Abstract
In this correspondence, we have formulated a stochastic optimization problem to find the optimal threshold values to reduce the overkills of dies under a tolerable retest level in wafer testing process. The problem is a hard optimization problem with a huge solution space. We propose an ordinal optimization theory-based two-level algorithm to solve for a vector of good enough threshold values and compare with those obtained by others using a set of 521 real test wafers. The test results confirm the feature of controlling the retest level in our formulation, and the pairs of overkills and retests resulted from our approach are almost Pareto optimal. In addition, our approach spends only 6.05 min in total in a Pentium IV personal computer to obtain the good enough threshold values.
Original language | English |
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Pages (from-to) | 1229-1234 |
Number of pages | 6 |
Journal | IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans |
Volume | 36 |
Issue number | 6 |
DOIs | |
State | Published - 11 2006 |
Externally published | Yes |
Keywords
- Genetic algorithm (GA)
- Neural network
- Ordinal optimization (OO)
- Overkill
- Retest
- Stochastic optimization
- Water probing