A hybrid approach to machine-tool selection through AHP and simulation

The selection process of a machine tool has been a critical issue for companies for years, because the improper selection of a machine tool might cause many problems having a negative effect on productivity, precision, flexibility, and a company's responsive manufacturing capabilities. Therefore, in this paper, to determine the best machine tool satisfying the needs and expectations of a manufacturing organization among a set of possible alternatives in the market, a hybrid approach is proposed, which integrates an analytic hierarchy process (AHP) with simulation techniques. The AHP as one of the most commonly used multiple criteria decision-making methods is used to narrow down all possible machine tool alternatives in the market by eliminating those whose scores (or weights) are smaller than a determined value obtained under certain circumstances. Then, a simulation generator is used first to automatically model a manufacturing organization, where the ultimate machine tool will be used, and second to try each alternative remaining from the AHP as a scenario on the generated model. Finally, the final alternative is selected by using the unit investment cost ratio, which is calculated by dividing the investment cost per year of each alternative by the additional number of produced units obtained from the simulation experiment of the relevant alternative.

[1]  Bülent Çatay,et al.  A decision support system for machine tool selection , 2004 .

[2]  Claude Dennis Pegden,et al.  Introduction to SIMAN , 1983, WSC '85.

[3]  Mario T. Tabucanon,et al.  Decision support system for multicriteria machine selection for flexible manufacturing systems , 1994 .

[4]  Zeki Ayağ,et al.  An integrated approach to evaluating conceptual design alternatives in a new product development environment , 2005 .

[5]  Thomas L. Saaty,et al.  Decision Making, Scaling, and Number Crunching , 1989 .

[6]  Mustafa Yurdakul,et al.  AHP as a strategic decision-making tool to justify machine tool selection , 2004 .

[7]  Bhaskaran Gopalakrishnan,et al.  Decision support system for machining center selection , 2004 .

[8]  E. Cagno.  Competitive Bidding : A Multi-criteria Approach to Assess the Probability of Winning , 1997 .

[9]  Bing Jiang,et al.  The development of intelligent decision support tools to aid the design of flexible manufacturing systems , 2000 .

[10]  Haldun Aytuḡ,et al.  A framework and a simulation generator for kanban-controlled manufacturing systems , 1998 .

[11]  Robert M. O'Keefe,et al.  Data-driven generic simulators for flexible manufacturing systems , 1991 .

[12]  Michael J. Scott,et al.  Quantifying Certainty in Design Decisions: Examining AHP , 2002 .

[13]  Reuven R. Levary,et al.  An analytic hierarchy process based simulation model for entry mode decision regarding foreign direct investment , 1999 .

[14]  Zeki Ayağ,et al.  A fuzzy AHP-based simulation approach to concept evaluation in a NPD environment , 2005 .

[15]  Svetan M. Ratchev,et al.  Integrated framework for machining equipment in selection of CIM , 1998, Int. J. Comput. Integr. Manuf..

[16]  Tai-Yue Wang,et al.  Machine selection in flexible manufacturing cell: A fuzzy multiple attribute decision-making approach , 2000 .

[17]  Zone-Ching Lin,et al.  Evaluation of machine selection by the AHP method , 1996 .

[18]  Toshiyuki Sueyoshi,et al.  A unified framework for the selection of a Flexible Manufacturing System , 1995 .

[19]  Bernard J. Schroer,et al.  A Simulation Assistant for Modeling Manufacturing Systems , 1989, Simul..

[20]  Jorge Haddock,et al.  A decision support system for specific machine selection , 1989 .

[21]  William J. Kolarik,et al.  Strategic planning in manufacturing systems: AHP application to an equipment replacement decision , 1995 .

[22]  Adedeji B. Badiru,et al.  DDM: Decision support system for hierarchical dynamic decision making , 1993, Decis. Support Syst..

[23]  Hannu Kivijärvi,et al.  INTEGRATING AHP AND DYNAMIC SIMULATION: EXPERIENCES, CONCEPTUALIZATIONS AND BUSINESS EXPERIMENTS , 1999 .

[24]  Y. A. Tung,et al.  A revised weighted sum decision model for robot selection , 1996 .

[25]  Fatemeh Zahedi,et al.  The Analytic Hierarchy Process—A Survey of the Method and its Applications , 1986 .

[26]  Zeki Ayağ,et al.  An analytic-hierarchy-process based simulation model for implementation and analysis of computer-aided systems , 2002 .

[27]  Louis G. Birta,et al.  A knowledge-based approach for the validation of simulation models: the foundation , 1996, TOMC.

[28]  T. Saaty,et al.  Fundamentals of the analytic network process — Dependence and feedback in decision-making with a single network , 2004 .

[29]  Henry C. W. Lau,et al.  Integration of expert system with analytic hierarchy process for the design of material handling equipment selection system , 2001 .

[30]  Felix T.S. Chan,et al.  Design and evaluation of automated cellular manufacturing systems with simulation modelling and AHP approach: A case study , 1996 .

[31]  F. Lootsma.  Fuzzy Logic for Planning and Decision Making , 1997 .