Robust Phase I monitoring of Poisson Regression Profiles in Multistage Processes | ||
Journal of Quality Engineering and Production Optimization | ||
مقاله 11، دوره 8، شماره 1، مرداد 2023، صفحه 197-216 اصل مقاله (755.32 K) | ||
نوع مقاله: CFP- Quality Engineering Techniques in Production and Service Systems | ||
شناسه دیجیتال (DOI): 10.22070/jqepo.2023.17865.1264 | ||
نویسنده | ||
fatemeh sogandi* | ||
Department of Industrial Engineering, Faculty of Engineering, University of Torbat Heydrieh, Mashhad, Iran | ||
چکیده | ||
The challenge of monitoring and controlling processes where the response variable follows a Poisson distribution, rather than a normal distribution, is addressed in this paper. The significant impact of outliers on model estimators, which subsequently affects the performance of control charts, is also highlighted. To overcome these challenges, the use of robust estimators for monitoring profiles and enhancing control chart efficiency is proposed. Furthermore, as industries increasingly adopt multistage processes in manufacturing instead of a single stage, monitoring these processes becomes essential. Therefore, two robust control charts, namely the and control charts, designed for Poisson regression profiles in multistage processes, are proposed. The efficiency of the proposed control chart is assessed using the signal probability criterion and its performance is compared to that of a classic control chart in Phase I. Extensive simulation studies are conducted to appraise the performance of these monitoring schemes under different shifts and stages, considering contamination scenarios as well. Based on the simulation results, it is found that the control chart using robust estimators provides better performance compared to the classic control chart, demonstrating the effectiveness of the proposed method. Additionally, a real example is presented to further evaluate the performance of this approach. | ||
کلیدواژهها | ||
Poisson regression profiles؛ Multistage processes؛ Phase I؛ Robust control chart | ||
مراجع | ||
Abbasi, S. A., Yeganeh, A., & Shongwe, S. C. (2022). Monitoring non-parametric profiles using adaptive EWMA control chart. Scientific Reports, 12(1), 14336.
Ahmadi Karavigh, M. H., & Amiri, A. (2022). MEWMA based control charts with runs rules for monitoring multivariate simple linear regression profiles in Phase II. Communications in Statistics-Simulation and Computation, 1-28.
Ahmadi, O., Shahriari, H., & Samimi, Y. (2018). A robust wavelet based profile monitoring and change point detection using S-estimator and clustering. Journal of Industrial and Systems Engineering, 11(3), 167-189.
Amiri, A., Koosha, M., & Azhdari, A. (2011, December). Profile monitoring for Poisson responses. In 2011 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1481-1484). IEEE.
Amiri, A., Koosha, M., Azhdari, A., & Wang, G. (2015). Phase I monitoring of generalized linear model-based regression profiles. Journal of Statistical Computation and Simulation, 85(14), 2839-2859.
Amiri, A., Sogandi, F., & Ayoubi, M. (2018). Simultaneous monitoring of correlated multivariate linear and GLM regression profiles in Phase II. Quality Technology & Quantitative Management, 15(4), 435-458.
Asadzadeh, S., & Aghaie, A. (2009). Cause-selecting control charts based on Huber’s M-estimator. The International Journal of Advanced Manufacturing Technology, 45(3-4), 341-351.
Asadzadeh, S., AGHAEI, A., & Yang, S. F. (2008). Monitoring and diagnosing multistage processes: a review of cause selecting control charts.
Bahrami, H., Niaki, S. T. A., & Khedmati, M. (2021). Monitoring multivariate profiles in multistage processes. Communications in Statistics-Simulation and Computation, 50(11), 3436-3464.
Cantoni, E., & Ronchetti, E., (2001) Robust inference for generalized linear models. Journal of the American Statistical Association, 96(455),1022-1030.
Chang, Y. C., & Chen, C. M. (2020). A Kullback‐Leibler information control chart for linear profiles monitoring. Quality and Reliability Engineering International, 36(7), 2225-2248.
Cheema, M., Amin, M., Mahmood, T., Faisal, M., Brahim, K., & Elhassanein, A. (2023). Deviance and Pearson Residuals-Based Control Charts with Different Link Functions for Monitoring Logistic Regression Profiles: An Application to COVID-19 Data. Mathematics, 11(5), 1113.
Derakhshani, R., Esmaeeli, H., & Amiri, A. (2020). Phase II Monitoring of Poisson Regression Profiles in Multi-Stage Processes. International Journal of Reliability, Quality and Safety Engineering, 27(04), 2050012.
Derakhshani, R., Esmaeeli, H., & Amiri, A. (2021). Monitoring binary response profiles in multistage processes. Journal of Quality Engineering and Production Optimization, 6(2), 97-114.
Ding, N., He, Z., He, S., & Song, L. (2023). Real-time profile monitoring schemes considering covariates using Gaussian process via sensor data. Quality Technology & Quantitative Management, 1-19.
Ebadi, M., & Shahriari, H. (2014). Robust estimation of parameters in simple linear profiles using M-estimators. Communications in Statistics-Theory and Methods, 43(20), 4308-4323.
Fallahdizcheh, A., & Wang, C. (2022). Profile monitoring based on transfer learning of multiple profiles with incomplete samples. IISE transactions, 54(7), 643-658.
Ghashghaei, R., & Amiri, A. (2017). Sum of squares control charts for monitoring of multivariate multiple linear regression profiles in phase II. Quality and Reliability Engineering International, 33(4), 767-784.
Ghashghaei, R., Amiri, A., & Khosravi, P. (2019). New control charts for simultaneous monitoring of the mean vector and covariance matrix of multivariate multiple linear profiles. Communications in Statistics-Simulation and Computation, 48(5), 1382-1405.
Hakimi, A., Amiri, A., & Kamranrad, R. (2017). Robust approaches for monitoring logistic regression profiles under outliers. International Journal of Quality & Reliability Management.
Haq, A. (2022). Adaptive MEWMA charts for univariate and multivariate simple linear profiles. Communications in Statistics-Theory and Methods, 51(16), 5383-5411.
Haq, A., Bibi, M., & Shah, B. A. (2022). A novel approach to monitor simple linear profiles using individual observations. Communications in Statistics-Simulation and Computation, 51(11), 6269-6282.
Hassanvand, F., Samimi, Y., & Shahriari, H. (2019). A robust control chart for simple linear profiles in two‐stage processes. Quality and Reliability Engineering International, 35(8), 2749-2773.
Hauck, D. J., Runger, G. C., & Montgomery, D. C. (1999). Multivariate statistical process monitoring and diagnosis with grouped regression‐adjusted variables. Communications in Statistics-Simulation and Computation, 28(2), 309-328.
He, K., Zhang, Q., & Hong, Y. (2019). Profile monitoring based quality control method for fused deposition modeling process. Journal of Intelligent Manufacturing, 30, 947-958.
Huber, P. J., & Ronchetti, E. M. (2012) Robust Statistics. Hoboken: John Wiley & Sons.
Jearkpaporn, D., Borror, C. M., Runger, G. C., & Montgomery, D. C. (2007). Process monitoring for mean shifts for multiple stage processes. International Journal of Production Research, 45(23), 5547-5570.
Jones, C. L., Abdel‐Salam, A. S. G., & Mays, D. A. (2021). Practitioners guide on parametric, nonparametric, and semiparametric profile monitoring. Quality and Reliability Engineering International, 37(3), 857-881.
Kamranrad, R., & Amiri, A. (2016). Robust Holt-Winter based control chart for monitoring autocorrelated simple linear profiles with contaminated data. Scientia Iranica, 23(3), 1345-1354.
Kang, L. & Albin, S.L., (2000). Online monitoring when the process yields a linear profile, Journal of Quality Technology, 32(4), 418-426.
Khalili, S., & Noorossana, R. (2022). Online monitoring of autocorrelated multivariate linear profiles via multivariate mixed models. Quality Technology & Quantitative Management, 19(3), 319-340.
Khedmati, M., & Niaki, S. T. A. (2016). Phase II monitoring of general linear profiles in the presence of between‐profile autocorrelation. Quality and Reliability Engineering International, 32(2), 443-452.
Khedmati, M., & Niaki, S. T. A. (2016a). A new control scheme for phase‐ii monitoring of simple linear profiles in multistage processes. Quality and Reliability Engineering International, 32(7), 2559-2571.
Khedmati, M., & Niaki, S. T. A. (2016b). Monitoring simple linear profiles in multistage processes by a MaxEWMA control chart. Computers & Industrial Engineering, 98, 125-143.
Khedmati, M., & Niaki, S. T. A. (2017). Phase-I monitoring of general linear profiles in multistage processes. Communications in Statistics-Simulation and Computation, 46(6), 4465-4489.
Khedmati, M., & Niaki, S. T. A. (2022). Phase-I robust parameter estimation of simple linear profiles in multistage processes. Communications in Statistics-Simulation and Computation, 51(2), 460-485.
Koosha, M., & Amiri, A. (2013). Generalized linear mixed model for monitoring autocorrelated logistic regression profiles. The International Journal of Advanced Manufacturing Technology, 64, 487-495.
Kordestani, M., Hassanvand, F., Samimi, Y., & Shahriari, H. (2020). Monitoring multivariate simple linear profiles using robust estimators. Communications in Statistics-Theory and Methods, 49(12), 2964-2989.
Li, C. I., & Tsai, M. R. (2023). Control charts for profile monitoring of within-profile correlations using the Tweedie exponential dispersion process model. Journal of Statistical Computation and Simulation, 93(4), 513-532.
Maleki, M. R., Amiri, A., & Castagliola, P. (2018). An overview on recent profile monitoring papers (2008–2018) based on conceptual classification scheme. Computers & Industrial Engineering, 126, 705-728.
Maleki, M. R., Amiri, A., & Taheriyoun, A. R. (2017). Phase II monitoring of binary profiles in the presence of within-profile autocorrelation based on Markov Model. Communications in Statistics-Simulation and Computation, 46(10), 7710-7732.
Maleki, M. R., Salmasnia, A., Maboudou-Tchao, E. M., & Khanbeygi, P. (2022). Phase II monitoring of logistic regression profiles with estimated parameters. Journal of Statistical Computation and Simulation, 92(13), 2721-2739.
Mammadova, U., & Özkale, M. R. (2021). Profile monitoring for count data using Poisson and Conway–Maxwell–Poisson regression-based control charts under multicollinearity problem. Journal of Computational and Applied Mathematics, 388, 113275.
Mammadova, U., & Özkale, M. R. (2023). Comparison of deviance and ridge deviance residual-based control charts for monitoring Poisson regression profiles. Communications in Statistics-Simulation and Computation, 52(3), 826-853.
Mohammadzadeh, M., Yeganeh, A., & Shadman, A. (2021). Monitoring logistic profiles using variable sample interval approach. Computers & Industrial Engineering, 158, 107438.
Moheghi, H. R., Noorossana, R., & Ahmadi, O. (2021). GLM profile monitoring using robust estimators. Quality and Reliability Engineering International, 37(2), 664-680.
Nasiri Boroujeni, M., Samimi, Y., & Roghanian, E. (2022). Parametric and non-parametric methods for monitoring nonlinear fuzzy profiles. The International Journal of Advanced Manufacturing Technology, 118(1-2), 67-8.
Nassar, S. H., & Abdel‐Salam, A. S. G. (2021). Semiparametric MEWMA for Phase II profile monitoring. Quality and Reliability Engineering International, 37(5), 1832-1846.
Nie, B., Liu, D., Liu, X., & Ye, W. (2021). Phase I non-linear profiles monitoring using a modified Hausdorff distance algorithm and clustering analysis. International Journal of Quality & Reliability Management, 38(2), 536-550.
Piri, S., Abdel-Salam, A. S. G., & Boone, E. L. (2021). A wavelet approach for profile monitoring of Poisson distribution with application. Communications in Statistics-Simulation and Computation, 50(2), 525-536.
Prabhu, S. S. & Runger, G. C., (1997), Designing a multivariate EWMA control chart, Journal of Quality Technology, 29(1), 8-15.
Qi, D., Wang, Z., Zi, X., & Li, Z. (2016). Phase II monitoring of generalized linear profiles using weighted likelihood ratio charts. Computers & Industrial Engineering, 94, 178-187.
Sabahno, H., & Amiri, A. (2023). Simultaneous monitoring of the mean vector and covariance matrix of multivariate multiple linear profiles with a new adaptive Shewhart-type control chart. Quality Engineering, 1-19.
Saeed, U., Mahmood, T., Riaz, M., & Abbas, N. (2018). Simultaneous monitoring of linear profile parameters under progressive setup. Computers & Industrial Engineering, 125(1), 434-450.
Salam, A. S. G. A. (2022, January). Phase II Profile Monitoring via Robust Semi-Parametric MCUSUM. In Online International Symposium on Applied Mathematics and Engineering (ISAME22) January 21-23, 2022 Istanbul-Turkey (p. 98).
Shadman, A., Mahlooji, H., Yeh, A. B., & Zou, C. (2015). A change point method for monitoring generalized linear profiles in Phase I. Quality and Reliability Engineering International, 31(8), 1367-1381.12.
Shahriari, H., & Ahmadi, O. (2017). Robust estimation of complicated profiles using wavelets. Communications in Statistics-Theory and Methods, 46(4), 1573-1593.
Shahriari, H., Ahmadi, O., & Samimi, Y. (2016). Estimation of complicated profiles in Phase I, clustering and S‐estimation approaches. Quality and Reliability Engineering International, 32(7), 2455-2469.
Sogandi, F., & Amiri, A. (2017). Monotonic change point estimation of generalized linear model-based regression profiles. Communications in Statistics-Simulation and Computation, 46(3), 2207-2227.
Sogandi, F., Aminnayeri, M., Mohammadpour, A., & Amiri, A. (2019). Risk-adjusted Bernoulli chart in multi-stage healthcare processes based on state-space model with a latent risk variable and dynamic probability control limits. Computers & Industrial Engineering, 130, 699-713.
Sogandi, F., Aminnayeri, M., Mohammadpour, A., & Amiri, A. (2021). Phase I risk-adjusted Bernoulli chart in multistage healthcare processes based on the state-space model. Journal of Statistical Computation and Simulation, 91(3), 522-542.
Tsung, F., Li, Y., & Jin, M. (2008). Statistical process control for multistage manufacturing and service operations: a review and some extensions. International Journal of Services Operations and Informatics, 3(2), 191-204.
Woodall, W.H. (2007). Current research on profile monitoring. Production, 17(3), 420-425.
Yao, C., Li, Z., He, C., & Zhang, J. (2020). A Phase II control chart based on the weighted likelihood ratio test for monitoring polynomial profiles. Journal of Statistical Computation and Simulation, 90(4), 676-698.
Yeganeh, A., & Shadman, A. (2021). Monitoring linear profiles using Artificial Neural Networks with run rules. Expert Systems with Applications, 168, 114237.
Yeganeh, A., Abbasi, S. A., Pourpanah, F., Shadman, A., Johannssen, A., & Chukhrova, N. (2022a). An ensemble neural network framework for improving the detection ability of a base control chart in non-parametric profile monitoring. Expert Systems with Applications, 204, 117572.
Yeganeh, A., Fadaei, S., & Shadman, A. (2021). Developing EWMAR control chart with run rules for profile monitoring. Journal of Quality Engineering and Management, 10(4), 279-298.
Yeganeh, A., Parvizi Amineh, M., Shadman, A., Shongwe, S. C., & Mohasel, S. M. (2023). Combination of sequential sampling technique with GLR control charts for monitoring linear profiles based on the random explanatory variables. Mathematics, 11(7), 1683.
Yeganeh, A., Shadman, A., & Abbasi, S. A. (2022b). Enhancing the detection ability of control charts in profile monitoring by adding RBF ensemble model. Neural Computing and Applications, 34(12), 9733-9757.
Yeh, A. B., Huwang, L., & Li, Y. M. (2009). Profile monitoring for a binary response. IIE Transactions, 41(11), 931-941.
Zhou, Q., & Qiu, P. (2022). Phase I monitoring of serially correlated nonparametric profiles by mixed‐effects modeling. Quality and Reliability Engineering International, 38(1), 134-152.
Zi, X., Zou, C., & Tsung, F. (2012). A distribution-free robust method for monitoring linear profiles using rank-based regression. IIE Transactions, 44(11), 949-963. | ||
آمار تعداد مشاهده مقاله: 125 تعداد دریافت فایل اصل مقاله: 6 |