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Time between events control charts for gamma distribution
Author(s) -
Shah Muhammad Taqi,
Azam Muhammad,
Aslam Muhammad,
Sherazi Uzma
Publication year - 2021
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.2763
Subject(s) - control chart , gamma distribution , statistic , computer science , statistical process control , monte carlo method , exponential distribution , data mining , transformation (genetics) , scheme (mathematics) , exponential function , process (computing) , statistics , reliability engineering , engineering , mathematics , mathematical analysis , biochemistry , chemistry , gene , operating system
Modern and emerging techniques of technology have brought a revolution in quality inspection of products. When events in highly efficient production processes occur rarely, it requires to inspect and monitor the time between occurrence of these events (TBE). The exponential and gamma distributions are commonly used models for time between events (TBE) data. In this article, a new monitoring scheme has been established for TBE data based on exponential and gamma distributions. In a previous research, transformation‐based control charts have been developed for TBE. The proposed study is aimed to use the exact probability distribution of charting statistic rather than applying transformations to data and this has remained still unaddressed. Average run length (ARL) and percentage decrease in ARL (ΔARL) have been calculated using Monte Carlo simulations and the proposed monitoring method has been compared with existing techniques applied to transformed data. The proposed scheme provides a simpler design structure and better performance on different sample sizes in identifying annoying process variations. Further, the technique has been applied to simulated and real‐life data sets of time between manufacturing plant accidents to highlight the worth and particle applicability of the proposed work.