Abstract
Integrated Steel Manufacturers (ISMs) perform all of the steps necessary to convert iron ore into finished products. As a result they are characterized by high capital expenditures and long cycle times. The custom nature of finished products and significant demand uncertainty explains why ISMs typically produce to order. However, recent increased competition from low cost mini-mills is causing some ISMs to compete by serving the needs of higher-paying customers who want exotic products, and faster and reliable deliveries. Consequently, ISMs are exploring the option of satisfying a portion of their demand by converting strategically placed semi-finished inventory into finished products, which helps to reduce both the time between order receipt and order dispatch, and its variability. In this study we propose a two-stage stochastic integer programming model that can be used to choose the semi-finished products that should be made to stock, and their target inventory levels. Properties of this model are exploited to develop a fast heuristic applicable to large-scale instances of the problem encountered in industry. Numerical experiments are used to validate the heuristic, and examples based on data from a particular ISM are used to illustrate important managerial insights.
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