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Computer aided FMS machine tools subsystem selection using the evolutionary system of multicriteria analysis

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
One of the key problems in the area of flexible manufacturing systems (FMS) design is a problem of proper design of manufacturing subsystem and especially the machine tools selection. Although the problem seems to be simple, in fact it is difficult to solve because of large variety and number of parameters and also brief foredesign which are highly influential for the decision. This study shows possibility of implementation the Evolutionary System of Multicriteria Analysis for defining the importance of solutions in the process of casing-class FMS machine tools selection.
Rocznik
Strony
18--29
Opis fizyczny
Bibliogr. 24 poz., fig., tab.
Twórcy
autor
  • Lublin University of Technology, Faculty of Management, Department of Enterprise Organization, ul. Nadbystrzycka 38, 20-618 Lublin
  • Lublin University of Technology, Faculty of Fundamentals of Technology, Department of Fundamentals of Technology, ul. Nadbystrzycka 38, 20-618 Lublin
autor
  • Lublin University of Technology, Faculty of Mechanical Engineering, Institute of Technological Systems of Information, ul. Nadbystrzycka 36, 20-618 Lublin
Bibliografia
  • 1. ARSLAN M.C., CATAY B., BUDAK E.: A decision support system for machine tool selection, Journal of Manufacturing Technology Management (2004), Vol. 5, pp. 101-109.
  • 2. ATAMANI A., LASHKARI R.S: A model of machine tool selection and operation allocation in flexible manufacturing systems, International Journal of Production Research (1998), Vol. 36, pp. 1339-1349.
  • 3. AYAG Z, OZDEMIR R.G.: A fuzzy AHP approach to evaluating machine tool alternatives, Journal of Intelligent Manufacturing (2006), Vol. 17, 179-190.
  • 4. AYAG Z.: A hybrid approach to machine tool selection through AHP and simulation. International Journal of Production Research (2007), Vol. 45, No. 9, pp. 2029-2050.
  • 5. BALAJI C.M., GURUMURTHY A., KODALI R.: Selection of a machine tool for FMS using ELECTRE III – a case study. Automation Science and Engineering (2009), pp. 171-176.
  • 6. CHAN F.T.S., SWARNKAR R.: Ant colony optimization approach to a fuzzy goal programming model for a machine tool selection and operation problem in an FMS, Robotics and Computer-Integrated Manufacturing (2006), Vol. 22, pp. 353-362.
  • 7. CIMREN E., CATAY B., BUDAK E.: Development of a machine tool selection system using AHP, Intelligent Journal of Advances Technology (2007), Vol. 35, pp. 363-376.
  • 8. DAGDEVIREN M.: Decision making in equipment selection: an integrated approach with AHP and PROMETHEE, Journal of Intelligent Manufacturing (2008), Vol. 19, pp. 397-406.
  • 9. GOLA A., ŚWIĆ A., Brief Preliminary Design for a Method of FMS Machine Tools Subsystem Selection, PAMM (2010) Vol. 9, Issue 1, pp. 663-664. 10. GOLA A., ŚWIĆ A., Computer Aided FMS Machine Tools Subsystem Selection – Conception of Methodology, [w:] Z.Banaszak, J.Matuszek, Applied Computer Science. Supporting Enterprise Management Processes (2009), Vol. 5, No 1, Wyd. ATH, Bielsko-Biała, s. 27-39.
  • 11. HONCZARENKO J., Słaby I.: Metodyka doboru obrabiarek skrawajacych, Mechanik, Nr 3/2009, s. 166-173.
  • 12. LIN Z.C., YANG C.B.: Evaluation of machine selection by the AHP method, Journal of Materials Processing Technology (1994), Vol. 57, pp. 253-258.
  • 13. MISHRA S., PRAKASH, TIVARI M.K, LASHKARI R.S.: A fuzzy goal-programming model for machine tool selection and operation allocation problem in FMS: A quick converging simulated annealing-based approach, International Journal of Production Research (2006), Vol. 44. No. 1, pp. 43-76.
  • 14. MONTUSIEWICZ J., Ewolucyjna analiza wielokryterialna w zagadnieniach technicznych, Prace IPPT Polskiej Akademii Nauk, Warszawa 2004.
  • 15. MONTUSIEWICZ J.: Komputerowe wspomaganie decyzji przy użyciu Ewolucyjnego Systemu Analizy Wielokryterialnej, Przegląd Mechaniczny nr 5’07, Suplement, s. 107-110.
  • 16. ONUT S., KARA S.S., EFENDIGIL T.: A hybrid fuzzy MCDM approach to machine tool selection, Journal of Intelligent Manufacturing (2008), Vol. 19, pp. 443-453.
  • 17. PRIMOSE P.L., LEONARD R., Selecting Technology for Investment in Flexible Manufacturing, International Journal of Flexible Manufacturing Systems (1991), Vol. 4, pp. 51-77.
  • 18. RAO R.V., PARNICHKUN M.: Flexible manufacturing system selection using acombinatorial mathematics-based decision-making method, International Journal of Production Research, Vol. 47, Issue 24, pp. 6981-6998.
  • 19. ŚWIĆ A., GOLA A., Elements of Design of Production Systems – Methodology of Machine Tool Selection in Casing-Class FMS, Management and Production Engineering Review (2010), Vol. 1, No. 2, pp. 73-81.
  • 20. TABUCANON M.T., BATANOV D.N., VERMA D.K.: Intelligent Decision Support System (DSS) for the selection process of alternative machines for Flexible Manufacturing Systems (FMS), Computers in Industry (1994), Vol. 25, pp. 131-143.
  • 21. TOLIO T. (red.): Design of Flexible Production Systems. Methodologies and Tools, Springer-Verlag, Berlin Heidelberg 2009.
  • 22. WANG T.Y., SHAW C.F., CHEN Y.L.: Machine selection in flexible manufacturing cell: A fuzzy multiple attribute decision making approach, International Journal of Production Research (2000), Vol. 30, pp. 2079-2097.
  • 23. YOURDAKUL M.: AHP as a strategic decision making tool to justify machine tool selection, Journal of Materials Processing Technology (2004), Vol. 146, pp. 365-376.
  • 24. ZAWADZKA L., Modele optymalizacji wielokryterialnej. Przykłady aplikacji, [w:] L. Zawadzka, Inżynieria systemów zarz+dzania, Wyd. Politechniki Gdańskiej, Gdańsk 2002.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b0111b9e-a534-44cf-9de4-ba6d95ffe064
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