DocumentCode
655322
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
fYear
2013
fDate
11-13 Sept. 2013
Firstpage
504
Lastpage
508
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;
fLanguage
English
Publisher
ieee
Conference_Titel
e-Business Engineering (ICEBE), 2013 IEEE 10th International Conference on
Conference_Location
Coventry
Type
conf
DOI
10.1109/ICEBE.2013.79
Filename
6686312
Link To Document