Development of KM-Based Multi-Criteria Decision-Making Method for Evaluation of 4-Axis CNC Machine Tool

Abstract:

Facing the increasing competitive environment of globalization, companies are forced to make careful decisions so as to get the competitive advantage. The analytic hierarchy process (AHP) method has be proposed and popularly applied in many disciplines over three decades. In the past, many scholars also developed various improved methods such as Delphi AHP , fuzzy AHP, or Analytic Network Process (ANP) to enhance the decision quality. However, all the current AHP related methods have no function to provide enough reference information and a friendly environment to support the decision makers. Recently, Knowledge Management (KM) has attracted a great deal of interest in industry and academy. Therefore, in this paper, we proposed a KM-based AHP decision-making method to provide the questionnaire designer a guideline or reference and developed a decision-support web questionnaire system based on the knowledge chain model. A case study of selecting a 4-axis machine tool was illustrated the implementation and applicability of this method, a mold manufacturing company was invited as the survey objective. The method proposed in this research provides a different research direction and it is general in form to be applied for the other multi-criteria decision making cases.

• Periodical: Applied Mechanics and Materials (Volume 163)
• Pages: 143-150
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.163.143
• Online since: April 2012
• Authors: Jo Peng Tsai, Hsin Yu Cheng, Jen Her Wu, Rong Shean Lee
• Keywords: 4-Axis Machine Tool, Analysis Hierarchy Process (AHP), Knowledge Chain, Multi-Criteria Decision Making

References

[1] T.L. Saaty, The Analytic Hierarchy Process, McGraw-Hill, New York, (1980).

[2] L.A. Vidal, F. Marle, J.C. Bocquet, Using a Delphi process and the Analytic Hierarchy Process (AHP) to evaluate the complexity of projects, Expert Systems with Applications, Vol. 38 (2011), pp.5388-5405.

DOI: 10.1016/j.eswa.2010.10.016

[3] H.Y. Wu, J.K. Chen I.S. Chen, Innovation capital indicator assessment of Taiwanese Universities: A hybrid fuzzy model application, Expert Systems with Applications, Vol. 37 (2010), pp.1635-1642.

DOI: 10.1016/j.eswa.2009.06.045

[4] M.P. Niemira, T.L. Saaty, An Analytic Network Process model for financial-crisis forecasting, International Journal of Forecasting, Vol. 20 (2004), pp.573-587.

DOI: 10.1016/j.ijforecast.2003.09.013

[5] T.H. Davenport, Best Practice Make Better Decisions, Harvard Business Review, (2009), pp.117-124.

[6] K. Jones, Knowledge Management As A Foundation For Decision Support Systems, Journal Of Computer Information Systems, (2006), pp.116-125.

[7] H.F. Lin, An application of fuzzy AHP for evaluating course website quality, Computers & Education, Vol. 54 (2010), pp.877-888.

DOI: 10.1016/j.compedu.2009.09.017

[8] C.C. Huang, P.Y. Chu, Y.H. Chiang, A fuzzy AHP application in government-sponsored R&D project selection, Omega, Vol. 36 (2008), pp.1038-1052.

DOI: 10.1016/j.omega.2006.05.003

[9] Y.J. Chiu and Y.W. Chen, Using AHP in patent valuation, Mathematical and Computer Modelling, Vol. 46 (2007), pp.1054-1062.

DOI: 10.1016/j.mcm.2007.03.009

[10] C.W. Holsapple, M. Singh, The knowledge chain model: activities for competitiveness, Expert Systems with Applications, Vol. 20 (2001), pp.77-98.

DOI: 10.1016/s0957-4174(00)00050-6

[11] M.T. Tabucanon, D.N. Batanov and D.K. Verma, Intelligent decision support system (DSS) for the selection process of alternative machines for flexible manufacturing systems (FMS), Computers in Industry, Vol. 25 (1994), p.131–143.

DOI: 10.1016/0166-3615(94)90044-2

[12] S. Myint and M.T. Tabucanon, A multiple-criteria approach to machine selection for flexible manufacturing systems, International Journal of Production Economics, Vol. 33 (1994), No. 1-3, pp.121-131.

DOI: 10.1016/0925-5273(94)90125-2

[13] Z.C. Lin and C.B. Yang, Evaluation of machine selection by the AHP method, Journal of Material Processing Technology, Vol. 57 (1996), p.253–258.

[14] L.H.S. Luong, A decision support system for the selection of computer-integrated manufacturing technologies, Robotics and Computer-Integrated Manufacturing, Vol. 14 (1998), pp.45-53.

DOI: 10.1016/s0736-5845(97)00026-4

[15] T.Y. Wang, C.F. Shaw and Y.L. Chen, Machine selection in flexible manufacturing cell: a fuzzy multiple attribute decision making approach, International Journal of Production Research, Vol. 38 (2000), No. 9, p.2079–(2097).

DOI: 10.1080/002075400188519

[16] M. Yurdakul, AHP as a strategic decision-making tool to justify machine tool selection, Journal of Materials Processing Technology, Vol. 146 (2004), p.365–376.

DOI: 10.1016/j.jmatprotec.2003.11.026

[17] M.C. Arslan, B. Çatay and E. Budak, A decision support system for machine tool selection, Journal of Manufacturing Technology Management, Vol. 15 (2004), No. 1, p.101–109.

DOI: 10.1108/09576060410512374

[18] Z. Ayağ, and R. G. Özdemir, A fuzzy AHP approach to evaluating machine tool alternatives, Journal of Intelligent Manufacturing, Vol. 17 (2006), p.179–190.

DOI: 10.1007/s10845-005-6635-1

[19] C.W. Chang, C.R. Wu, C.T. Lin and H.C. Chen, An application of AHP and sensitivity analysis for selecting the best slicing machine, Computers & Industrial Engineering, Vol. 52 (2007), p.296–307.

DOI: 10.1016/j.cie.2006.11.006

[20] C. Çimren, B. Çatay and E. Budak, Development of a machine tool selection system using AHP, The International Journal of Advanced Manufacturing Technology, Vol. 35 (2007), 363–376.

DOI: 10.1007/s00170-006-0714-0

[21] O. Durán, and J. Aguilo, Computer-aided machine-tool selection based on a Fuzzy-AHP approach, Expert Systems with Applications, Vol. 34 (2008), p.1787–1794.

DOI: 10.1016/j.eswa.2007.01.046