Title: Achieving cost robustness in processes with mixed multiple quality characteristics and dynamic variability
Authors: Gregory L. Boylan; Paul L. Goethals
Addresses: Department of Industrial Engineering, Clemson University, Clemson, SC 29634, USA. ' Department of Mathematical Sciences, US Military Academy, West Point, NY 10997, USA
Abstract: The tenuous economic conditions of the past several years continue to threaten the economic existence of many companies, forcing them to re-examine ways for reducing costs without surrendering quality. A common technique for achieving high quality at minimal cost focuses on identifying the ideal process mean setting among various quality characteristics. In the design of this approach, referred to as the |optimal process mean problem|, comparatively little research has addressed the realities of mixed multiple quality characteristics and the dynamic nature of process variability. To address this gap, this paper examines situations involving mixed multiple quality characteristics, proposing a methodology to accurately predict the location of the optimal process mean vector as it shifts in response to changing process variability. This knowledge of a feasible region for the optimal vector can help to achieve robustness in cost by providing a mechanism for maintaining the most profitable process target settings.
Keywords: optimal process mean vector; mixed multiple quality characteristics; process robustness; cost robustness; multivariate skew normal distribution; dynamic variability.
International Journal of Experimental Design and Process Optimisation, 2011 Vol.2 No.3, pp.243 - 264
Available online: 24 Sep 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article