This paper presents a test, diagnosis, and rework analysis model for use in manufacturing process modeling. The approach includes a model of functional test operations characterized by fault coverage, false positives, and defects introduced in test, in addition to rework and diagnosis (diagnostic test) operations that have variable success rates and their own defect introduction mechanisms. The model accommodates multiple rework attempts on a product instance. The model is applied within a framework for optimizing the location(s) and characteristics (fault coverage/test cost, rework success rate/rework cost) of Test/Diagnosis/Rework (TDR) operations in a general manufacturing process. A new search algorithm called Waiting Sequence Search (WSS) is applied to traverse a general process flow to perform the cumulative calculation of a yielded cost objective function. Real-Coded Genetic Algorithms (RCGAs) are used to perform a multi-objective optimization that minimizes yielded cost. An example of a general complex process flow is used to demonstrate the feasibility of the algorithm.

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