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Monitoring the process mean under the Bayesian approach with application to hard bake process
- Source :
- Scientific Reports, Vol 13, Iss 1, Pp 1-19 (2023)
- Publication Year :
- 2023
- Publisher :
- Nature Portfolio, 2023.
-
Abstract
- Abstract This study introduces the Bayesian adaptive exponentially weighted moving average (AEWMA) control chart within the framework of measurement error, examining two separate loss functions: the squared error loss function and the linex loss function. We conduct an analysis of the posterior and posterior predictive distributions utilizing a conjugate prior. In the presence of measurement error (ME), we employ a linear covariate model to assess the control chart's effectiveness. Additionally, we explore the impacts of measurement error by investigating multiple measurements and a method involving linearly increasing variance. We conduct a Monte Carlo simulation study to assess the control chart's performance under ME, examining its run length profile. Subsequently, we offer a specific numerical instance related to the hard-bake process in semiconductor manufacturing, serving to verify the functionality and practical application of the suggested Bayesian AEWMA control chart when confronted with ME.
Details
- Language :
- English
- ISSN :
- 20452322
- Volume :
- 13
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Scientific Reports
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.0cfbc700b04016b04eb30fbd2ddf6f
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41598-023-48206-1