Title :
A Nonparametric GA-GWMA Sign Chart for Green SCM Optimization
Author :
Shin-Li Lu ; Chen-Fang Tsai
Author_Institution :
Dept. of Ind. Manage. & Enterprise Inf., Aletheia Univ., New Taipei, Taiwan
Abstract :
This study presents a novel design of the nonparametric generally weighted moving average (GWMA) sign chart with dynamic genetic algorithm (GA) optimizer applied in green supply chain management (GSCM) to upgrade customers satisfaction of suppliers´ production stabilities. In recent years, nonparametric control charts hold a significant place among statistical process control charts. Some researchers have developed various nonparametric control charts and investigated the detection capabilities of these charts. The major advantage of these control charts is that the underlying process does not specifically assume normality or any parametric distribution. Simulation studies show that the nonparametric GWMA sign chart is not flexible but can improve the detection capability in small process shifts.
Keywords :
control charts; customer satisfaction; environmental factors; genetic algorithms; statistical process control; supply chain management; GA optimizer; customers satisfaction; dynamic genetic algorithm optimizer; green SCM optimization; green supply chain management; nonparametric GA-GWMA sign chart; nonparametric control charts; nonparametric generally weighted moving average sign chart; statistical process control charts; supplier production stability; Biological cells; Control charts; Monitoring; Optimization; Process control; Quality control; Standards; Detection capability; EWMA sign chart; GWMA sign chart; Nonparametric control chart;
Conference_Titel :
e-Business Engineering (ICEBE), 2013 IEEE 10th International Conference on
Conference_Location :
Coventry
DOI :
10.1109/ICEBE.2013.79