Sakalli, Umit SamiBirgoren, Burak2020-06-252020-06-252019closedAccess0305-215X1029-0273https://doi.org/10.1080/0305215X.2019.1668933https://hdl.handle.net/20.500.12587/7671Birgoren, Burak/0000-0001-9045-6092A critical process in brass casting is the blending of pure and scrap materials to satisfy specified metal ratios. The primary focus in such blending problems has always been cost minimization. The optimal blends produced by mathematical models use large amounts of scrap materials, which are cheaper but have high variations in ingredient ratios. This gives rise to quality problems. This study aims at joint optimization of cost and quality. A chance-constrained nonlinear mathematical model is developed for maximizing the minimum process capability level for a fixed cost. Then parametric programming is used to run the model for different costs to produce a Pareto-optimal frontier. An application to data from a brass factory showed that the frontier is highly nonlinear, enabling the decision maker to select a competitive process capability and cost value combination. The proposed approach is applicable to any blending problem in which ingredient amounts have statistical variation.eninfo:eu-repo/semantics/closedAccessJoint optimizationstochastic programmingprocess capabilitybrass castingblending problemArticle10.1080/0305215X.2019.16689332-s2.0-85074052823Q1WOS:000488498300001Q2