Presenting a model for statistical process control in order to optimize efficiency and quality in manufacturing industries
Subject Areas :
Industrial Management
abbas morovvati
1
,
Seyed Jalaledin Hosseini Ghoncheh
2
,
Hasan Haleh
3
1 - MA Student, Department of Industrial Management, Faculty of Management and Economics, Islamic Azad University, Science and Research Unit, Tehran, Iran
2 - Department of Mathematics, Islamic Azad University, Takestan branch, Takestan, Iran
3 - Department of Industrial Management, Golpayegan Technical and Engineering Faculty, Isfahan University of Technology, Golpayegan, Iran
Received: 2023-06-14
Accepted : 2023-09-04
Published : 2023-09-23
Keywords:
Efficiency,
Statistical Process Control,
Clustering,
Quality,
manufacturing industries,
Abstract :
In this research, a combined statistical process control model is presented to identify factors affecting efficiency and quality in manufacturing and component manufacturing industries, and then controlling and optimizing these processes is considered. Manufacturing and component industries are considered as the main body of the country's industries for case study and implementation. Clustering techniques are used to discover factors affecting efficiency. And then using decision tree algorithms to predict efficiency and quality in these industries, and in the final stage, control charts of dispersion and average variables are used to draw control charts. The comparison table of the parameters is prepared by the output of the Clementine software, and RapidMiner software is used in the neural network section. The results obtained from the identification of influencing and forecasting factors are close to the target values from a technical point of view, and the control charts are consistent with the technical control limits of the characteristics and are useful for optimizing the target value, which is efficiency and quality.
References:
Alexander, S.M. (1987). The application of expert system to manufacturing process control. Computers ind.Engng, 12:307-312.
Alt, F.B. (1985). Multivariate Quality Control. Encyclopedia of the Statistical Sciences, 6:110-122
Anderson, T.W., John, Wiley & Sons, Hnc. (1984). An Introduction to multivariate statistical analysis. Wiley series in probability and statistics, 3rd
Bag, Monark, Susanta Kumar Gauri, and Shankar Chakraborty. "An expert system for control chart pattern recognition." The International Journal of Advanced Manufacturing Technology62 (2012): 291-301.
Doganaksoy, N., Faltin, F.W. & Tucker, W.T. (1991), Identification of out of control quality characteristics in multivariate manufacturing environment. Communication in statistics, Theory and methods, 20(9):2275-2290.
Fatemi Qomi, Mohammad Taqi. (2001). Statistical Quality Control. Tehran. University of Technology Amir Kabir. (In Persian)
S. Bunney. & B.G. Dale. (1997). The implementation of quality management tools and techniques: A study. The TQM Magazine, 9(3), 183–189.
Hosni, Y.A. & Elshennawy, A.K. (1988). Knowledge-based Quality Control System. Computers Ind.Engng, 15,331-337.
Ismaili, M. (2014). Data Mining Concepts and Technique. Tehran. Niaze danesh. (in persian)
Jackson, J.E. (1980). Principal Components & Factor Analysis: Part I- Principal components. Journal of Quality Technology, 12(4), 201-213.
Johnson, R.A & Wichern, D.W. (1992). Applied Multivariate Statistical Analysis. Prentice Hall, 3rd
Masud, A. S., & Thenappan, M. S. (1993). A knowledge-based advisory system for statistical quality control. The International Journal of Production Research, 31(8), 1891-1900.
Mehrafrooz, Z. & Noorossana, R. (2011). An integrated model based on statistical process control and maintenance. Computers & Industrial Engineering, 61(4), 1245-1255.
Mirsepassi, Naser. & Motaghi, Mohammad Hossein. Selajgeh. Sanjar. (2009). Examining the factors related to the slowness of the implementation of the comprehensive quality management system in the public sector of Iran. Journal of Management Research, 81, Summer. (In Persian)
Montgomery, Douglas. (2007). Statistical Quality Control. Translated by Nur al-Sana, Rasool. Tehran: University of Science and Technology Publications, 8th (In Persian)
Murphy, B.J. (1987). Selecting out of control variables with hotellings multivariate quality control procedure. The Statistician, 36, 571-583.
Roland, Caulcutt. (1996). Assembly Automation. Statistical process control (SPC), 16(4), 10–14.
Ryan, T.P. (1989). Statistical Methods for Quality Improvement. John Wiley & sons Inc.
Srivastava, M.S. & Khatri, C.G. (1979). An introduction to Multivariate statistics. North Holland Inc.
Tsacle, E. G., and N. A. Aly. (1996). "An expert system model for implementing statistical process control in the health care industry." Computers & industrial engineering1-2, 450-477.
Willborn Walter, W.O. (1990). Expert System In Support Of Quality Management. Annual Quality Congress Transactions, 44,758-763.
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Alexander, S.M. (1987). The application of expert system to manufacturing process control. Computers ind.Engng, 12:307-312.
Alt, F.B. (1985). Multivariate Quality Control. Encyclopedia of the Statistical Sciences, 6:110-122
Anderson, T.W., John, Wiley & Sons, Hnc. (1984). An Introduction to multivariate statistical analysis. Wiley series in probability and statistics, 3rd
Bag, Monark, Susanta Kumar Gauri, and Shankar Chakraborty. "An expert system for control chart pattern recognition." The International Journal of Advanced Manufacturing Technology62 (2012): 291-301.
Doganaksoy, N., Faltin, F.W. & Tucker, W.T. (1991), Identification of out of control quality characteristics in multivariate manufacturing environment. Communication in statistics, Theory and methods, 20(9):2275-2290.
Fatemi Qomi, Mohammad Taqi. (2001). Statistical Quality Control. Tehran. University of Technology Amir Kabir. (In Persian)
S. Bunney. & B.G. Dale. (1997). The implementation of quality management tools and techniques: A study. The TQM Magazine, 9(3), 183–189.
Hosni, Y.A. & Elshennawy, A.K. (1988). Knowledge-based Quality Control System. Computers Ind.Engng, 15,331-337.
Ismaili, M. (2014). Data Mining Concepts and Technique. Tehran. Niaze danesh. (in persian)
Jackson, J.E. (1980). Principal Components & Factor Analysis: Part I- Principal components. Journal of Quality Technology, 12(4), 201-213.
Johnson, R.A & Wichern, D.W. (1992). Applied Multivariate Statistical Analysis. Prentice Hall, 3rd
Masud, A. S., & Thenappan, M. S. (1993). A knowledge-based advisory system for statistical quality control. The International Journal of Production Research, 31(8), 1891-1900.
Mehrafrooz, Z. & Noorossana, R. (2011). An integrated model based on statistical process control and maintenance. Computers & Industrial Engineering, 61(4), 1245-1255.
Mirsepassi, Naser. & Motaghi, Mohammad Hossein. Selajgeh. Sanjar. (2009). Examining the factors related to the slowness of the implementation of the comprehensive quality management system in the public sector of Iran. Journal of Management Research, 81, Summer. (In Persian)
Montgomery, Douglas. (2007). Statistical Quality Control. Translated by Nur al-Sana, Rasool. Tehran: University of Science and Technology Publications, 8th (In Persian)
Murphy, B.J. (1987). Selecting out of control variables with hotellings multivariate quality control procedure. The Statistician, 36, 571-583.
Roland, Caulcutt. (1996). Assembly Automation. Statistical process control (SPC), 16(4), 10–14.
Ryan, T.P. (1989). Statistical Methods for Quality Improvement. John Wiley & sons Inc.
Srivastava, M.S. & Khatri, C.G. (1979). An introduction to Multivariate statistics. North Holland Inc.
Tsacle, E. G., and N. A. Aly. (1996). "An expert system model for implementing statistical process control in the health care industry." Computers & industrial engineering1-2, 450-477.
Willborn Walter, W.O. (1990). Expert System In Support Of Quality Management. Annual Quality Congress Transactions, 44,758-763.
