Abstract
Supply chain management (SCM) in semiconductor manufacturing differs from many other SCM applications in that it has to simultaneously consider both long and short time scale stochasticity and nonlinearity. We present a two-level hierarchical structure for SCM motivated by these considerations. A linear programming (LP)-based strategic planning module forms the outer loop which makes long timescale decisions on the starts of factories. A model predictive control (MPC) based tactical execution module forms the inner loop which generates short timescale decisions on the starts of factories by considering the stochasticity and nonlinearity on both supply and demand sides. Two representative case studies are examined under diverse realistic conditions with this integrated framework. It is demonstrated that given conditions of stochasticity, nonlinearity, and forecast error this hierarchical decision structure can be tuned to manage representative semiconductor manufacturing supply chains in a manner appealing to operations.
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This work was supported by grants from the Intel Research Council and the National Science Foundation (CMMI-0432429).
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Wang, W., Rivera, D.E. & Mittelmann, H.D. Inner and outer loop optimization in semiconductor manufacturing supply chain management. Comput Manag Sci 6, 411–434 (2009). https://doi.org/10.1007/s10287-008-0081-4
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DOI: https://doi.org/10.1007/s10287-008-0081-4