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JACIII Vol.17 No.4 pp. 526-534
doi: 10.20965/jaciii.2013.p0526
(2013)

Paper:

Dynamic Scheduling Approaches to Wafer Test Scheduling with Unpredictable Error

Tsubasa Matsuo*, Masahiro Inuiguchi*, and Kenichiro Masunaga**

*Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama-cho, Toyonaka, Osaka 560-8531, Japan

**Renesas Electronics Co., 2-6-2 Otemachi, Chiyoda-ku, Tokyo 100-0004, Janapn

Received:
February 28, 2013
Accepted:
April 12, 2013
Published:
July 20, 2013
Keywords:
semiconductor manufacturing, simulation, genetic-based machine learning
Abstract

Scheduling of semiconductor wafer testing processes can be seen as a resource constraint project scheduling problem (RCPSP). However, it includes uncertainties caused by human factors, wafer errors and so on. Because some uncertainties are not simply quantitative, range estimation of the parameters would not be very useful. Considering such uncertainties, finding a good situation-dependent dispatching rule would be more suitable than solving the RCPSP under uncertainties. In this paper we apply the Pitts approach, one of the genetic algorithms, to the situation-dependent dispatching rule acquisition. We compare the obtained rule with the simple dispatching rules and examine the effectiveness and usefulness of the obtained rule in the problems with unpredictable wafer errors.

Cite this article as:
Tsubasa Matsuo, Masahiro Inuiguchi, and Kenichiro Masunaga, “Dynamic Scheduling Approaches to Wafer Test Scheduling with Unpredictable Error,” J. Adv. Comput. Intell. Intell. Inform., Vol.17, No.4, pp. 526-534, 2013.
Data files:
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Last updated on Oct. 15, 2021