Product quality characteristic error traceability analysis method based on multi-source perception

Abstract

The invention relates to a product quality characteristic error traceability analysis method based on multi-source perception, which comprises the following steps of establishing causal relationship between processes by using historical data; screening the historical data so as to compose the screened historical data into a sample space; taking the sample space as the analysis standard, and monitoring the real-time data by a T2 control chart method; performing the orthogonal decomposition on the outbound T2 value according to the causality to obtain decomposition terms; carrying out the out-of-bounds analysis on the T2 statistic value of the decomposition term, and locating the problem procedure. The method of the invention utilizes a large amount of multiple historical data to complete the analysis of the correlation relation between the processes, and reduces the influence brought by the subjective factors. The out-of-bounds T2 value is decomposed according to the relationship directed graph obtained from the analysis process of the relationship between processes, so as to determine the problem process, achieve the accurate grasp of the process, and then achieve the purpose of problem traceability.

Description

technical field [0001] This method involves the fields of process analysis, model static and / or dynamic analysis, and in particular relates to a method for traceability analysis of product quality characteristic errors based on multi-source perception, which is used for traceability of process problems. Background technique [0002] The concept of statistical process control (Statistical Process Control) originated in the 1920s, with the control chart proposed by Dr. Shewhart of the United States as the main symbol. Since this concept was put forward, it has been widely used in industry and service industry. With the help of mathematical statistics knowledge, it analyzes and monitors the fluctuations in the production process, and proposes preventive measures, so that the production process is in a controlled state that is only affected by random factors. Control charts are the most important tools in statistical process control. According to different purposes, they can be...

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Problems solved by technology

In the prior art, the use of T 2 When the control chart monitors the actual processing process, it often occurs that the individual processes are monitored without loss of control, but the entire process is monitored but the phenomenon of loss of control occurs, which makes it difficult to locate the error source accurately; and in actual situations, The causal relationship network between processing procedures is mostly established based on process specification documents, expert evaluation, etc. Human subjective factors account for a large proportion, and the established network relationship often cannot scientifically and effectively reflect the relationship between processes

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