Seven methods of quality control

Seven methods of quality control are commonly used statistical management methods, also known as primary statistical management methods. It mainly includes control chart, causal chart, correlation chart, Pareto chart, statistical analysis table, data layering method, scatter diagram and other so-called QC seven tools.

in fact, the methods of quality management can be divided into two categories: one is organizational quality management based on the idea of total quality management; The second is quality control based on mathematical statistics.

organizational quality management method refers to the method of quality management from the perspective of organizational structure, business processes and working methods of personnel. It is based on the idea of total quality management, and its main contents include formulating quality policy, establishing quality assurance system, carrying out QC group activities, sharing quality responsibilities of various departments, and conducting quality diagnosis.

statistical quality control is the control chart first put forward by Dr. W.A.Shewhart of Bell Telephone Laboratory in the United States in 1924, which has made great progress for more than half a century. Now these methods can be roughly divided into the following three categories.

(1) Primary statistical management methods: also known as commonly used statistical management methods. It mainly includes control chart, causal chart, correlation chart, Pareto chart, statistical analysis table, data layering method, scatter diagram and other so-called seven QC tools (or seven techniques of quality control). Using these tools, we can systematically collect all kinds of data related to product quality from the ever-changing production process, and use statistical methods to sort out, process and analyze the data, and then draw various charts, calculate some data indicators, find out the law of quality change and realize quality control. Kaoru ishikawa, a famous Japanese quality management expert, once said that 95% of the quality management problems in an enterprise can be solved by using these seven QC tools flexibly by all the staff from top to bottom in the enterprise. The implementation of total quality management is also inseparable from the mastery and flexible application of these tools by personnel at all levels and departments of enterprises.

(2) Intermediate statistical management methods: including sampling survey method, sampling inspection method, function inspection method, experiment planning method, method research, etc. These methods are not necessarily mastered by all staff of the enterprise, but are mainly used by relevant technicians and people in the quality management department.

(3) advanced statistical management methods: including advanced experimental planning method and multivariate analysis method. These methods are mainly used for complex engineering analysis and quality analysis, and they are usually only used by professionals with the help of computer means.

here is a brief introduction to the seven commonly used methods of primary statistical quality management, namely the so-called "QC seven tools", for the reference of netizens.

(1) statistical analysis table

statistical analysis table is a tool for sorting out data and preliminarily analyzing reasons by using statistical tables, and its format can be varied. Although this method is simple, it is practical and effective.

(2) data stratification method

data stratification method is the same in nature, and the data collected under the same conditions are summarized together for comparative analysis. Because in actual production, there are many factors that affect the quality change. If we don't distinguish these factors, it is difficult to get the law of change. Data layering can be carried out in many ways according to the actual situation. For example, according to different times and shifts, according to the types of equipment used, according to the feeding time and composition of raw materials, according to inspection methods and use conditions, according to different defective items, and so on. The data stratification method is often used in combination with the above statistical analysis table.

The application of data layering method is mainly a systematic concept, that is, if you want to process quite complicated data, you must know how to systematically and purposefully classify and summarize these data.

Scientific management emphasizes management techniques to make up for the deficiency of previous management based on experience and visual judgment. This management technique requires not only the establishment of correct ideas, but also the application of data, so as to analyze the work and take correct measures.

how to establish the original data and collect these data according to the required purpose is also the most basic work of many quality control methods.

For example, the competition in China's aviation market has become increasingly fierce with the opening up in recent years. In order to win the market, airlines not only strengthen various measures, but also make efforts in service quality. We can also often see customer satisfaction surveys on airplanes. This survey was conducted through a questionnaire. The design of questionnaire is usually divided into ground service quality and aircraft service quality. The ground is divided into booking and waiting; Aircraft is divided into flight attitude, catering, hygiene and so on. Through these surveys, we can gather these data and get where to strengthen the service quality.

(3) Pareto diagram (Plato)

Pareto diagram is also called Plato, and it is named after the inventor of this diagram, the Italian economist Plato in the 9th century. Plato first used Pareto diagram to analyze the distribution of social wealth. He found that 81% of Italy's wealth was concentrated in the hands of 21%. Later, people found that many occasions obeyed this law, so it was called Pareto Law. Later, Dr. Zhu Lan, an American quality management expert, extended Plato's statistical chart and applied it to quality management. Pareto diagram is a tool to analyze and find the main factors affecting quality. Its form is a double rectangular coordinate diagram, with the left ordinate indicating frequency (such as the number of pieces, etc.) and the right ordinate indicating frequency (such as percentage). The broken line indicates cumulative percentage, and the abscissa indicates various factors that affect the quality, which are arranged from left to right according to the degree of influence (that is, the frequency of occurrence). By observing and analyzing the Pareto Diagram, we can grasp the main and original factors that affect the quality. In fact, this method is very useful not only in quality management, but also in many other management work, such as inventory management.

in the process of quality management, there are many problems to be solved, but we often don't know where to start, but in fact, as long as we can find out a few influential reasons, we can solve more than 81% of the problems. Plato systematically classified the items (levels) according to the collected data, and calculated the data (such as non-performing rate and loss amount) and the proportion of each item, and then arranged them in order of size, plus the graph of accumulated value.

In factories or offices, losses such as inefficiency, defects and defective products can also be converted into more than 81% of the loss amount according to their causes or phenomena, which is called Plato's analysis.

Plato's use should be based on the category (phenomenon category) of the hierarchical method, and it can only be drawn into Plato according to the statistics adjusted in order.

the steps of Plato's analysis;

(1) The things to be handled are classified according to the situation (phenomenon) or reason.

(2) Although the vertical axis can represent the number of pieces, it is better to express it strongly in terms of money.

(3) Determine the period of data collection, from when to when, as the basis of Plato's data, and the period should be as regular as possible.

(4) The items are arranged on the horizontal axis from left to right according to the size of half.

(5) Draw a histogram.

(6) connect cumulative curves.

Plato's method (key control method) provides us with the ability to grasp important things and key things under the condition that we can't cover everything, and these important things are not judged by intuition, but are based on data, and are enhanced by graphics. That is, the hierarchical method provides a statistical basis, and Plato's law can help us grasp the key things.

(4) Causal analysis chart

Causal analysis chart takes results as characteristics and causes as factors, and the relationship between them is indicated by arrows. Causal analysis chart is a good way to fully mobilize employees' brains, find out the reasons and brainstorm, and it is especially suitable for democratic management of quality in working groups. When there is a certain quality problem and the reason is not clear, we can mobilize everyone to find the possible reasons for the problem, so that everyone can speak freely and list all the possible reasons.

the so-called causal analysis diagram is to illustrate many reasons for a certain result in a systematic way, that is, to express the relationship between the result (characteristic) and the cause (factor) in a diagram. Its shape is like fishbone, also known as fishbone map.

there must be a reason for the formation of a certain result, and we should try to find out the reason by graphic method. Dr. kaoru ishikawa, the Japanese quality control authority, first put forward this concept, so the characteristic reason diagram is also called [Ishikawa diagram]. Causal analysis chart can be used in various stages of general management and work improvement, especially in the early stage of establishing consciousness, which is easy to make the cause of the problem clear and design steps to solve the problem.

(1) Use steps of the analysis chart

Step 1: Gather relevant personnel.

gather experienced people related to this problem, preferably 4-11 people.

step 2: hang a large piece of white paper and prepare 2-3 colored pens.

step 3: the assembled personnel will speak on the reasons that affect the problem, and the contents of the speech will be recorded on the map, and no criticism or questioning is allowed in the middle. (Brainstorming)

Step 4: The time is about 1 hours, and collecting 21-31 reasons can end.

Step 5: As for the collected reasons, which one has the greatest influence, the leaders will take turns to speak, and after consultation, those who think it has the greatest influence will be circled in red.

step 6: as in step 5, for those who have been circled with a red circle, if they think it is the most important, they can be circled with two or three circles.

Step 7: Draw a new reason map, and remove the ones that are not circled. The columns with more circles will be given the highest priority.

Causal analysis chart provides a tool to capture important reasons, so the participants should include those who have experience in this work, so it is easy to be effective.

(2) Causal analysis diagram and Plato's use

To establish Plato, it is necessary to first establish statistical tables of required purposes by levels. The purpose of establishing Plato is to master a few important projects that have great influence on the overall situation. The reason diagram of reuse characteristics discusses the causes of these projects one by one, and takes improvement countermeasures. Therefore, the causal analysis diagram can be used alone or in conjunction with Plato.

(3) Re-analysis of Causal Analysis Diagram

Only by getting to the root of the problem can we fundamentally solve the problem. After the main causes of the problems are found out, the experimental analysis is carried out by the method of experimental design, and the specific experimental methods are proposed to find out the best working methods. The problems may be completely solved, which is to solve the problems and prevent them.

everyone and any enterprise have their goals, but in the process of pursuing the goals, there are always many tangible and intangible obstacles. What are these obstacles, how do they form, how to solve them and other issues are the main concepts of the cause analysis diagram method.

if a manager makes a concrete summary of the goals he pursues within the scope of his management work, we can know that there are not many in terms of projects. However, for every project you pursue, there are primary reasons and secondary reasons that will affect your goal. These reasons are the variables that prevent you from achieving your work.

how to list the pursued projects one by one, and sort out the main and secondary reasons that affect the achievement of each project, and use the causal analysis diagram to express them, and strengthen them in a planned way according to these reasons, which will make your management work more handy.

similarly, with these cause analysis diagrams, even if a problem occurs, it can be faster and more reliable in the process of solving the problem.

(5) Histogram

Histogram, also known as histogram, is a main tool to show the change of data. Histogram can be used to analyze the regularity of chaotic data, and the distribution of product quality characteristics can be seen intuitively, and the central value or distribution of data can be seen at a glance, which is convenient for judging its overall quality distribution. When making histogram, some statistical concepts are involved. First of all, the data should be grouped, so how to group reasonably is the key problem. Grouping is usually carried out according to the principle of equal group distance. The two key figures are the number of groups and the group distance.

(6) scatter diagram

scatter diagram, also known as correlation graph, is to stipple two variable data that may be related on a coordinate graph to indicate whether there is correlation between a pair of data. This kind of paired data may be the relationship between feature-cause, feature-feature and cause-cause. Through the observation and analysis, the correlation between the two variables can be judged. This problem is also common in practical production, such as the relationship between quenching temperature and workpiece hardness during heat treatment, and the relationship between the content of an element in the material and the strength of the material. Although this relationship exists, it is difficult to express it with accurate formula or functional relationship. In this case, it is very convenient to analyze it with correlation diagram. Assuming that there are a pair of variables X and y,x represents a certain influencing factor and Y represents a certain quality characteristic value, the data of X and Y can be represented by points on the coordinate diagram through experiments or collection, and the correlation between X and Y can be judged according to the distribution characteristics of points.

In our life and work, many phenomena and causes are related regularly, while others are related irregularly. If we want to understand it, we can judge the correlation between them by means of scatter diagram statistics.

(7) Control chart

Control chart is also called control chart. Since the use of control chart was first put forward by Dr. W.A.Shewhart of Bell Telephone Laboratory in the United States in 1924, control chart has been an important tool for scientific management, especially in quality management. It is a graph with control boundaries, which is used to distinguish whether the cause of quality fluctuation is accidental or systematic, and can provide information about the existence of systematic causes, so as to judge whether the production process is under control. Control charts can be divided into two categories according to their uses. One is the control chart for analysis, which is used to analyze the changes of quality characteristic values in the production process to see whether the process is in a stable and controlled state; Another kind is the control chart for management, which is mainly used to find out whether there is any abnormal situation in the production process to prevent unqualified products.

statistical management method is an effective tool for quality control, but the following problems must be paid attention to in application, otherwise the due effect will not be achieved. These problems are mainly: 1) The data is incorrect. There may be two reasons for the wrong data, one is the artificial use of the wrong data, the other is because the statistical method is not really mastered; 2) The data collection method is incorrect. If the sampling method itself is wrong, the subsequent analysis method is useless no matter how correct it is; 3) The record of data is wrongly copied; 4) Handling of abnormal values. Usually, the data obtained in the production process always contains some anomalies.