Research situation of concurrent tolerance design has been analyzed. As fuzzy factors are objective and unavoidable in concurrent tolerance design, fuzzy optimization theory is applied in the design. A new mathematica...Research situation of concurrent tolerance design has been analyzed. As fuzzy factors are objective and unavoidable in concurrent tolerance design, fuzzy optimization theory is applied in the design. A new mathematical model of concurrent tolerance design is constructed.展开更多
Using Response Surface Methodology (RSM), an optimizing model of concurrent parameter and tolerance design is proposed where response mean equals its target in the target being best. The optimizing function of the mod...Using Response Surface Methodology (RSM), an optimizing model of concurrent parameter and tolerance design is proposed where response mean equals its target in the target being best. The optimizing function of the model is the sum of quality loss and tolerance cost subjecting to the variance confidence region of which six sigma capability can be assured. An example is illustrated in order to compare the differences between the developed model and the parameter design with minimum variance. The results show that the proposed method not only achieves robustness, but also greatly reduces cost. The objectives of high quality and low cost of product and process can be achieved simultaneously by the application of six sigma concurrent parameter and tolerance design.展开更多
基金This Project is supported by National Natural Science Foundation of China.
文摘Research situation of concurrent tolerance design has been analyzed. As fuzzy factors are objective and unavoidable in concurrent tolerance design, fuzzy optimization theory is applied in the design. A new mathematical model of concurrent tolerance design is constructed.
基金the National Natural Science Foundation of China (No:70572044)New Central Elitist(No:04-0240)
文摘Using Response Surface Methodology (RSM), an optimizing model of concurrent parameter and tolerance design is proposed where response mean equals its target in the target being best. The optimizing function of the model is the sum of quality loss and tolerance cost subjecting to the variance confidence region of which six sigma capability can be assured. An example is illustrated in order to compare the differences between the developed model and the parameter design with minimum variance. The results show that the proposed method not only achieves robustness, but also greatly reduces cost. The objectives of high quality and low cost of product and process can be achieved simultaneously by the application of six sigma concurrent parameter and tolerance design.
