Integration of production quantity and control chart design in automotive manufacturing

Abstract

We formulate the problem as a two-stage stochastic programming model. In the first stage, control limit parameter k is decided for the p-chart and in the second stage, production quantity is determined that minimizes total quality-related and production costs. We solve the model by sample average approximation algorithm (SAA). In a numerical study, we investigate the effect of various factors on control limit parameter k and the total cost. Our numerical study shows that (i) an increase on the mean defect rate increases both the total cost and the total production quantity, (ii) effect of an increasing process variance to the control limit parameter k is significantly small, (iii) frequency of special cause occurrences affects the total cost significantly and (iv) all the experiments show that the commonly used 3 control limits in practice are wider than required. (C) 2016 Elsevier Ltd. All rights reserved.