Coordinating Strategic Capacity Planning in the Semiconductor Industry

Abstract

We study strategic capacity planning in the semiconductor industry. Working with a major US semiconductor manufacturer on the configuration of their worldwide production facilities, we identify two unique characteristics of this problem as follows: (1) wafer demands and manufacturing capacity are both main sources of uncertainty, and (2) capacity planning must consider the distinct viewpoints from marketing and manufacturing. We formulate a multi-stage stochastic program with demand and capacity uncertainties. To reconcile the marketing and manufacturing perspectives, we consider a decomposition of the planning problem resembling decentralized decision-making. We develop recourse approximation schemes representing different decentralization schemes, which vary in information requirements and complexity. We show that it is possible to arrive at near optimal solutions (within 6.5%) with information decentralization while using a fraction (16.2%) of the computer time.