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ABSTRACT In this paper, we suggest a linear programming formulation that allows for solving volume and capacity planning prob- lems in semiconductor manufacturing systems. We assume a general product structure that includes commodities, cus- tom products, finished products between these two extreme classes, and several types of unfinished products. Compu- tational experiments with respect to the required level of detail of bottleneck modeling are performed. Furthermore, we investigate the sensitivity of the model with respect to noisy demand data. It turns out that the number of modeled bottleneck is not crucial and that our approach can treat noisy demand data appropriately. 1 INTRODUCTION This research is motivated by mid-term production plan- ning problems in semiconductor manufacturing systems. Here, volumes for non-final products and committed vo- lumes for final products have to be determined taking the finite capacity of the manufacturing systems and the re- quested demand into account. We call this type of problems volume and capacity planning problems because production volumes are deter- mined that lead to a certain capacity allocation over time. Volume and capacity planning is challenging in the semi- conductor industry (cf. Geng and Jiang 2008 and Gupta et al. 2006) because of complex manufacturing processes: usually be- tween 400 and 800 process steps are required on a large number of tools to produce an integrated circuit. Typically, semiconductor manufacturing enterprises are organized as manufacturing net- works that contain dozens of facilities around the world. frequent changes of technology and products: new type of tools are required to produce state of the art integrated circuits. The life-cycle of products is becoming very short. long lead times and large costs for extending ca- pacity: capacity expansions are time consuming and very expensive. highly uncertain demand and capacity: the de- mand for integrated circuits is very volatile. Semi- conductor manufacturing systems are stochastic systems because of tool break downs and rework. Therefore, the capacity offered by the manufactur- ing system is to a certain degree unpredictable. Volume and capacity planning decisions are important in- structions for lower level planning and scheduling deci- sions, for example for master planning. There is some work related to strategic capacity plan- ning questions in semiconductor manufacturing (cf. the more detailed discussion in Section 2.2). However, ques- tions of an appropriate level of detail in modeling or ques- tions related to the consideration of stochastic demand are only inadequately addressed so far. Based on a linear pro- gramming formulation, we study the question which level of detail is necessary in modeling the bottlenecks that con- strain the capacity of the manufacturing system. However, our model is more an operative than a strategic planning model.
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This note was uploaded on 04/11/2011 for the course ECE 357 taught by Professor Subjolly during the Spring '11 term at National University of Ireland, Galway.

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