The method of data stratification is essentially the same, and the data collected under the same conditions are summarized for comparative analysis. Because in actual production, there are many factors that affect the quality change. If these factors are not distinguished, 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 time and shift, according to the type of equipment used, according to the feeding time and raw material composition, according to the inspection method and use conditions, according to different defective products and so on. The data stratification method is often used in combination with the above statistical analysis table.

App application

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

Scientific management emphasizes management skills to make up for the shortcomings of previous management based on experience and visual judgment. This management technology not only needs to establish correct ideas, but also needs to apply data to analyze the work and take correct measures.

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

For example, the aviation market in China has become more and more fierce with the opening up in recent years. In order to win the market, airlines have not only strengthened various measures, but also made great efforts in service quality. We can often see customer satisfaction surveys on the plane. The 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 reservation and waiting; Aircraft can be divided into flight attitude, catering, sanitation and so on. Through these surveys, we can collect these data and get where to strengthen the quality of service.