Semiconductor Manufacturer’s Capacity Reservation with Substitution

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Abstract:

When the products are withdrawn from the market, some capacity is reserved for a certain time because the manufacturer is responsible for providing after-sale service during the entire quality guarantee period. We consider a capacity reservation problem of a semiconductor manufacturer with two kinds of products and the corresponding demands are random. The demands can be substituted when one type of capacity has been depleted. The optimization goal is to determine the reserved capacity for each type of product. The problem is formulated by a stochastic programming model in which the objective is to minimize the total service cost of the manufacturer. We show that the concavity and convexity of the optimal function is depended on the joint distribution function density of the products. An iterative algorithm is designed to find the optimal capacity conservation quantities and a numerical experiment is used to illustrate its effectiveness.

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571-575

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June 2012

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] Hsieh B.H., S.C. Chang, C.H. Chen. 2000. Dynamic scheduling rule selection for fab operations. Semiconductor Manufacturing Technology Workshop, Hsinchu, Taiwan.

DOI: 10.1109/smtw.2000.883097

Google Scholar

[2] Teunter R H, L. Fortuin. 1998. End-of-life service: A case study. Operational Research, Vol. 107, No. 4, pp.: 19-34.

DOI: 10.1016/s0377-2217(97)00365-2

Google Scholar

[3] Alstrup, J., S. Boas, O.B.G. Madsen, R.V.V. Vidal. 1986. Booking policy for flights with two types of passengers. European Journal of Operational Research, Vol. 27, No. 3, pp.274-288.

DOI: 10.1016/0377-2217(86)90325-5

Google Scholar

[4] Bitran, G.R., S. Dasu. 1992. Ordering policies in an environment of stochastic yields and substitutable demands. Operations Research, Vol. 40, No. 5, pp.999-1017.

DOI: 10.1287/opre.40.5.999

Google Scholar

[5] Ha, A.Y. 2000. Stock rationing in an M/E/1 make-to-stock queue. Management Science, Vol. 46, No. 1, pp.77-87.

DOI: 10.1287/mnsc.46.1.77.15135

Google Scholar

[6] Tomlin, B., Y. Wang. 2008. Pricing and operational recourse in co-production systems. Management Science, Vol. 54, No. 3, pp.522-537.

DOI: 10.1287/mnsc.1070.0807

Google Scholar

[7] Shumsky, R.A., F.Q. Zhang. 2009. Dynamic Inventory Management with Substitution. Operations research, Vol. 57, No. 3, pp.671-684.

Google Scholar

[8] R. Dekker, M. J. Kleijn and P. J. de Rooij. 1998. A spare parts stocking policy based on equipment criticality. International Journal of Production Economics, Vol. 56-57, pp.69-77.

DOI: 10.1016/s0925-5273(97)00050-9

Google Scholar

[9] Bitran, G.R., D. Tirupati. 1988. Planning and scheduling for epitomical wafer production facilities. Operation Research, Vol. 36, No. 1, pp.34-49.

DOI: 10.1287/opre.36.1.34

Google Scholar

[10] Yoo C.S. 2008. Semiconductor manufacturing technology. World Scientific, Singapore.

Google Scholar

[11] Patterson D.A.,J.L. Hennessy. 2008. Computer Organization and Design (4th Edition), Elsevier, Netherlands.

Google Scholar

[12] Liao S.H., T.C. Hu. 2007. Knowledge transfer and competitive advantage on environmental uncertainty: An empirical study of the Taiwan semiconductor industry. Technovation, Vol. 27, pp.402-411.

DOI: 10.1016/j.technovation.2007.02.005

Google Scholar