Using in-line equipment condition and yield information for maintenance scheduling and dispatching in semiconductor wafer fabs

Citation
Tw. Sloan et Jg. Shanthikumar, Using in-line equipment condition and yield information for maintenance scheduling and dispatching in semiconductor wafer fabs, IIE TRANS, 34(2), 2002, pp. 191-209
Citations number
38
Categorie Soggetti
Engineering Management /General
Journal title
IIE TRANSACTIONS
ISSN journal
0740817X → ACNP
Volume
34
Issue
2
Year of publication
2002
Pages
191 - 209
Database
ISI
SICI code
0740-817X(200202)34:2<191:UIECAY>2.0.ZU;2-R
Abstract
Yield is one of the most important measures of manufacturing performance in the semiconductor industry, and equipment condition plays a critical role in determining yield. Researchers and practitioners alike have traditionall y treated the problems of equipment maintenance scheduling and production d ispatching independently, ignoring how equipment condition may affect diffe rent product types or families in different ways. This paper addresses the problem of how to schedule maintenance and production for a multiple-produc t, multiple-stage production system. The problem is based on the situation found in semiconductor wafer fabrication where the equipment condition dete riorates over time, and this condition affects the yield of the production process. We extend a recently developed Markov decision process model of a single-stage system to account for the fact that semiconductor wafers have multiple layers and thus make repeated visits to each workstation. We then propose a methodology by which the single-stage results can be applied in a multi-stage system. Using a simulation model of a four-station wafer fab, we test the policies generated by the model against a variety of other main tenance and dispatching policy combinations. The results indicate that our method provides substantial improvements over traditional methods and perfo rms better as the diversity of the product set increases. In the scenarios examined, the reward earned using the policies from the combined production and maintenance scheduling method was an average of more than 70% higher t han the reward earned using other policy combinations such as a fixed-state maintenance policy and a first-come, first-serve dispatching policy.