Koksoy, Onur2019-08-012019-08-0120080096-3003https://dx.doi.org/10.1016/j.amc.2007.06.023https://hdl.handle.net/11480/5266Quite often, engineers obtain measurements associated with several response variables. Both the design and analysis of multi-response experiments with a focus on quality control and improvement have received little attention although they are sorely needed. In a multi-response case the optimization problem is more complex than in the single-response situation. In this paper we present a method to optimize multiple quality characteristics based on the mean square error (MSE) criterion when the data are collected from a combined array. The proposed method will generate more alternative solutions. The string of solutions and the trade-offs aid in determining the underlying mechanism of a system or process. The procedure is illustrated with an example, using the generalized reduced gradient (GRG) algorithm for nonlinear programming. (C) 2007 Elsevier Inc. All rights reserved.eninfo:eu-repo/semantics/closedAccessmulti-response process optimizationmean square errorrobust parameter designresponse surface methodologynonlinear programmingArticle196260361210.1016/j.amc.2007.06.0232-s2.0-38649135776Q1WOS:000253631700013Q2