one after another, indicating that the process characteristics are changing upward or downward.

D The arrangement status of the points changes periodically. At this time, the operation time can be processed hierarchically and the control chart can be remade to find out the cause of the problem. The ability of the

control chart to reveal abnormal phenomena will vary depending on the amount of data in each group when grouping the data, the sample collection method, and the division of layers. We should not just be satisfied with the use of one control chart, but should change various data collection methods and usage methods, and produce various types of charts, so as to achieve better results.

It is worth noting that if an abnormal phenomenon that exceeds management boundaries is discovered, but no efforts are made to investigate the cause and take countermeasures, then although the control chart is very effective, it is just an empty piece of paper.

-END-

Article source: Internet (such as infringement and deletion)

Article editor: Blean

Submission method: wangy j@benchmarklean.cn

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