An intelligent GA-nonparametric DEWMA sign chart for green chain management

Kuo-Ming Chao, C-F. Tsai, S-L. Lu

    Research output: Chapter in Book/Report/Conference proceedingChapter

    3 Citations (Scopus)

    Abstract

    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.
    Original languageEnglish
    Title of host publicationProceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2014
    EditorsJ-L. Hou, A.J.C. Trappey, C-W. Wu, K-H. Chang, C-S. Liao, W-M. Shen, J-P. Barthès, J-Z. Luo
    PublisherIEEE
    Pages247-252
    ISBN (Print)9781479937769
    DOIs
    Publication statusPublished - 2014

    Bibliographical note

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    Keywords

    • detection ability
    • DEWMA sign chart
    • EWMA sign chart
    • green chain optimization
    • nonparametric control chart

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