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Ghasemi Eshkaftaki, Zohre, Zeinal Hamadani, Ali, Ahmadi Yazdi, Ahmad. (1400). Evaluating Parameter Estimation Effect on the Polynomial Profile Monitoring Methods’ Phase II Performance. , 55(2), 133-150. doi: 10.22059/jieng.2021.326559.1785
Zohre Ghasemi Eshkaftaki; Ali Zeinal Hamadani; Ahmad Ahmadi Yazdi. "Evaluating Parameter Estimation Effect on the Polynomial Profile Monitoring Methods’ Phase II Performance". , 55, 2, 1400, 133-150. doi: 10.22059/jieng.2021.326559.1785
Ghasemi Eshkaftaki, Zohre, Zeinal Hamadani, Ali, Ahmadi Yazdi, Ahmad. (1400). 'Evaluating Parameter Estimation Effect on the Polynomial Profile Monitoring Methods’ Phase II Performance', , 55(2), pp. 133-150. doi: 10.22059/jieng.2021.326559.1785
Ghasemi Eshkaftaki, Zohre, Zeinal Hamadani, Ali, Ahmadi Yazdi, Ahmad. Evaluating Parameter Estimation Effect on the Polynomial Profile Monitoring Methods’ Phase II Performance. , 1400; 55(2): 133-150. doi: 10.22059/jieng.2021.326559.1785

Evaluating Parameter Estimation Effect on the Polynomial Profile Monitoring Methods’ Phase II Performance

Advances in Industrial Engineering
دوره 55، شماره 2، تیر 2021، صفحه 133-150    اصل مقاله (756.64 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/jieng.2021.326559.1785
نویسندگان
Zohre Ghasemi Eshkaftaki1؛ Ali Zeinal Hamadani1؛ Ahmad Ahmadi Yazdi* 2
1Department of Industrial and Systems Engineering, Isfahan University of Technology, Isfahan, Iran.
2Department of Industrial Engineering, Yazd University, Yazd, Iran
چکیده
In some statistical process monitoring applications, the quality of a product or process can be determined by a linear or nonlinear regression relationship called "profile". Basically, standard monitoring methods involve two phases: Phase I and Phase II. Usually, it is assumed that the process parameters are known, however this condition in many applications is not met and parameters are estimated using the in-control data set collected in Phase I. The present study evaluates and compares some Phase II control chart approaches for monitoring the second order polynomial profiles when the process parameters are estimated. These methods includes Orthogonal, MEWMA and dEWMA-OR control charts. The performance of each control chart is measured in terms of ARL, SDRL, AARL and SDARL metrics using Monte Carlo simulation approach. The results showed that the in-control and out-of-control performance of control charts is strongly affected by parameter estimation, especially when only a few Phase I samples are used to estimate the parameters. Moreover, the superior overall performance of the Orthogonal method rather than the other competing methods is shown. Furthermore, we concluded that F estimation method leads to better performance of control charts in Phase II.
کلیدواژه‌ها
Profile Monitoring؛ Polynomial Profile؛ Estimation Effect؛ Control Chart؛ Run Length؛ Statistical Process Control
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