Title: A case of unconstrained multiple-factor optimisation with unknown function in the textile industry
Authors: Qidong Cao; Thomas E. Griffin; Xiaoming Li
Addresses: College of Business Administration, Winthrop University, 701 Oakland Ave., Rock Hill, SC 29732, USA ' H. Wayne Huzienga School of Business and Entrepreneurship, Nova Southeastern University, 3301 College Ave., Ft. Lauderdale, FL 33314, USA ' Department of Business Administration, Tennessee State University, 330 10th Ave. N, Nashville, TN 37203, USA
Abstract: We applied an extremal experiment in a paper machine clothing factory to solve a quality problem caused by automatic bobbin-changers. The experimental study maximised the breaking strength of weld point and therefore led to a substantial gain in the gross profit. Questions answered in the extremal experiment of this study are useful to other practitioners who can apply the extremal experiment to their industries where an unconstrained multiple-factor optimisation model with unknown functions between the dependent variable and the factors is employed.
Keywords: extremal experiment; sequential experiments; steepest ascent method; parameter optimisation; factorial design.
International Journal of Operational Research, 2019 Vol.34 No.1, pp.54 - 65
Available online: 04 Dec 2018 *Full-text access for editors Access for subscribers Free access Comment on this article