How to cite this paper
Boroujeni, M., Samimi, Y & Roghanian, E. (2021). Monitoring fuzzy linear quality profiles: A comparative study.International Journal of Industrial Engineering Computations , 12(1), 37-48.
Refrences
Akbari, M.G., Mohammadalizadeh, R., & Rezaei, M. (2012). Bootstrap statistical inference about the regression coefficients based on fuzzy data. International Journal of Fuzzy Systems, 14(4), 549-556.
Alaeddini, A., Ghazanfari, M., & Nayeri, M. A. (2009). A hybrid fuzzy-statistical clustering approach for estimating the time of changes in fixed and variable sampling control charts. Information Sciences, 179(11), 1769-1784.
Celmin’s, A. (1987). Least-squares model fitting of fuzzy vector data. Fuzzy Sets and Systems, 22(3), 245-269.
Chen, J., & Liang, Y. (2016). Development of fuzzy logic-based statistical process control chart pattern recognition system. The International Journal of Advanced Manufacturing Technology, 86(1-4), 1011–1026.
Cheng, C.B. (2005). Fuzzy process control: construction of control charts with fuzzy numbers. Fuzzy Sets and Systems, 154(2),287-303.
Coppi, R., D’Urso, P., Giordani, P., & Santoro, A. (2006). Least squares estimation of a linear regression model with LR fuzzy response. Computational Statistics & Data Analysis, 51(1), 267–286.
D’Urso, P. (2003). Linear regression analysis for fuzzy/crisp input and fuzzy/crisp output data. Computational Statistics & Data Analysis, 42(1-2), 47–72.
Demirli, K., & Vijayakumar, S. (2010). Fuzzy logic based assignable cause diagnosis using control chart patterns. Information Sciences, 180(17), 3258-3272.
El-Shal, S.M., & Morris, A.S. (2000). A fuzzy rule-based algorithm to improve the performance of statistical process control in quality systems. Journal of Intelligent and Fuzzy Systems, 9(3-4), 207-223.
Fernández, M. N. P. (2017, July). Fuzzy theory and quality control charts. In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 1-6). IEEE.
Franceschini, F., & Romano, D. (1999). Control chart for linguistic variables: A method based on the use of linguistic quantifiers. International Journal of Production Research, 37(16), 3791-3801.
Ghobadi, S., Noghondarian, K., Noorossana, R., & Mirhosseini, S.M.S. (2014). Developing a multivariate approach to monitor fuzzy quality profiles. Quality & Quantity, 48(2), 817-836.
Gulbuy, M., Kahraman, C., & Ruan, D. (2004). α‐Cut fuzzy control charts for linguistic data. International Journal of Intelligent Systems, 19(12), 1173-1195.
Hassanpur, H., Maleki, H.R., & Yaghoobi, M.A. (2009). A goal programming approach for fuzzy linear regression with nonfuzzy input and fuzzy output data. Asia Pacific Journal of Operational Research, 26(5), 1-18.
Hong, D. H., & Hwang, C. (2006, September). Fuzzy nonlinear regression model based on LS-SVM in feature space. In International Conference on Fuzzy Systems and Knowledge Discovery (pp. 208-216). Springer, Berlin, Heidelberg., https://doi.org/10.1007/11881599_23
Kanagawa, A., Tamaki, F., & Ohta, H. (1993). Control charts for process average and the variability based on linguistic data. International Journal of Production Research, 31(4), 913-922.
Kang, L., & Albin, S.L. (2000). On-line monitoring when the process yields a linear profile. Journal of Quality Technology, 32(4), 418-426.
Kim, K., Mahmoud, M.A., & Woodall, W.H. (2003). On the monitoring of linear profiles. Journal of Quality Technology, 35(3), 317-328.
Korner, R., & Nather, W. (1998). Linear regression with random fuzzy variables: extended classical estimates, best linear estimates, least squares estimates. Information Sciences, 109(1-4), 95-118.
Mahmoud, M.A., Parker, P.A., Woodall, W.H., & Hawkins, D.M. (2007). A change point method for linear profile data. Quality and Reliability Engineering International, 23(2), 247–268.
Moghadam, G., Raissi Ardali, G.A., & Amirzadeh, V. (2015). Developing new methods to monitor phase II fuzzy linear profiles. Iranian Journal of Fuzzy Systems, 12(4), 59-77.
Moghadam, G., Raissi Ardali, G.A., & Amirzadeh, V. (2016). New fuzzy EWMA control charts for monitoring phase II fuzzy profiles. Decision Science Letters, 5(1), 119-128.
Moghadam, G., Raissi Ardali, G.A., & Amirzadeh, V. (2018). A novel phase I fuzzy profile monitoring approach based on fuzzy change point analysis. Applied Soft Computing, 71, 488-504.
Montgomery, D.C. (2009). Introduction to Statistical Quality Control (6th ed.). New York: John Wiley & Sons.
Noghondarian, K., & Ghobadi, S. (2012). Developing a univariate approach to phase I monitoring of fuzzy quality profiles. International Journal of Industrial Engineering Computations, 3(5), 829-842.
Noorossana, R., Saghaei, A., & Amiri, A. (2011). Statistical analysis of profile monitoring (Vol. 865). John Wiley & Sons.
Raz, T., & Wang, J.H. (1990). Probabilistic and membership approaches in the construction of control charts for linguistic data. Production Planning & Control, 1(3), 147-157.
Sabegh, M.H.Z., Mirzazadeh, A., Salehian, S., & Weber, G.W. (2014). A literature review on the fuzzy control chart; classifications & analysis. International Journal of Supply and Operations Management, 1(2), 167-189.
Senturk, S., & Antucheviciene, J. (2017). Interval Type-2 Fuzzy c-Control Charts: An Application in a Food Company. Informatica, 28(2), 269-283.
Senturk, S., Erginel, N., Kaya, I., & Kahraman, C. (2014). Fuzzy exponentially weighted moving average control chart for univariate data with a real case application. Applied Soft Computing, 22, 1-10.
Su, Z., Wang, P., & Song, Z. (2013). Kernel-based nonlinear fuzzy regression model. Engineering Applications of Artificial Intelligence, 26(2), 724-738.
Taheri, S.M., & Arefi, M. (2009). Testing fuzzy hypotheses based on fuzzy test statistic. Soft Computing, 13(6), 617-625.
Taleb, H., & Limam, M. (2002). On fuzzy and probabilistic control charts. International Journal of Production Research, 40(12), 2849-2863.
Tanaka, H., Uejima, S., & Asai, K. (1982). Linear regression analysis with fuzzy model. IEEE Transaction of Systems and Man Cybernetics, 12(6), 903-907.
Tanaka, H. (1987). Fuzzy data analysis by possibilistic linear models. Fuzzy Sets and Systems, 24(3), 363-375.
Viertl, R. (2011). Statistical methods for fuzzy data (1st ed.). Austria: John Wiley & Sons.
Wang, D., Li, P., & Yasuda, M. (2014). Construction of Fuzzy Control Charts Based on Weighted Possibilistic Mean. Communications in Statistics- Theory and Methods, 43(15), 3186-3207.
Zarandi, M.H.F., & Alaeddini, M. (2010). A general fuzzy-statistical clustering approach for estimating the time of change in variable sampling control charts. Information Sciences, 180(16), 3033-3044.
Zou, C., Zhang, Y., & Wang, Z. (2006). A control chart based on a change-point model for monitoring linear profiles. IIE Transactions, 38(12), 1093-1103.
Alaeddini, A., Ghazanfari, M., & Nayeri, M. A. (2009). A hybrid fuzzy-statistical clustering approach for estimating the time of changes in fixed and variable sampling control charts. Information Sciences, 179(11), 1769-1784.
Celmin’s, A. (1987). Least-squares model fitting of fuzzy vector data. Fuzzy Sets and Systems, 22(3), 245-269.
Chen, J., & Liang, Y. (2016). Development of fuzzy logic-based statistical process control chart pattern recognition system. The International Journal of Advanced Manufacturing Technology, 86(1-4), 1011–1026.
Cheng, C.B. (2005). Fuzzy process control: construction of control charts with fuzzy numbers. Fuzzy Sets and Systems, 154(2),287-303.
Coppi, R., D’Urso, P., Giordani, P., & Santoro, A. (2006). Least squares estimation of a linear regression model with LR fuzzy response. Computational Statistics & Data Analysis, 51(1), 267–286.
D’Urso, P. (2003). Linear regression analysis for fuzzy/crisp input and fuzzy/crisp output data. Computational Statistics & Data Analysis, 42(1-2), 47–72.
Demirli, K., & Vijayakumar, S. (2010). Fuzzy logic based assignable cause diagnosis using control chart patterns. Information Sciences, 180(17), 3258-3272.
El-Shal, S.M., & Morris, A.S. (2000). A fuzzy rule-based algorithm to improve the performance of statistical process control in quality systems. Journal of Intelligent and Fuzzy Systems, 9(3-4), 207-223.
Fernández, M. N. P. (2017, July). Fuzzy theory and quality control charts. In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 1-6). IEEE.
Franceschini, F., & Romano, D. (1999). Control chart for linguistic variables: A method based on the use of linguistic quantifiers. International Journal of Production Research, 37(16), 3791-3801.
Ghobadi, S., Noghondarian, K., Noorossana, R., & Mirhosseini, S.M.S. (2014). Developing a multivariate approach to monitor fuzzy quality profiles. Quality & Quantity, 48(2), 817-836.
Gulbuy, M., Kahraman, C., & Ruan, D. (2004). α‐Cut fuzzy control charts for linguistic data. International Journal of Intelligent Systems, 19(12), 1173-1195.
Hassanpur, H., Maleki, H.R., & Yaghoobi, M.A. (2009). A goal programming approach for fuzzy linear regression with nonfuzzy input and fuzzy output data. Asia Pacific Journal of Operational Research, 26(5), 1-18.
Hong, D. H., & Hwang, C. (2006, September). Fuzzy nonlinear regression model based on LS-SVM in feature space. In International Conference on Fuzzy Systems and Knowledge Discovery (pp. 208-216). Springer, Berlin, Heidelberg., https://doi.org/10.1007/11881599_23
Kanagawa, A., Tamaki, F., & Ohta, H. (1993). Control charts for process average and the variability based on linguistic data. International Journal of Production Research, 31(4), 913-922.
Kang, L., & Albin, S.L. (2000). On-line monitoring when the process yields a linear profile. Journal of Quality Technology, 32(4), 418-426.
Kim, K., Mahmoud, M.A., & Woodall, W.H. (2003). On the monitoring of linear profiles. Journal of Quality Technology, 35(3), 317-328.
Korner, R., & Nather, W. (1998). Linear regression with random fuzzy variables: extended classical estimates, best linear estimates, least squares estimates. Information Sciences, 109(1-4), 95-118.
Mahmoud, M.A., Parker, P.A., Woodall, W.H., & Hawkins, D.M. (2007). A change point method for linear profile data. Quality and Reliability Engineering International, 23(2), 247–268.
Moghadam, G., Raissi Ardali, G.A., & Amirzadeh, V. (2015). Developing new methods to monitor phase II fuzzy linear profiles. Iranian Journal of Fuzzy Systems, 12(4), 59-77.
Moghadam, G., Raissi Ardali, G.A., & Amirzadeh, V. (2016). New fuzzy EWMA control charts for monitoring phase II fuzzy profiles. Decision Science Letters, 5(1), 119-128.
Moghadam, G., Raissi Ardali, G.A., & Amirzadeh, V. (2018). A novel phase I fuzzy profile monitoring approach based on fuzzy change point analysis. Applied Soft Computing, 71, 488-504.
Montgomery, D.C. (2009). Introduction to Statistical Quality Control (6th ed.). New York: John Wiley & Sons.
Noghondarian, K., & Ghobadi, S. (2012). Developing a univariate approach to phase I monitoring of fuzzy quality profiles. International Journal of Industrial Engineering Computations, 3(5), 829-842.
Noorossana, R., Saghaei, A., & Amiri, A. (2011). Statistical analysis of profile monitoring (Vol. 865). John Wiley & Sons.
Raz, T., & Wang, J.H. (1990). Probabilistic and membership approaches in the construction of control charts for linguistic data. Production Planning & Control, 1(3), 147-157.
Sabegh, M.H.Z., Mirzazadeh, A., Salehian, S., & Weber, G.W. (2014). A literature review on the fuzzy control chart; classifications & analysis. International Journal of Supply and Operations Management, 1(2), 167-189.
Senturk, S., & Antucheviciene, J. (2017). Interval Type-2 Fuzzy c-Control Charts: An Application in a Food Company. Informatica, 28(2), 269-283.
Senturk, S., Erginel, N., Kaya, I., & Kahraman, C. (2014). Fuzzy exponentially weighted moving average control chart for univariate data with a real case application. Applied Soft Computing, 22, 1-10.
Su, Z., Wang, P., & Song, Z. (2013). Kernel-based nonlinear fuzzy regression model. Engineering Applications of Artificial Intelligence, 26(2), 724-738.
Taheri, S.M., & Arefi, M. (2009). Testing fuzzy hypotheses based on fuzzy test statistic. Soft Computing, 13(6), 617-625.
Taleb, H., & Limam, M. (2002). On fuzzy and probabilistic control charts. International Journal of Production Research, 40(12), 2849-2863.
Tanaka, H., Uejima, S., & Asai, K. (1982). Linear regression analysis with fuzzy model. IEEE Transaction of Systems and Man Cybernetics, 12(6), 903-907.
Tanaka, H. (1987). Fuzzy data analysis by possibilistic linear models. Fuzzy Sets and Systems, 24(3), 363-375.
Viertl, R. (2011). Statistical methods for fuzzy data (1st ed.). Austria: John Wiley & Sons.
Wang, D., Li, P., & Yasuda, M. (2014). Construction of Fuzzy Control Charts Based on Weighted Possibilistic Mean. Communications in Statistics- Theory and Methods, 43(15), 3186-3207.
Zarandi, M.H.F., & Alaeddini, M. (2010). A general fuzzy-statistical clustering approach for estimating the time of change in variable sampling control charts. Information Sciences, 180(16), 3033-3044.
Zou, C., Zhang, Y., & Wang, Z. (2006). A control chart based on a change-point model for monitoring linear profiles. IIE Transactions, 38(12), 1093-1103.