Modeling the Impact of Supply Contract Modifications in Mid-term Master Planning of Semiconductor Manufacturing: A Foundry Model

  • Marwa Attiya

Student thesis: Master's Thesis


This thesis deals with the dynamics of modifying supply contracts in semiconductor manufacturing that arises at a mid-term production planning level i.e., known as master production schedule or master planning. In this level, planning aims to find the best match between supply and demand, and to drive the manufacturing activities by dealing with customer orders, managing inventories, utilizing the limited resources, and releasing orders to various production sites. The viability and the accuracy of these decisions can dramatically affect the profitability. The focus of this work would be on the wafer fabrication stage (i.e., the front-end operations); where raw silicon wafers are used to create the patterns of the integrated circuits (ICs) prior to being cut into the individual microchips, tested, and packaged (i.e., the back-end operations). The fabrication process of ICs on silicon wafer is arguably the most complex manufacturing process within the semiconductor supply network characterized by globalization; production is no longer confined to a single in-house fabrication site and could also be outsourced to external silicon foundries. Other challenges involved are the several-hundred processing steps, the re-entrant flows, the frequent disturbances, the capital-intensive assets, the high degree of automation, the short product life cycle and the market demand fluctuations. The development of planning approaches to quantitatively address the ever-present uncertainties within the semiconductor manufacturing networks remains challenging, given the specifics of this industry. A two-stage demand-driven model is developed and evaluated; the mixed-integer program is capable to simulate changes on production deployment plan by initiating or seizing the production as a response to any changes in demand or available capacity, and to find the optimal scenario-specific production distribution while taking the capacity utilization and the industrial constraints into consideration.
Date of Award2014
Original languageAmerican English
SupervisorIrfan Saadat (Supervisor)


  • Semiconductors; Design and Construction; Semiconductor Industry.

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