Maximization of manufacturing yield of systems with arbitrary distributions of component values

Maximization of manufacturing yield of systems with arbitrary distributions of component values

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Article ID: iaor200242
Country: Netherlands
Volume: 99
Issue: 1
Start Page Number: 373
End Page Number: 383
Publication Date: Dec 2000
Journal: Annals of Operations Research
Authors: , ,
Keywords: yield management
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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