Robust models for manufacturing capacity planning under demand uncertainty

Abstract

The objective of this work is to develop mathematical models and tools to aid decision makers in devising capacity plans for a manufacturing network in face of uncertainty in future demand. A manufacturing network is constituted by a set of plants serving a set of markets with a set of products. It is specified in terms of a product portfolio for each market and a product portfolio, resource capacities and a set of markets to serve, for each plant. Based on this definition, we address the following question: Given a manufacturing network, determine when to change the manufacturing capacity, where to change it and by how much to change it. Our approach is to devise a plan that is robust with respect to certain perturbations in demand forecasts, rather than one that is optimal with respect to the inherent uncertainty in demand. Thus the idea we follow is to superimpose perturbations on demand forecasts used by decision-makers, and devise a plan that can withstand those variations. Representing manufacturing capacity through the notion of operating configurations, we formulate dynamic optimization models to address the problem.