Optimization of Test/Diagnosis/Rework Location(s) and Characteristics in Electronic System Assembly

Abstract

Abstract. In this paper, an optimization methodology is used to select the locations and characteristics of test, diagnosis and rework operations in electronic systems assembly processes. Real-coded genetic algorithms are used to perform a multi-variable optimization that minimizes the yielded cost of products resulting from an assembly process that includes test/diagnosis/rework operations characterized by costs, yields fault coverage, and rework attempts. A general complex process flow is analyzed using the algorithms proposed in this paper, and a multichip module assembly process flow is used to demonstrate that the methodology can identify optimum test and rework solutions that result in a reduction in yielded cost.

Estimating production test properties from test measurement data

“…Work on test optimization is found in the statistics, operations research, electronic engineering, software engineering and production management literature; recent papers from these fields include , , , and . A wide variety of models and optimization algorithms have been proposed; ant colony and genetic algorithms are currently popular for optimization.…”