A decision making process application for the slurry production in ceramics via fuzzy cluster and data mining

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April 2012, 8(2): 285-297. doi: 10.3934/jimo.2012.8.285

A decision making process application for the slurry production in ceramics via fuzzy cluster and data mining

Feyza Gürbüz ^1, and Panos M. Pardalos ^2,

1.	Department of Industrial Engineering, University of Erciyes, Kayseri 38039, Turkey
2.	Center for Applied Optimization Department of Industrial and Systems Engineering, University of Florida, 32611, United States

Received December 2010 Revised July 2011 Published April 2012

Abstract
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To increase productivity, companies are in search of techniques that enable them to make faster and more effective decisions. Data mining and fuzzy clustering algorithms can serve for this purpose. This paper models the decision making process of a ceramics production company using a fuzzy clustering algorithm and data mining. Factors that affect the quality of slurry are measured over time. Using this data, a fuzzy clustering algorithm assigns the degrees of memberships of the slurry for the different quality clusters. An expert can decide on acceptance or rejection of slurry based on calculated degrees of memberships. In addition, by using data mining techniques we generated some rules that provide the optimum conditions for acceptance of the slurry.

Keywords: decision trees, ceramics., Data mining, fuzzy cluster analysis.

Mathematics Subject Classification: Primary: 58F15, 58F17; Secondary: 53C3.

Citation: Feyza Gürbüz, Panos M. Pardalos. A decision making process application for the slurry production in ceramics via fuzzy cluster and data mining. Journal of Industrial & Management Optimization, 2012, 8 (2) : 285-297. doi: 10.3934/jimo.2012.8.285

References:

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[2]	Roelof K. Brouwer and Albert Groenwold, Modified fuzzy c-means for ordinal valued attributes with particle swarm for optimization,, Fuzzy Sets and Systems, 161 (2010), 1774. doi: 10.1016/j.fss.2009.10.019.
[3]	Toly Chen, Incorporating fuzzy c-means and a back-propagation network ensemble to job completion time prediction in a semiconductor fabrication factory,, Fuzzy Sets and Systems, 158 (2007), 2153. doi: 10.1016/j.fss.2007.04.013.
[4]	Wei-Chou Chen, Shian-Shyong Tseng and Ching-Yao Wang, Novel manufacturing defect detection method using association rule mining techniques,, Expert Systems with Applications, 29 (2005), 807. doi: 10.1016/j.eswa.2005.06.004.
[5]	Russ M. Dabbas and Hung-Nan Chen, Mining semiconductor manufacturing data for productivity improvement-An integrated relational database approach,, Computers in Industry, 45 (2001), 29. doi: 10.1016/S0166-3615(01)00079-3.
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[9]	Alex A. Freitas, "Data Mining and Knowledge Discovery with Evolutionary Algorithms,", Springer-Verlag, (2002).
[10]	J. L. Garcia-Lapresta, M. Martinez-Panero and L. L. Lazzari, A group decision making method using fuzzy triangular numbers,, in, (2001), 35.
[11]	Adem Göleç, "Fuzzy Modelling Approach in Feature-Based Computer-Aided Process Planning,", Ph.D thesis, (2001).
[12]	D. Hand, H. Manila and P. Smyth, "Principles of Data Mining,", A Bradford Book, (2001).
[13]	Maurice Houtsma and Arun Swami, Set-oriented data mining in relational databases,, Data & Knowledge Engineering, 17 (1995), 245. doi: 10.1016/0169-023X(95)00024-M.
[14]	K. Josien and T. W. Liao, Integrated use of fuzzy C-means and fuzzy KNN for GT part family and machine cell formation,, International Journal of Production Research, 38 (2000), 3513. doi: 10.1080/002075400422770.
[15]	Han Jiawei and Micheline Kamber, "Data Mining: Concepts And Techniques,", University Of Simon Fraser, (2001).
[16]	Andrew Kusiak and Mathew Smith, Data mining in design of products and production systems,, Annual Reviews in Control, 31 (2007), 147. doi: 10.1016/j.arcontrol.2007.03.003.
[17]	Surendra Kumar and C. S. P. Rao, Application of ant colony, genetic algorithm and data mining-based techniques for scheduling,, Robotics and Computer-Integrated Manufacturing, 25 (2009), 901. doi: 10.1016/j.rcim.2009.04.015.
[18]	Der-Chang Li and Chun-Wu Yeh, A non-parametric learning algorithm for small manufacturing data sets,, Expert Systems with Applications, 34 (2008), 391. doi: 10.1016/j.eswa.2006.09.008.
[19]	Emmanouil Magkos, Manolis Maragoudakis, Vassilis Chrissikopoulos and Stefanos Gritzalis, Accurate and large-scale privacy-preserving data mining using the election paradigm,, Data & Knowledge Engineering, 68 (2009), 1224. doi: 10.1016/j.datak.2009.06.003.
[20]	Ye Nong, "The Handbook of Data Mining,", Lawrence Erlbaum Associates Publishers, (2003).
[21]	Atakan Öztürk, Sinan Kayalıgil and Nur E. Özdemirel, Manufacturing lead time estimation using data mining,, European Journal of Operational Research, 173 (2006), 683. doi: 10.1016/j.ejor.2005.03.015.
[22]	Nikhil R. Pal and James C. Bezdek, On cluster validity for the fuzzy c-means model,, IEEE Transactions on Fuzzy Systems, 3 (1995), 370. doi: 10.1109/91.413225.
[23]	Lee Sangjae, Using data envelopment analysis and decision trees for efficiency analysis and recommendation of B2C controls,, Decision Support Systems, 49 (2010), 486. doi: 10.1016/j.dss.2010.06.002.
[24]	Magne Setnes, Supervised fuzzy clustering for rule extraction,, IEEE Transactions on Fuzzy Systems, 8 (2000), 416. doi: 10.1109/91.868948.
[25]	Michio Sugeno and Takahiro Yasukawa, A fuzzy-logic based approach to qualitative modeling,, IEEE Transactions on Fuzzy Systems, 1 (1993), 7. doi: 10.1109/TFUZZ.1993.390281.
[26]	, "User Manual of Polyanalyst 5,", 2005., ().
[27]	Wei Yan, Chun-Hsien Chen and Meng-Dar Shieh, Product concept generation and selection using sorting technique and fuzzy c-means algorithm,, Computers & Industrial Engineering, 50 (2006), 273. doi: 10.1016/j.cie.2006.05.003.
[28]	Ian H. Witten and Eibe Frank, "Data Mining: Practical Machine Learning Tools and Techniques,", Elsevier, (2005).

show all references

References:

[1]	M. Arenas, A. Bilboa, M. V. Rodriguez Uria and M. Jimenez, A Fuzzy goal programming model for evaluating a hospital service performance,, in, (2001), 19.
[2]	Roelof K. Brouwer and Albert Groenwold, Modified fuzzy c-means for ordinal valued attributes with particle swarm for optimization,, Fuzzy Sets and Systems, 161 (2010), 1774. doi: 10.1016/j.fss.2009.10.019.
[3]	Toly Chen, Incorporating fuzzy c-means and a back-propagation network ensemble to job completion time prediction in a semiconductor fabrication factory,, Fuzzy Sets and Systems, 158 (2007), 2153. doi: 10.1016/j.fss.2007.04.013.
[4]	Wei-Chou Chen, Shian-Shyong Tseng and Ching-Yao Wang, Novel manufacturing defect detection method using association rule mining techniques,, Expert Systems with Applications, 29 (2005), 807. doi: 10.1016/j.eswa.2005.06.004.
[5]	Russ M. Dabbas and Hung-Nan Chen, Mining semiconductor manufacturing data for productivity improvement-An integrated relational database approach,, Computers in Industry, 45 (2001), 29. doi: 10.1016/S0166-3615(01)00079-3.
[6]	Margaret H. Dunham, "Data Mining: Introductory and Advanced Topics,", Prentice Hall PTR, (2002).
[7]	Mohammad R. Emami, Burhan I. Türksen and Andrew A. Goldenberg, An improved fuzzy modeling algorithm part I: Inference mechanism,, in, (1996).
[8]	Mohammad R. Emami, Burhan I. Türksen and Andrew A. Goldenberg, Development of a systematic methodology of fuzzy logic modeling,, IEEE Transactions on Fuzzy Systems, 6 (1998), 346. doi: 10.1109/91.705501.
[9]	Alex A. Freitas, "Data Mining and Knowledge Discovery with Evolutionary Algorithms,", Springer-Verlag, (2002).
[10]	J. L. Garcia-Lapresta, M. Martinez-Panero and L. L. Lazzari, A group decision making method using fuzzy triangular numbers,, in, (2001), 35.
[11]	Adem Göleç, "Fuzzy Modelling Approach in Feature-Based Computer-Aided Process Planning,", Ph.D thesis, (2001).
[12]	D. Hand, H. Manila and P. Smyth, "Principles of Data Mining,", A Bradford Book, (2001).
[13]	Maurice Houtsma and Arun Swami, Set-oriented data mining in relational databases,, Data & Knowledge Engineering, 17 (1995), 245. doi: 10.1016/0169-023X(95)00024-M.
[14]	K. Josien and T. W. Liao, Integrated use of fuzzy C-means and fuzzy KNN for GT part family and machine cell formation,, International Journal of Production Research, 38 (2000), 3513. doi: 10.1080/002075400422770.
[15]	Han Jiawei and Micheline Kamber, "Data Mining: Concepts And Techniques,", University Of Simon Fraser, (2001).
[16]	Andrew Kusiak and Mathew Smith, Data mining in design of products and production systems,, Annual Reviews in Control, 31 (2007), 147. doi: 10.1016/j.arcontrol.2007.03.003.
[17]	Surendra Kumar and C. S. P. Rao, Application of ant colony, genetic algorithm and data mining-based techniques for scheduling,, Robotics and Computer-Integrated Manufacturing, 25 (2009), 901. doi: 10.1016/j.rcim.2009.04.015.
[18]	Der-Chang Li and Chun-Wu Yeh, A non-parametric learning algorithm for small manufacturing data sets,, Expert Systems with Applications, 34 (2008), 391. doi: 10.1016/j.eswa.2006.09.008.
[19]	Emmanouil Magkos, Manolis Maragoudakis, Vassilis Chrissikopoulos and Stefanos Gritzalis, Accurate and large-scale privacy-preserving data mining using the election paradigm,, Data & Knowledge Engineering, 68 (2009), 1224. doi: 10.1016/j.datak.2009.06.003.
[20]	Ye Nong, "The Handbook of Data Mining,", Lawrence Erlbaum Associates Publishers, (2003).
[21]	Atakan Öztürk, Sinan Kayalıgil and Nur E. Özdemirel, Manufacturing lead time estimation using data mining,, European Journal of Operational Research, 173 (2006), 683. doi: 10.1016/j.ejor.2005.03.015.
[22]	Nikhil R. Pal and James C. Bezdek, On cluster validity for the fuzzy c-means model,, IEEE Transactions on Fuzzy Systems, 3 (1995), 370. doi: 10.1109/91.413225.
[23]	Lee Sangjae, Using data envelopment analysis and decision trees for efficiency analysis and recommendation of B2C controls,, Decision Support Systems, 49 (2010), 486. doi: 10.1016/j.dss.2010.06.002.
[24]	Magne Setnes, Supervised fuzzy clustering for rule extraction,, IEEE Transactions on Fuzzy Systems, 8 (2000), 416. doi: 10.1109/91.868948.
[25]	Michio Sugeno and Takahiro Yasukawa, A fuzzy-logic based approach to qualitative modeling,, IEEE Transactions on Fuzzy Systems, 1 (1993), 7. doi: 10.1109/TFUZZ.1993.390281.
[26]	, "User Manual of Polyanalyst 5,", 2005., ().
[27]	Wei Yan, Chun-Hsien Chen and Meng-Dar Shieh, Product concept generation and selection using sorting technique and fuzzy c-means algorithm,, Computers & Industrial Engineering, 50 (2006), 273. doi: 10.1016/j.cie.2006.05.003.
[28]	Ian H. Witten and Eibe Frank, "Data Mining: Practical Machine Learning Tools and Techniques,", Elsevier, (2005).

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