Implementation of fuzzy rule-based algorithms in p control chart to improve the performance of statistical process control

Publish Year: 1397
نوع سند: مقاله ژورنالی
زبان: English
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JR_RIEJ-7-4_003

تاریخ نمایه سازی: 30 فروردین 1400

Abstract:

In the statistical process control when the process is very sensitive and control limit shifts are the prime concerns, there fuzzy control charts can be a better solution. In decision making, extra “rather in control” and “rather out of control” decisions facilitate to find out the slight changes in the control chart. The automation of fuzzy control chart in the Excel VBA makes the data input and decisions making process faster. The vagueness of the data is removed as the charts deal with the triangular or trapezoidal area rather than some points in the control limits. Alongside the fuzzy control charts, Marcucci approach has been followed to find out the goodness-of-fit of the samples and to find out the effectiveness of fuzzy control charts.

Authors

Md. F. Rabbi

Department of Industrial Engineering and Management, Faculty of Mechanical Engineering, Khulna University of Engineering and Technology, Khulna, Bangladesh.

N. Chakrabarty

Department of Industrial Engineering and Management, Faculty of Mechanical Engineering, Khulna University of Engineering and Technology, Khulna, Bangladesh.

J. Shefa

Department of Industrial Engineering and Management, Faculty of Mechanical Engineering, Khulna University of Engineering and Technology, Khulna, Bangladesh.

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  • [1]     Erginel, N. (2014). Fuzzy rule-based $tilde p $ and ...
  • [2]      Taleb, H., & Limam, M. (2002). On fuzzy and ...
  • [3]      El-Shal, S. M., & Morris, A. S. (2000). A ...
  • [4]     Paul, A. K., Shill, P. C., Rabin, M. R. ...
  • [5]     Hsu, H. M., & Chen, Y. K. (2001). A ...
  • [6]     [6] Yang, X., Wang, Z., & Zi, X. (2017). ...
  • [7]     Sousa, S., Rodrigues, N., & Nunes, E. (2017). Application ...
  • [8]     Kaya, I., Erdoğan, M., & Yıldız, C. (2017). Analysis ...
  • [9]     Fadaei, S., & Pooya, A. (2018). Fuzzy U control ...
  • [10]  Zhang, B., Yang, C., Zhu, H., Shi, P., & ...
  • [11]  Naik, N., Diao, R., & Shen, Q. (2018). Dynamic ...
  • [12]  Keivanpour, S., Ait-Kadi, D., & Mascle, C. (2017). Automobile ...
  • [13]  Cheng, C. B. (2005). Fuzzy process control: Construction of ...
  • [14]  Faraz, A., & Moghadam, M. B. (2007). Fuzzy control ...
  • [15]  Erginel, N. (2008). Fuzzy individual and moving range control ...
  • [16]  Colubi, A. (2009). Statistical inference about the means of ...
  • [17]  Kanagawa, A., Tamaki, F., & Ohta, H. (1993). Control ...
  • [18]  Kaya, İ., & Kahraman, C. (2011). Process capability analyses ...
  • [19]  Faraz, A., & Shapiro, A. F. (2010). An application ...
  • [20]  Laviolette, M., Seaman, J. W., Barrett, J. D., & ...
  • [21]  Marcucci, M. (1985). Monitoring multinomial processes. Journal of quality technology, 17(2), ...
  • [22]  Saaty, T. L. (1974). Measuring the fuzziness of sets. ...
  • [23]  Wang, J. H., & RAZ, T. (1990). On the ...
  • [24]  Woodall, W. H. (1997). Control charts based on attribute ...
  • [25]  Woodall, W. H., Tsui, K. L., & Tucker, G. ...
  • [26]  Montgomery, D. C. (2009). Introduction to statistical quality control. John ...
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