Volume 33, Issue 1 (IJIEPR 2022)                   IJIEPR 2022, 33(1): 68-85 | Back to browse issues page


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Hakimi A, Farughi H, Amiri A, Arkat J. Phase I Monitoring of Multivariate Ordinal Based Processes: The MR and LRT Approaches (A Real Case Study in Drug Dissolution Process). IJIEPR 2022; 33 (1) :68-85
URL: http://ijiepr.iust.ac.ir/article-1-1245-en.html
1- Department of Industrial Engineering, Faculty of Engineering, University of Kurdistan
2- Department of Industrial Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran , h.farughi@uok.ac.ir
3- Department of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iran
4- Department of Industrial Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran
Abstract:   (1599 Views)
In some statistical processes monitoring (SPM) applications, relationship between two or more ordinal factors is shown by an ordinal contingency table (OCT) and it is described by the ordinal Log-linear model (OLLM). Newton-Raphson algorithm methods have also been used to estimate the parameters of the log-linear model. In this paper, the OLLM based processes is monitored using MR and likelihood ratio test (LRT) approaches in Phase I. Some simulation studies are applied to performance evaluation of the proposed approaches in terms of probability of signal under step shifts, drifts and the presence of outliers. Results show that, by imposing the small and moderate shifts in the ordinal log-linear model parameters, the MR statistic has better performance than LRT. In addition, a real case study in dissolution testing in pharmaceutical industry is employed to show the application of the proposed control charts in Phase I.  
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Type of Study: Research | Subject: Statistical Process Control Statistical Process Control or Quality Control
Received: 2021/04/18 | Accepted: 2022/01/10 | Published: 2022/03/19

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