Maximization of Manufacturing Yield of Systems with Arbitrary Distributions of Component Values |
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Authors: | Abbas Seifi K. Ponnambalam Jiri Vlach |
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Affiliation: | (1) Department of Industrial Engineering, Amirkabir University of Technology, Tehran, P.O. Box 15875-4413, Amirkabir, Iran;(2) Department of Systems Design Engineering, University of Waterloo, Waterloo, Ontario, Canada, N2L 3G1;(3) Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario, Canada, N2L 3G1 |
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Abstract: | This paper presents a general method for maximizing manufacturing yield when the realizations of system components are independent random variables with arbitrary distributions. Design specifications define a feasible region which, in the nonlinear case, is linearized using a first-order approximation. The method attempts to place the given tolerance hypercube of the uncertain parameters such that the area with higher yield lies in the feasible region. The yield is estimated by using the joint cumulative density function over the portion of the tolerance hypercube that is contained in the feasible region. A double-bounded density function is used to approximate various bounded distributions for which optimal designs are demonstrated on a tutorial example. Monte Carlo simulation is used to evaluate the actual yields of optimal designs. |
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Keywords: | yield maximization design optimization asymmetrical PDF |
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