Product Design and Inventory Deployment for Improving Delivery Time Performance in the Steel Industry

University Of Minnesota-Twin Cities, Minneapolis MN

Investigators

Abstract

This grant provides funding for the development of mathematical models and numerical tools which can be used to determine the optimal design (dimensions, grade, and weight) of steel slabs, and optimal replenishment policies for slab inventories. A two-step approach will be used. In the first step, optimal design configurations will be determined using a combination of heuristics to generate both a good initial solution and refinements to the initial solution. A stochastic integer programming formulation involving binary variables will be used to provide bounds on the performance of these heuristic solutions. For a given number of slab designs, these methods will determine those configurations that maximize coverage, measured in terms of total finished tons that can be manufactured from the chosen configurations. In the second step, a multi period stochastic linear program will be developed to determine replenishment batch sizes for each slab design configuration in order to minimize the sum of inventory holding and production inefficiency costs. If successful, the results of this research will provide a science-based solution to a chronic problem faced by integrated steel mills (ISMs). By focusing on reducing the number of slab designs, ISMs can pursue specialty steel markets while simultaneously reducing their production process complexity and inventory costs. Solution techniques developed to solve the underlying stochastic optimization problems, will have wider applications to industries with similar process architecture, e.g., paper and pulp, and to other stochastic optimization problems involving a large number of scenarios. The latter occur in a host of applications ranging from energy models, capacity planning to financial asset management. Models proposed for determining optimal replenishment policies, especially when coupled with the possibility of delaying product differentiation, will be useful for manufacturing firms trying to cope with increased product variety.