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Tolerance Optimization with Markov Chain Process  

Lee, Jin-Koo (Dept.of Mechanical Engineering, Seoul National University of Technology)
Publication Information
Transactions of the Korean Society of Machine Tool Engineers / v.13, no.2, 2004 , pp. 81-87 More about this Journal
Abstract
This paper deals with a new approach to tolerance optimization problems. Optimal tolerance allotment problems can be formulated as stochastic optimization problems. Most schemes to solve the stochastic optimization problems have been found to exhibit difficulties in multivariate integration of the probability density function. As a typical example of stochastic optimization the optimal tolerance allotment problem has the same difficulties. In this stochastic model, manufacturing system is represented by Gauss-Markov stochastic process and the manufacturing unit availability is characterized for realistic optimization modeling. The new algorithm performed robustly for a large deviation approximation. A significant reduction in computation time was observed compared to the results obtained in previous studies.
Keywords
Tolerance Optimization; Stochastic Process; Yield; Gauss-Markov Process;
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