MODELING METHODS FOR MANAGING RAW MATERIAL COMPOSITIONAL UNCERTAINTY IN ALLOY PRODUCTION

摘要

Operational uncertainties create inefficiencies in metal alloy production. One that greatly influences remelter batch optimization is variation in raw material composition, particularly for secondary materials. Currently, to accommodate compositional variation, firms commonly set production targets well inside of the window of compositional specification required for performance reasons. Window narrowing, while effective, does not make use of statistical sampling data, leading to sub-optimal usage of secondary materials. This paper explores the use of a chance constrained optimization method, which allows explicit consideration of statistical information on composition. The framework and a case study of cast and wrought production with available scrap materials are presented. Results show that it is possible to increase scrap consumption without compromising the likelihood of batch errors, when using this method compared to conventional window narrowing.