Six Sigma Applied Research Supported By Multi-Tool Intergration

In the present, quality has become the key element of constituted enterprise competitiveness. Continuous improvement of product quality and the quality of management capabilities is the base of enterprise. From the customer's point of view of quality issues,6σquality management uses a scientific way to approach zero defect quality, reduce business costs and increase competitiveness of enterprises significantly. So, it has achived wide concern and attention of the industry.6σmanagement requires a range of integrated tools support. Therefore, the study of 6σmulti-tool integration to support application delivery has important theoretical significance and practical value.According to the core improved method of 6σmanagement -DMAIC model, the 6a implementation framework, supported by muti-integration tool, is established. The definition phase problem selection and control phases of abnormal pattern recognition during the improving process are studied in this issue.Considering that the definition phase of the current approach to the problem can not be well defined and the choice is inadequate, this paper proposes a method of integrating QFD/FMEA, consideres customer needs, problems and damage frequency, in order to achieve the proper definition of the problem and options. Considering the actual implementation process of the fuzzy data, a fuzzy set associated with the gray QFD/FMEA integration method is used to realize the assessment of fuzzy information, so as to define all kinds of issues and options effectively.The control phase of DMAIC improvement is to achieve assurance and continuous improvement in front of phase. Aiming at the process of implementing enterprise only pay attention to document improvements in process capability analysisin at this stage, while ignoring continuous process measurement (control) and easily lead to the improvement of project failure problems, uses BP neural based control chart pattern recognition method exception to achieve real-time monitoring of the production site for the timely detection of abnormal production.With reversing radar 6a of the DMAIC quality improvement empirical study, QFD/FMEA integration method is used to select G1G2 gap and define the problem. Measurement system is analysised to reduce the error caused by measurement. Variance analysis and experimental design method is used to analysis, improve and optimize the key factors, then get the best parameters of the key factors. At last, control chart and process capability analysis method is used to control and monitoring G1G2 production to prevent abnormal fluctuations and guarantee the improve results.