A unified framework for probabilistic sequential tolerance control
Sequential tolerance control (STC) is a methodology that uses available measurement information at the completion of one manufacturing operation to position the set point for subsequent operations. It has been shown that STC can lead to inferior solutions when the manufacturing process distributions are skewed. This paper presents an adaptive sphere-fitting method (ASF-STC) that adjusts for such skewness. ASF-STC requires as inputs both the direction of skewness and the probability distribution parameters for each operation. Heuristic methods for estimating each of these inputs are presented. Through computational testing, ASF-STC is shown to offer significant improvements over STC when such skewness exists.
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Document Type: Research Article
Affiliations: Department of Industrial and Manufacturing Engineering The Pennsylvania State University 310 Leonhard Building University Park PA 16802
Publication date: 2004-04-01