In green management, the quality control performs a key factor for chain materials and products in chain productions. Selecting the correct control chart is essential to effectively monitoring process shifts. In particularly, a nonparametric control chart is recommended over a traditional control chart when the quality characteristics of a process are unknown. This paper designs an intelligent genetic algorithm (GA)-nonparametric EWMA sign chart for green chain management by an adaptive GA controller to upgrade green chains satisfactions. In this paper, we extend the nonparametric exponentially weighted moving average (EWMA) sign chart to a double EWMA (DEWMA) sign chart to improve the detection ability in small green process shifts. Simulation studies show that the nonparametric DEWMA sign chart performs better than the EWMA sign chart in detecting small process shifts, but that they perform similarly when detecting large shifts.
|Title of host publication||Proceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2014|
|Editors||J-L. Hou, A.J.C. Trappey, C-W. Wu, K-H. Chang, C-S. Liao, W-M. Shen, J-P. Barthès, J-Z. Luo|
|Publication status||Published - 2014|
Bibliographical noteThe full text of this item is not available from the repository.
© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
- detection ability
- DEWMA sign chart
- EWMA sign chart
- green chain optimization
- nonparametric control chart