Variation mode and effect analysis

In this paper, we introduce an engineering method, variation mode and effect analysis (VMEA) developed to systematically look for noise factors affecting key product characteristics (KPCs) early in product development. Conducted on a systematic basis, the goal of VMEA is to identify and prioritize noise factors that significantly contribute to the variability of KPCs and might yield unwanted consequences with respect to safety, compliance with governmental regulations, and functional requirements. As a result of the analysis, a variation risk priority number (VRPN) is calculated which directs the attention to areas where reasonably anticipated variation might be detrimental.

[1]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[2]  Ida Gremyr,et al.  Use and knowledge of robust design methodology: A survey of Swedish industry , 2003 .

[3]  Anne C. Shoemaker,et al.  Robust design: A cost-effective method for improving manufacturing processes , 1986, AT&T Technical Journal.

[4]  W. A. Shewhart,et al.  Statistical method from the viewpoint of quality control , 1939 .

[5]  Don Clausing Total quality development : a step-by-step guide to world class concurrent engineering , 1994 .

[6]  Anna C. Thornton,et al.  More than Just Robust Design: Why Product Development Organizations Still Contend with Variation and its Impact on Quality , 2000 .

[7]  M. J. Harry,et al.  SIX SIGMA : A BREAKTHROUGH STRATEGY FOR PROFITABILITY , 1998 .

[8]  R. N. Kackar Off-Line Quality Control, Parameter Design, and the Taguchi Method , 1985 .

[9]  R. N. Kackar Response: Off-Line Quality Control, Parameter Design, and the Taguchi Method , 1985 .

[10]  Abbie Griffin,et al.  The Voice of the Customer , 1993 .

[11]  Raghu N. Kacker,et al.  A methodology for planning experiments in robust product and process design , 1988 .

[12]  Madhan Shridhar Phadke,et al.  Quality Engineering Using Robust Design , 1989 .

[13]  Thong Ngee Goh,et al.  A pragmatic approach to experimental design in industry , 2001 .

[14]  W. J. Hill,et al.  The Impact of Six Sigma Improvement—A Glimpse into the Future of Statistics , 1999 .

[15]  Bovas Abraham,et al.  VARIATION REDUCTION AND ROBUST DESIGNS , 2001 .

[16]  Larry R. Smith,et al.  Six Sigma and the Evolution of Quality in Product Development , 2001 .

[17]  A. R. Crathorne,et al.  Economic Control of Quality of Manufactured Product. , 1933 .