The quality cost of non-conformance associated with first run production builds is typically more than five times that of later production runs. If a manufacturing organization is to gain market share and increase its profitability, it must explore methods of accelerating its learning curves through defect prevention. Current "Transition to Production" concept methodologies attempt with limited success to accelerate organizational learning through Design for Manufacturability (DFM), design phase dimensional management studies, manufacturing floor statistical methods (SPC, DOE, etc.), and various qualitative strategies. While each of these techniques are effective to some degree in reducing future nonconformances, an integrated, design-phase approach utilizing current technology is needed. "Virtual Process Capability" (VPC) is a methodology for integrating statistical process capability knowledge directly into the hardware design phase, resulting in the improved performance and reduced product costs typically associated with mature product manufacturing. The intent behind the methodology is to realistically simulate the manufacture of hardware products by understanding their underlying model equations and the statistical distributions of each involved contributing parameter. Once each product has been simulated and an expected percentage defective has been estimated, mathematical programming and statistical quality engineering techniques are then utilized for improvement purposes. Data taken from the practical application of this methodology at Raytheon Aircraft has conservatively estimated that for each dollar invested ten are saved. As a technical extension to this developed methodology, statistical insights and methods are provided as to how product and process improvement analysis is best accomplished. Included within this area of discussion is the statistical development and validation of improved measures for the more efficient detection of dispersion and mean effects than that of more traditional methods. Additionally, the use of mathematical programming techniques is creatively employed as an improved mechanism in the optimization of nominal-the-best type problems.
| Identifer | oai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:dissertations-3056 |
| Date | 01 January 1998 |
| Creators | Mackertich, Neal A |
| Publisher | ScholarWorks@UMass Amherst |
| Source Sets | University of Massachusetts, Amherst |
| Language | English |
| Detected Language | English |
| Type | text |
| Source | Doctoral Dissertations Available from Proquest |
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