Abstract
Revolution in manufacturing and service industries brings a considerable change in the quality of the products and services. Most systems produce near-zero defects; therefore, data related to defects has many zeros. For estimation, the traditional Poisson model cannot deal with the excess number of zeros. Hence, a possible alternative solution is to use the zero-inflated Poisson model. From a quality control perspective, many control charts monitor zero-inflated Poisson processes. However, very few have considered covariates along with the zero-inflated Poisson variable in monitoring and termed model-based monitoring. This study is designed to propose the model-based Homogenous Weighted Moving Average (HWMA) and Double Homogenous Weighted Moving Average (DHWMA) control charts based on the Pearson residuals of ZIP models. In addition, a simulation-based comparative study is designed where findings are reported using run-length metrics. The findings revealed that the PR-DHWMA chart performs relatively better than the PR-HWMA chart.
Original language | English |
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Title of host publication | 2022 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) |
Publisher | IEEE |
Pages | 0482-0486 |
Number of pages | 5 |
DOIs | |
Publication status | Published - 26 Dec 2022 |
Externally published | Yes |
Keywords
- control chart
- model-based monitoring
- Pearson residuals
- statistical process control
- zero-inflated Poisson