• Title of article

    Phase II Monitoring of the Ordinal Multivariate Categorical Processes

  • Author/Authors

    Hakimi, Ahmad Department of Industrial Engineering - Faculty of Engineering - University of Kurdistan - Sanandaj, Iran , Farughi, Hiwa Department of Industrial Engineering - Faculty of Engineering - University of Kurdistan - Sanandaj, Iran , Amiri, Amirhossein Department of Industrial Engineering - Faculty of Engineering - Shahed University - Tehran, Iran , Arkat, Jamal Department of Industrial Engineering - Faculty of Engineering - University of Kurdistan - Sanandaj, Iran

  • Pages
    19
  • From page
    249
  • To page
    267
  • Abstract
    Statistical variables are divided into two categories: nominal and ordinal, both of which have many uses. In some statistical process monitoring applications, the quality of a process or product is described by multiple ordinal quality characteristics, which is called ordinal multivariate process. An ordinal contingency table is used to show the relationships between these variables and is modeled on an ordinal log-linear model. In our manuscript, two new statistics including simple ordinal categorical and Generalized-p are developed for Phase II monitoring the ordinal log-linear model-based processes. The performance of the proposed statistics will be evaluated using some simulation studies and real-world numerical examples. The results show the advantages of a simple ordinal category control card. In addition, the performance of these statistics is accessed through sensitivity analysis of the row and column sizes of the contingency table. Meanwhile, a sensitivity analysis with three and four categorical factors is performed and similar results are obtained.
  • Keywords
    Multivariate Processes , Statistical Process Monitoring , Ordinal Variables , Phase II , Contingency Table
  • Journal title
    Advances in Industrial Engineering
  • Serial Year
    2021
  • Record number

    2658684