Geometric charts with bootstrap-based control limits using the Bayes estimator
- Authors
- 김민지; 이재헌
- Issue Date
- Jan-2020
- Publisher
- 한국통계학회
- Keywords
- Bayes estimator; bootstrap algorithm; control limits; geometric chart; statistical process control
- Citation
- Communications for Statistical Applications and Methods, v.27, no.1, pp 65 - 77
- Pages
- 13
- Journal Title
- Communications for Statistical Applications and Methods
- Volume
- 27
- Number
- 1
- Start Page
- 65
- End Page
- 77
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/37685
- DOI
- 10.29220/CSAM.2020.27.1.065
- ISSN
- 2287-7843
2383-4757
- Abstract
- Geometric charts are effective in monitoring the fraction nonconforming in high-quality processes. The in-control fraction nonconforming is unknown in most actual processes; therefore, it should be estimated using the Phase I sample. However, if the Phase I sample size is small the practitioner may not achieve the desired in-control performance because estimation errors can occur when the parameters are estimated. Therefore, in this paper, we adjust the control limits of geometric charts with the bootstrap algorithm to improve the in-control performance of charts with smaller sample sizes. The simulation results show that the adjustment with the bootstrap algorithm improves the in-control performance of geometric charts by controlling the probability that the in-control average run length has a value greater than the desired one. The out-of-control performance of geometric charts with adjusted limits is also discussed.
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Collections - College of Business & Economics > Department of Applied Statistics > 1. Journal Articles
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