Monitoring process variability: a hybrid Taguchi loss and multiobjective genetic algorithm approach

Document Type: Original Manuscript

Authors

1 University of Melbourne

2 Babol University of Technology

Abstract

The common consideration on economic model is that there is knowledge about the risk of occurrence of an assignable cause and the various cost parameters that does not always adequately describe what happens in practice. Hence, there is a need for more realistic assumptions to be incorporated. In order to reduce cost penalties for not knowing the true values of some parameters, this paper aims to develop a bi-objective model of the economic-statistical design of the S control chart to minimize the mean hourly loss cost while minimizing out-of-control average run length and maintaining reasonable in-control average run length considering Taguchi loss function. The purpose of Taguchi loss function is to reflect the economic loss associated with variation in, and deviations from, the process target or the target value of a product characteristic. In contrast to the existing modeling approaches, the proposed model and given Pareto-optimal solution sets enables the chart designer to obtain solutions that is effective even for control chart design problems in uncertain environments. A comparison study with a traditional economic design model reveals that the proposed chart presents a better approach for quality system costs and the power of control chart in detecting the assignable cause.

Highlights

  • A bi-objective model of the economic-statistical design of S control chart is developed.The proposed model gives
  • Pareto-optimal solutions which are effective in uncertain environments.
  • The proposed chart gives better approach for quality system costs and power of control chart in detecting the assignable cause.

Keywords

Main Subjects