Open AccessOne-sided 4-out-of-5 Run Rules Charts for the Multivariate Coefficient of Variation in the Finite Horizon Process
Author(s) -
Khai Wah Khaw,
XinYing Chew,
Ming Ha Lee,
Wai Chung Yeong,
Sajal Saha
Publication year - 2021
Publication title -
wseas transactions on mathematics
Language(s) - English
Resource type - Journals
eISSN - 2224-2880
pISSN - 1109-2769
DOI - 10.37394/23206.2021.20.47
Subject(s) - process (computing) , horizon , computer science , process variation , markov chain , multivariate statistics , variation (astronomy) , industrial engineering , algorithm , statistics , mathematics , engineering , machine learning , physics , geometry , astrophysics , operating system
Quality improvement has been receiving great attention in industries. In recent years, the finite horizon process is commonly encountered in industries due to flexible manufacturing production. Past research works on finite horizon process monitoring are still limited. Because of this, one-sided 4-out-of-5 run rules charts are proposed to monitor the multivariate coefficient of variation in a finite horizon process. The performance measures of the proposed charts are derived using the Markov-chain approach. The proposed schemes can serve as a framework for practitioners who wish to perform process monitoring easily and efficiently. Numerical comparisons between the proposed and existing charts have been made, in terms of the truncated average run length and the expected truncated average run length criteria. The findings reveal that the proposed charts outperform the existing charts for detecting small and moderate process shifts in the finite horizon process.