Research Of Statistical Process Control Technology In ABS/ESC Block Production Of JSYT Corporation

In today’s highly competitive market environment, how to reduce costs, improveproduct quality is an outstanding problem of every Chinese company must be faced. Usingadvanced quality management and process control tools to prevention and monitoring theproduction process, improve product quality, reduce costs has been widely carried out indeveloped countries. Statistical process control techniques are widely used in theautomotive industry from the1950s were introduced to Japan, followed by large-scaleimplementation in Europe and the United States automotive industry, steel industry. Now ithas become an important part of the major automotive industry quality system certification.Although the statistical process control, zero defect management, lean productionmanagement have been gradually introduced into Chinese enterprises. The process controllevel of Chinese enterprises has not been markedly improved by implementation ofstatistical process control.In this paper, we apply statistical process control to the ABS/ESC blocks’ production,combining with the products’ actual situation of JSYT.Using fuzzy comprehensiveevaluation method to implement a comprehensive evaluation of statistical process control.Providing a new way of evaluate the results of process control.The article first analyzes the current situation of statistical process controlapplications JSYT. Then, find the main problems in the process of extrusion. Analyzingthe main factors of affecting the ABS/ESC blocks quality, collecting relevant data to drawthe process control charts, analyze the abnormal of control charts and calculate the valueof the process capability. Some relative improvement measures were established toimprove the ABS/ESC blocks quality. Use of multivariate statistical process analysis toidentify the quantitative relationship between the key processes and factors that causechanges in the improvement process, the analysis of various process parameters on the sizeof the key processes impact. Finally is the conclusion and related Suggestions.