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General Information
    • ISSN: 2010-3697
    • Frequency: Bimonthly
    • DOI: 10.7763/IJMO
    • Editor-in-Chief: Prof. Adrian Olaru
    • Executive Editor: Ms.Yoyo Y. Zhou
    • Abstracting/ Indexing: Engineering & Technology Digital Library, ProQuest, Crossref, Electronic Journals Library, DOAJ, Google Scholar, EI (INSPEC, IET).
    • E-mail ijmo@iacsitp.com
Editor-in-chief
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2016 Vol.6(3): 177-187 ISSN: 2010-3697
DOI: 10.7763/IJMO.2016.V6.524

A Decision Support System for Optimization of Operator Schedule in Semiconductor Manufacturing Industries

I-Hui Li, Kuan-Ju Lai, and I-En Liao
Abstract—In the semiconductor manufacturing industry, most factories maintain a round-the-clock production operation. As a result, the problem arises as to how best to ensure the continuous operation of the factory while simultaneously meeting the leave requirements of the operators. Traditionally, the operator schedules are artificially dispatched by the operator schedule supervisor. That is, the operators submit their leave requests, and the operator schedule supervisor approves or rejects the requests in accordance with government and company regulations and the available manpower. In practice, a good operator schedule should not only meet the factory operation requirements, but should also respect the autonomy of the employees. Striking a balance between the two is highly challenging, and can result in a lose-lose situation if performed badly. Moreover, the manual scheduling process is extremely time consuming. Accordingly, the present study proposes a decision support system (DSS) for solving the operator scheduling problem using a genetic algorithm based on a joint consideration of government regulations, company policy, department regulations and personnel preferences. The proposed DSS defines multi-criterion: employee rights and company benefits for assessment. The experimental results show that the proposed DSS reduces the operator scheduling time from around 3~5 days to approximately 33 minutes for one manufacturing section with four shifts. Moreover, it is shown that the effectiveness of the proposed DSS in improving the benefits to the company while simultaneously satisfying the employees' rights is around 55% higher than that of the manual scheduling system.

Index Terms—Decision support system, multi-objective genetic algorithms, operator schedule problem, scheduling.

I. H. Li is with the Ling Tung University, Taichung, Taiwan (e-mail: sanityih@gmail.com).
K. J. Lai and I. E. Liao was with Department of Computer Science and Engineering, National Chung Hsing University, Taichung, Taiwan (e-mail: ieliao@nchu.edu.tw).

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Cite: I-Hui Li, Kuan-Ju Lai, and I-En Liao, "A Decision Support System for Optimization of Operator Schedule in Semiconductor Manufacturing Industries," International Journal of Modeling and Optimization vol. 6, no. 3, pp. 177-187, 2016.

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