a Sherbaf Moghaddam - Industrial Engineering Department, Faculty of Engineering, Shahed University, Tehran, Iran
a Amiri - Industrial Engineering Department, Faculty of Engineering, Shahed University, Tehran, Iran
m Bashiri - Industrial Engineering Department, Faculty of Engineering, Shahed University, Tehran, Iran

Cumulative Count of Conforming (CCC) charts are utilized for monitoring the quality characteristicsin high-quality processes. Executive cost of control charts is a motivation for researchers to designthem with the lowest cost. Usually, in most researches, only one objective named cost function isminimized subject to statistical constraints, which is not effective method for economic-statisticaldesign of control charts. In this paper, a multi-objective model for the economic-statistical design ofthe CCC control chart is developed. Then, multi-objective evolutionary algorithm (NSGA-II) forobtaining the Pareto optimal solution of the model is proposed. A numerical example is applied toillustrate the effectiveness of the proposed model. This model leads to lower cost and smallerprobability of Type I and Type II errors, compared with economic model. In addition, a sensitivityanalysis is done to investigate the effect of input parameters on the best solutions of the proposedmode

Statistical Process ControlCumulative Count of Conforming Charts,High-Quality ProcessesMulti-Objective Economic-Statistical DesignNSGA-II Algorithm