Research On Supply-chain Quality Control Based On 6Sigma

With the development of world economy and the intensifies of global competition, to highlight the development of core competitiveness, the business organization gradually has formed the supply-chain pattern making up of a variety of associated organizations. So the attention on quality management has changed from the enterprise's own product quality to the overall quality of the supply chain to meet the final customers'requirement to the quality of products and services.Based on the requirement of supply chain quality management, after analyzing some methods of supply chain quality management at home and abroad, this paper finds that domestic applications about 6Sigma quality controlling method are limited in a phase or process of the whole supply chain and based on exact statistics which are lack of flexibility about fuzzy data.The main work of this article is building a set of supply chain quality control methods based on 6Sigma: First, it uses improved value stream mapping integrated with value stream mapping and fishbone diagram to assess the weight of every phase in the supply chain according to the influence of the core company and the control ability of the third party logistics enterprise. Second, it finds the key factor using brain storming and AHP to ensure and the method of fuzzy comprehensive evaluation to analyse the quality factors and their weight with the use of key performance indicators. Then, through developing the DMAIC method in each duty-cycle, it finds the most impotant link and factors which affected the supply-chain quality in the last duty-cycle , improves them with improving schedule, and then summarizes the unclosed factors convenient for improvement in next duty-cycle... At last, it will achieve the goal of customer about 6Sigma with the PDCA cyclic methods.The method of supply-chain quality control build in this paper breaks though the bottleneck that the use of 6Sigma must base on exact statistics. It brings both exact statistics and fuzzy data into quality control to the whole supply-chain by the method of fuzzy comprehensive evaluation and the design of indicators. This paper also shows the lack of this method like that it cannot deal with the indicators which are more complex and the analysis need more in accuracy, which becomes the direction of the study in the future.