A Model to Determine the Best Capacity Scale of Fab for Semiconductor Fabrication
In order to meet market demand and increase competitive advantage, semiconductor manufacturing companies will expand the capacity in the existed fab or build new fab. Normally, except more advanced technology, the most significant characteristic of new fab is larger scale than existed fab. Although there are many benefits of a so-called Giga-fab, such as lower cost, shorter cycle time and more flexibilities etc., the Giga-fab scale will also increase risk of production management significantly. Therefore, the best capacity scale of Giga-fab is still an issue in this decade. In this work, a model to determine the best capacity scale of fab is proposed. Based on the opinions of experts, four decision criteria are defined, including demand, production performance, cost and accident. Besides, fuzzy analytic hierarchy process (FAHP) is applied to decide the weighting of these decision criteria. Regarding to the impact of decision criteria on capacity scale, four scoring equations are constructed. First of all, the 5-year demand forecast is considered as demand criterion and compared with the capacity scale. Secondly, production performance is focused on the changes of products’ cycle time under each specific scale level and the concept of X-factor is applied to the scoring. Thirdly, the cost criterion is based on the concept of economies of scale. Finally, regarding to the accident criterion, we use the concept of the insurance fee under different scale and risk to estimate the level of accident for different scale. By combining these scores of four criteria with their weightings, the best capacity scale can be determined ultimately.
文章引用: 杜莹美 , 张家玮 (2015) 晶圆厂最适产能规模决策模式。 管理科学与工程， 4， 13-18. doi: 10.12677/MSE.2015.41B003
 Chou, Y.C., Cheng, C.T., Yang F.C. and Liang, Y.Y. (2007) Evaluating alternative capacity strategies in semiconductor manufacturing under uncertain demand and price scenarios. International Journal of Production Economics, 105, 591-606.
 Hood, S.J., Bermon, S. and Barahona, F. (2003) Capacity planning under demand uncertainty for semiconductor manufacturing. IEEE Transactions on Semiconductor Manufacturing, 16, 273-280.
 Cakanyıldırım, M. and Roundy R.O. (2002) Optimal capacity expansion and contraction under demand uncertainty. Working Paper.
 Lin, J.F. (2006) The study of the economical scale of a semiconductor plant through simulations. Master Thesis, Department of Mechanical Engineering, National Taiwan University, Taipei.
 Hung, Y.F. and Leachman, R.C. (1996) A production planning methodology for semiconductor manufacturing based on iterative simulation and linear programming calculations. IEEE Transactions on Semiconductor Manufacturing, 9, 257-269.
 Driver, C. and Goffinet, F. (1998) Investment under demand uncertainty, exante pricing, and oligopoly. Review of Industrial Organization, 13, 409-423.
 Saaty, T.L. (1980) The Analytic Hierarchy Process. McGraw-Hill, New York.
 Buckley, J.J. (1985) Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17, 233-247.
 Teng, J.Y. and Tzeng, G.H. (1989) The content and application of analytic hierarchy process. Journal of the Chinese Statistical Association, 27, 13767-13786.
 Tzeng, G.H. (2001) Project evaluation: The lecture notes of theory and practice. Department of Industrial Engineering and Management Information, Huafan University, Taipei.