Research Article
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Year 2020, Volume: 18 Issue: 2, 53 - 62, 17.10.2020

Abstract

İşleme merkezlerine ait kataloglarda verilen kriterler değerlerinin doğru olup olmadığının belirsizliği, belirlenmelerinin hangi koşullarda gerçekleştiği ve birbirine yakın olması işlem merkezlerinin seçimine yönelik yeni yaklaşımların geliştirilmesini gerekli kılmaktadır. Bu makalede, işleme merkezlerine yönelik detaylı bir literatür ve katalog taramasının ardından işleme merkezlerinde kullanılan parçalar ve tipleri ve talaşlı işleme performansına etkileri belirlenmiştir. Belirlenen etkilerin seviyesini derecelendiren hiyerarşik bir yapıya oturtulması ile işleme merkezleri arasında bir seçim modeli geliştirilmiştir. Geliştirilen model literatürde mevcut direkt performansa dayalı seçim modellerine göre daha yoğun bir çalışma gerektirmesine rağmen sonuçları performansı ortaya çıkan yapıyı ve bileşenlerini esas aldığı için daha doğru seçim kararları verilmesini sağlayacaktır.

References

  • 1. İç, Y.T., Yurdakul, M., Eraslan, E. Development of a Component Based Machining Center Selection Model using AHP. International Journal of Production Research. 50(22),(2012), 6489–6498.
  • 2. İç, Y.T., Yurdakul, M. A Decision Support System for Selection of Machining Centers. Journal of the Faculty of Engineering and Architecture of Gazi University, 23(1),(2008), 85-95.
  • 3. Lin, Z-C., Yang C-B. Evaluation of machine selection by the AHP method. J Mater Proc Technol 57(1996)253–258.
  • 4. Çimren E, Budak E, Çatay B. Development of a machine tool selection system using analytic hierarchy process. In: Teti R (ed.), Proc of the 4th CIRP International Seminar on Intelligent Computation in Munufacturing Engineering, Sorrento, Italy, pp 193–198 (2004).
  • 5. Oeltjenbruns H., Kolarik W.J., Schnadt-Kirschner R. Strategic planning in manufacturing systems- AHP application to an equipment replacement decision. Int J Prod Econ 38(1995)189–197.
  • 6. 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).Comput Ind 25(1994)131–143.
  • 7. Yurdakul M. AHP as a strategic decision-making tool to justify machine tool selection. J Mater Proc Tech 146 (2004) 365–376
  • 8. Sun S. Assessing computer numerical control machines using data envelopment analysis. Int J Prod Res 40(9), (2002) 2011–2039
  • 9. Wang T.Y., Shaw C-F., Chen Y-L. Machine selection in flexible manufacturing cell: a fuzzy multiple attribute decision making approach. Int J Prod Res 38(9),(2000)2079–2097.
  • 10. Yurdakul, M., İç, Y.T. Analysis of the benefit generated by using fuzzy numbers in a TOPSIS model developed for machine tool selection problems. Journal of Materials Processing Technology, 209(1), (2009) 310–317.
  • 11. Yurdakul, M., İç, Y.T. Application of correlation test to criteria selection for multi criteria decision making (MCDM) models. International Journal of Advanced Manufacturing Technology, 40(3-4), (2009), 403–412.
  • 12. İç, Y.T., Yurdakul, M. Development of a decision support system for machining center selection”,Expert Systems With Applications, 36(2), (2009) 3505–3513.
  • 13. Arslan M.C., Catay B., Budak E. Decision support system for machine tool selection. In: Baykasoglu A, Dereli T (eds.) Proc ICRM–2002, 2nd International Conference on ResponsiveManufacturing, University of Gaziantep, Turkey, pp 752–757,(2002).
  • 14. Atmani, A. Lashkari, R.S., A model of machine-tool selection and operation allocation in Flexible Manufacturing System. International Journal of Production Research, 36(5), (1998)1339-1349.
  • 15. Gerrard, W. Selection Procedures Adopted by Industry for Introducing New Machine Tools. Advances in Manufacturing Technology III, Proc. Fourth Natl. Conf. on Production Research, Kogan Page, London, (1988), 525- 536.
  • 16. Haddock, J. and Hartshorn, T. A., “A Decision Support System for Specific Machine Selection”, Computers and Industrial Engineering 16(2), (1989), 277-286.
  • 17. İşleme merkezi üreten çeşitli firmaların internet siteleri ile www.mmsonline.com sitesi.
  • 18. Kalpakjian, S., and Schmid, S.R., Manufacturing Engineering and Technology, Prentice-Hall, Inc., Fourth Edition., Upper Saddle River, NJ (2001).
  • 19. Tlusty, G., Manufacturing Processes and Equipment, Chapter 7-10, Printice Hall, USA(2000).
  • 20. Altıntaş, Y., Manufacturing Automation:Metal Cutting Mechanics, Machine Tool Vibrations, and CNC Design, Cambridge University Press, Cambridge, UK (2000).
  • 21. İç, Y.T., Yıldırım, S., “MOORA-Based Taguchi Optimisation for Improving Product or Process Quality”, International Journal of Production Research, Cilt 51, No. 11, (2013) 3321-3341. 22. Brauers, W.K.M., “Multi-Objective Seaport Planning by MOORA decision Making”, Ann Oper Res, Cilt 206, (2013) 39–58.

İşleme Merkezlerinin Yapısal Bileşenlerini Kullanan Bir Seçim Modelinin Geliştirilmesi

Year 2020, Volume: 18 Issue: 2, 53 - 62, 17.10.2020

Abstract

İşleme merkezlerine ait kataloglarda verilen kriterler değerlerinin doğru olup olmadığının belirsizliği, belirlenmelerinin hangi koşullarda gerçekleştiği ve birbirine yakın olması işlem merkezlerinin seçimine yönelik yeni yaklaşımların geliştirilmesini gerekli kılmaktadır. Bu makalede, işleme merkezlerine yönelik detaylı bir literatür ve katalog taramasının ardından işleme merkezlerinde kullanılan parçalar ve tipleri ve talaşlı işleme performansına etkileri belirlenmiştir. Belirlenen etkilerin seviyesini derecelendiren hiyerarşik bir yapıya oturtulması ile işleme merkezleri arasında bir seçim modeli geliştirilmiştir. Geliştirilen model literatürde mevcut direkt performansa dayalı seçim modellerine göre daha yoğun bir çalışma gerektirmesine rağmen sonuçları performansı ortaya çıkan yapıyı ve bileşenlerini esas aldığı için daha doğru seçim kararları verilmesini sağlayacaktır.

References

  • 1. İç, Y.T., Yurdakul, M., Eraslan, E. Development of a Component Based Machining Center Selection Model using AHP. International Journal of Production Research. 50(22),(2012), 6489–6498.
  • 2. İç, Y.T., Yurdakul, M. A Decision Support System for Selection of Machining Centers. Journal of the Faculty of Engineering and Architecture of Gazi University, 23(1),(2008), 85-95.
  • 3. Lin, Z-C., Yang C-B. Evaluation of machine selection by the AHP method. J Mater Proc Technol 57(1996)253–258.
  • 4. Çimren E, Budak E, Çatay B. Development of a machine tool selection system using analytic hierarchy process. In: Teti R (ed.), Proc of the 4th CIRP International Seminar on Intelligent Computation in Munufacturing Engineering, Sorrento, Italy, pp 193–198 (2004).
  • 5. Oeltjenbruns H., Kolarik W.J., Schnadt-Kirschner R. Strategic planning in manufacturing systems- AHP application to an equipment replacement decision. Int J Prod Econ 38(1995)189–197.
  • 6. 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).Comput Ind 25(1994)131–143.
  • 7. Yurdakul M. AHP as a strategic decision-making tool to justify machine tool selection. J Mater Proc Tech 146 (2004) 365–376
  • 8. Sun S. Assessing computer numerical control machines using data envelopment analysis. Int J Prod Res 40(9), (2002) 2011–2039
  • 9. Wang T.Y., Shaw C-F., Chen Y-L. Machine selection in flexible manufacturing cell: a fuzzy multiple attribute decision making approach. Int J Prod Res 38(9),(2000)2079–2097.
  • 10. Yurdakul, M., İç, Y.T. Analysis of the benefit generated by using fuzzy numbers in a TOPSIS model developed for machine tool selection problems. Journal of Materials Processing Technology, 209(1), (2009) 310–317.
  • 11. Yurdakul, M., İç, Y.T. Application of correlation test to criteria selection for multi criteria decision making (MCDM) models. International Journal of Advanced Manufacturing Technology, 40(3-4), (2009), 403–412.
  • 12. İç, Y.T., Yurdakul, M. Development of a decision support system for machining center selection”,Expert Systems With Applications, 36(2), (2009) 3505–3513.
  • 13. Arslan M.C., Catay B., Budak E. Decision support system for machine tool selection. In: Baykasoglu A, Dereli T (eds.) Proc ICRM–2002, 2nd International Conference on ResponsiveManufacturing, University of Gaziantep, Turkey, pp 752–757,(2002).
  • 14. Atmani, A. Lashkari, R.S., A model of machine-tool selection and operation allocation in Flexible Manufacturing System. International Journal of Production Research, 36(5), (1998)1339-1349.
  • 15. Gerrard, W. Selection Procedures Adopted by Industry for Introducing New Machine Tools. Advances in Manufacturing Technology III, Proc. Fourth Natl. Conf. on Production Research, Kogan Page, London, (1988), 525- 536.
  • 16. Haddock, J. and Hartshorn, T. A., “A Decision Support System for Specific Machine Selection”, Computers and Industrial Engineering 16(2), (1989), 277-286.
  • 17. İşleme merkezi üreten çeşitli firmaların internet siteleri ile www.mmsonline.com sitesi.
  • 18. Kalpakjian, S., and Schmid, S.R., Manufacturing Engineering and Technology, Prentice-Hall, Inc., Fourth Edition., Upper Saddle River, NJ (2001).
  • 19. Tlusty, G., Manufacturing Processes and Equipment, Chapter 7-10, Printice Hall, USA(2000).
  • 20. Altıntaş, Y., Manufacturing Automation:Metal Cutting Mechanics, Machine Tool Vibrations, and CNC Design, Cambridge University Press, Cambridge, UK (2000).
  • 21. İç, Y.T., Yıldırım, S., “MOORA-Based Taguchi Optimisation for Improving Product or Process Quality”, International Journal of Production Research, Cilt 51, No. 11, (2013) 3321-3341. 22. Brauers, W.K.M., “Multi-Objective Seaport Planning by MOORA decision Making”, Ann Oper Res, Cilt 206, (2013) 39–58.
There are 21 citations in total.

Details

Primary Language Turkish
Subjects Mechanical Engineering
Journal Section Araştırma, Geliştirme ve Uygulama Makaleleri
Authors

Yusuf Tansel İç 0000-0001-9274-7467

Mustafa Yurdakul 0000-0002-1562-5738

Publication Date October 17, 2020
Submission Date July 7, 2020
Published in Issue Year 2020 Volume: 18 Issue: 2

Cite

Vancouver İç YT, Yurdakul M. İşleme Merkezlerinin Yapısal Bileşenlerini Kullanan Bir Seçim Modelinin Geliştirilmesi. MATİM. 2020;18(2):53-62.