Optimal robust and tolerance design for computer experiments with mixture proportion inputs

Computer experiments often have inputs that are proportions/fractions of components in a mixture. In these mixture computer experiments, it can be of interest to perform robust and tolerance design on the mixture proportions since the proportions are subjected to noise variations. Traditionally, manufacturing of mixture products is controlled via interval tolerances for mixture amounts. In this paper, an optimal tolerance region for proportions, which gives optimal quality cost among all possible tolerance regions for mixture proportions with the same acceptance probability, is proposed for integrated parameter and tolerance design (IPTD) in mixture computer experiments. Real examples are given to demonstrate the improvements that can be achieved with the optimal tolerance region. About the Speaker Mei Han is a Ph.D. candidate in the Department of Systems Engineering and Engineering Management, City University of Hong Kong. She received her B.Eng. degree (2014) in Automation from Huazhong University of Science and Technology. Her research focuses on statistical quality control and improvement. Enquiry: 3442 8408 All are Welcome! SEEM Seminar 2017-2018/003