Coordinated capacity migration and expansion planning for semiconductor manufacturing under demand uncertainties

Abstract

Semiconductor industry is very capital intensive in which capacity utilization significantly affect the capital effectiveness and profitability of semiconductor manufacturing companies. Due to constant technology advance driven by Moore's Law in semiconductor industry, multiple production technologies generally co-exist in a wafer fabrication facility with utilization of a pool of common tools for multiple technologies and critical tools dedicated for a specific technology. Because part of the equipment is common for products of different technologies, production managers have limited flexibility to dynamically allocate the capacity among the technologies via capacity migration. The possibility of capacity migration and interrelationship among different technologies make capacity planning difficult under demand and product-mix uncertainties. This paper aims to develop a dynamic optimization method that captures the unique characteristics of rolling demand forecast mechanism to solve capacity expansion and migration planning problems in semiconductor industry. In semiconductor industry, demand forecasts are rolling and updated when the latest market and demand information is available. This demand forecast mechanism makes forecast errors in different time periods correlated. We estimate the validity and robustness of the proposed dynamic optimization method in an empirical study in a semiconductor manufacturing company in Taiwan. The results showed practical viability of this approach and the findings can provide useful guidelines for capacity planning process under rolling forecast mechanism.