Semiconductor: Demand Planning and Supply Chain Coordination in the Contract Manufacturing Environments

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This grant supports the development of new analytical tools for semiconductor demand planning and supply chain coordination, focusing on the emerging platform of contract manufacturing. The objectives of the research are to (1) develop mathematical models that characterize demand drivers for products with short technology lifecycles, (2) create economic models that characterize incentives in contract manufacturing environments, (3) construct computing models that translate theoretical insights into operational decision tools, and (4) conduct extensive industry testing that validates the analytical developments. A main motivation of this research is that current demand and capacity management practices in the semiconductor industry were developed in the context of vertically integrated enterprises with long technology lifecycles and stable demand patterns. While the industry is moving toward increasingly complex supply chain partnerships, accelerated technology innovations, and rapid product introduction cycles, the operational implications of these changes are not well understood. This research offers innovative models that enhance our understanding of this dynamically changing environment. If successful, this research will make contributions from two important perspectives: 1. Effective Characterization of Demands with Shortening Technology Lifecycles. The shortened technological lifecycle poses major challenges to the time-series forecasting methods fundamental to all demand planning systems. This research examines demand characterization methods based on leading indicators and lifecycle growth models without relying on the sizable historical data required by time-series models. 2. Effective Supply-Demand Planning Within Complex Supply Chain Partnerships. Major corporations are moving away from vertical integration, while their product realization is being carried out through a supply chain structure built on outsourcing and partnerships. This research proposes a supply-demand planning framework designed for the emerging platform of contract manufacturing; in this setting, the uncertainty in both demand and capacity that is prevalent is modeled explicitly, while supply-demand planning decisions are integrated with contracting, sourcing, and capacity configuration decisions.