Title: Monitoring of Poisson multi-stage process in Phase II with Bayesian estimation of parameters

Authors: Fatemeh Sogandi; Fatemeh Ebrahimi

Addresses: Industrial Engineering Department, Faculty of Engineering, University of Torbat Heydarieh, Torbat Heydarieh, Iran ' Industrial Engineering Department, Faculty of Engineering, University of Torbat Heydarieh, Torbat Heydarieh, Iran

Abstract: In monitoring multi-stage processes, control charts are crucial tools that should consider both inter-stage and intra-stage links. However, most researchers have only focused on the cascade property, while there are many real-world applications with Poisson-distributed random variables. This paper proposes a Phase II monitoring scheme based on a Poisson state-space model that considers non-measurable or invisible process variables as latent variables for multi-stage processes. The Bayesian algorithm is used to estimate the parameters of the proposed model. Simulation results show that the proposed GEWMA control chart performs well in single and multiple stages, with various changes in the parameters, and helps to identify the out-of-control stage too.

Keywords: Poisson distribution; Bayesian approach; control chart; multi-stage processes; diagnosing method.

DOI: 10.1504/IJQET.2024.140145

International Journal of Quality Engineering and Technology, 2024 Vol.10 No.1, pp.86 - 98

Received: 27 May 2023
Accepted: 14 Feb 2024
Published online: 25 Jul 2024 *

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