Year 2017,
Volume: 15 Issue: 2, 92 - 105, 26.09.2018
Yusuf Tansel İç
,
Mustafa Yurdakul
,
Alkın Günyar
Hakan Önel
References
- [1] Durmuşoğlu, Semra., Köker, M. Sefa., "Türkiye'de Endüstriyel Robot Kullanımı", /sayfa/Semra_Durmusoglu-Turkiyede_Endustriyel_Robot_Kullanimi.html , Temmuz 2007.
- [2] Khouja, M., and Offodile, O.F., The industrial robot selection problem: literature review and directions for future research, IIE Transactions, 26(4) (1994)50-61.
- [3] Goh, C.-H., Analytic Hierarchy Process for robot selection, Journal of Manufacturing Systems, 16(1997) 5, 381-386.
- [4] Braglia, M. and Petroni, A., Evaluating and selecting investments in industrial robots, International Journal of Production Research, 37(1999) 18, 4157- 4178.
- [5] Parkan, C., and Wu., M-L., Decision -making and performance measurement models with application to robot selection, Computers and Industrial Engineering, 36(1999) 503-523.
- [6] Layek, A.M. and Lars, J.R. Algorithm based decision support system for the concerted selection of equipment in machining/assembly cells, International Journal of Production Research, 38 (2000) 2, 323- 339.
- [7] Khouja, M., Booth, D. E., Suh, M., and MahaneyJr, J. K. Statistical procedures for task assignment and robot selection in assembly cells, International Journal of Computer Integrated Manufacturing, 13 (2000) 2, 95- 106.
- [8] Chu, T-C., and Lin, Y.-C. A fuzzy topsis method for robot selection, International Journal of Advanced Manufacturing Technology, 21(2003) 284–290.
- [9] Bhangale, P.P., Agrawal, V.P., and Saha, S.K. Attribute based specification, comparison and selection of a robot, Mechanism and Machine Theory, 39(2004) 1345–1366.
- [10] Kapoor V., and Tak, S.S. Fuzzy application to the Analytic Hierarchy Process for robot selection, Fuzzy Optimization And Decision Making, 4(2005) 209–234.
- [11] Rao, R. V., Padmanabhan, K.K. Selection, identification and comparison of industrial robots using digraph and matrix methods, Robotics and Computer-Integrated Manufacturing, 22(2006), 373–383.
- [12] Karsak, E. E. Robot selection using an integrated approach based on quality function deployment and fuzzy regression, International Journal of Production Research, 46 (2008)3, 723–738.
- [13] Chatterjee P., Athawale, V. M. and Chakraborty, S. Selection of industrial robot s using compromise ranking and outranking methods, Robotics and Computer-Integrated Manufacturing, 26(2010), 483–489.
- [14] Koulouriotis, D.E., Ketipi, M.K. A fuzzy digraph method for robot evaluation and selection, Expert Systems with Applications, 38(2011) 11901–11910.
- [15] Devi, K. Extension of VIKOR method in intuitionistic fuzzy environment for robot selection, Expert Systems with Applications, 38(2011) 14163–14168.
- [16] Tao, L., Chen, Y., Liu, X., Wang, X. An integrated multiple criteria decision making model applying axiomatic fuzzy set theory, Applied Mathematical Modelling, 36(2012) 5046–5058.
- [17] Karsak, E. E., Sener, Z., Dursun, M. Robot selection using a fuzzy regression-based decision-making approach. International Journal of Production Research, 50(2012)23, 6826-6834.
- [18] Vahdani, B., Tavakkoli-Moghaddam, R., Mousavi, S. M., Ghodratnama, A. Soft computing based on new interval-valued fuzzy modified multi-criteria decision-making method. Applied Soft Computing, 13(2013) 165–172.
- [19] Ghorabaee, M.K., Developing an MCDM method for robot selection with interval type-2 fuzzy sets, Robotics and Computer-Integrated Manufacturing 37 (2016) 221–232
- [20] Ic Y.T., Yurdakul, M., Dengiz, B., Development of a decision support system for robot selection, Robotics and Computer-Integrated Manufacturing 29 (2013) 142–157.
- [21] Yi-Xi, You, J-X., Zhao, X., Liu, H-C., An integrated linguistic MCDM approach for robot evaluation and selection with incomplete weight information, International Journal of Production Research, 54(2016)18, 5452-5467.
- [22] Kumar, D., Datta, S., Mahapatra, S.S., "Application of TODIM (Tomada de Decisión Inerativa Multicritero) for industrial robot selection", Benchmarking: An International Journal, 23(2016)7, 1818-1833.
- [23] Breaza, R.E., Bologa, O., Racza, S.G., Selecting industrial robots for milling applications using AHP, Procedia Computer Science, 122 (2017) 346–353.
- [24] Agrawal, V.P., Kohli V., and Gupta S., Computer aided robot selection: the multi-attribute decision making approach, International Journal of Production Research, 29(1991)1629-1644.
- [25] Parkan Ç., Ming-Lu W., Decision -making and performance measurement models with application to robot selection, Computers and Industrial Eng., 36(1999)503-523.
- [26] Chen, C.T., Extensions of the TOPSIS for group decision-making under fuzzy environment, Fuzzy Sets and Systems, 114(2000)1-9.
- [27] Tsaur,S., H., Chang T.Y., Yen C.H. The evaluation of airline service quality by fuzzy MCDM, Tourism Management, 23(2002)107-115.
- [28] Jee D.H., Kong K.J., A method for optimal material selection aided with decision making theory, Materials and Design , 21(2000)199-206.
Endüstriyel Robot Seçimi İçin Bir Karar Destek Sistemi
Year 2017,
Volume: 15 Issue: 2, 92 - 105, 26.09.2018
Yusuf Tansel İç
,
Mustafa Yurdakul
,
Alkın Günyar
Hakan Önel
Abstract
Bu çalışmada, endüstriyel robot seçimi için bir karar
destek sistemi oluşturulmuştur. Piyasada bulunan 193 adet robot ele alınarak bu
robotların özelliklerini içeren bir veri tabanı oluşturulmuştur. Visual Basic
Kodlama dili ile oluşturulan karar destek sisteminde önce kullanıcıya
yöneltilen sorular ile istenilen nitelikte robotlar elde edilmeye çalışılmış,
ardından elde edilen bu robotlar arasında, literatürde çok sık kullanılan çok
kriterli karar verme yöntemlerinden biri olan TOPSIS uygulanarak bir sıralama
elde edilmiştir. Böylelikle kullanıcı için en iyi robot seçilmeye
çalışılmıştır. Geliştirilen karar destek sistemi endüstride gerçek hayat robot
seçim problemleri üzerinde denenmiştir.
References
- [1] Durmuşoğlu, Semra., Köker, M. Sefa., "Türkiye'de Endüstriyel Robot Kullanımı", /sayfa/Semra_Durmusoglu-Turkiyede_Endustriyel_Robot_Kullanimi.html , Temmuz 2007.
- [2] Khouja, M., and Offodile, O.F., The industrial robot selection problem: literature review and directions for future research, IIE Transactions, 26(4) (1994)50-61.
- [3] Goh, C.-H., Analytic Hierarchy Process for robot selection, Journal of Manufacturing Systems, 16(1997) 5, 381-386.
- [4] Braglia, M. and Petroni, A., Evaluating and selecting investments in industrial robots, International Journal of Production Research, 37(1999) 18, 4157- 4178.
- [5] Parkan, C., and Wu., M-L., Decision -making and performance measurement models with application to robot selection, Computers and Industrial Engineering, 36(1999) 503-523.
- [6] Layek, A.M. and Lars, J.R. Algorithm based decision support system for the concerted selection of equipment in machining/assembly cells, International Journal of Production Research, 38 (2000) 2, 323- 339.
- [7] Khouja, M., Booth, D. E., Suh, M., and MahaneyJr, J. K. Statistical procedures for task assignment and robot selection in assembly cells, International Journal of Computer Integrated Manufacturing, 13 (2000) 2, 95- 106.
- [8] Chu, T-C., and Lin, Y.-C. A fuzzy topsis method for robot selection, International Journal of Advanced Manufacturing Technology, 21(2003) 284–290.
- [9] Bhangale, P.P., Agrawal, V.P., and Saha, S.K. Attribute based specification, comparison and selection of a robot, Mechanism and Machine Theory, 39(2004) 1345–1366.
- [10] Kapoor V., and Tak, S.S. Fuzzy application to the Analytic Hierarchy Process for robot selection, Fuzzy Optimization And Decision Making, 4(2005) 209–234.
- [11] Rao, R. V., Padmanabhan, K.K. Selection, identification and comparison of industrial robots using digraph and matrix methods, Robotics and Computer-Integrated Manufacturing, 22(2006), 373–383.
- [12] Karsak, E. E. Robot selection using an integrated approach based on quality function deployment and fuzzy regression, International Journal of Production Research, 46 (2008)3, 723–738.
- [13] Chatterjee P., Athawale, V. M. and Chakraborty, S. Selection of industrial robot s using compromise ranking and outranking methods, Robotics and Computer-Integrated Manufacturing, 26(2010), 483–489.
- [14] Koulouriotis, D.E., Ketipi, M.K. A fuzzy digraph method for robot evaluation and selection, Expert Systems with Applications, 38(2011) 11901–11910.
- [15] Devi, K. Extension of VIKOR method in intuitionistic fuzzy environment for robot selection, Expert Systems with Applications, 38(2011) 14163–14168.
- [16] Tao, L., Chen, Y., Liu, X., Wang, X. An integrated multiple criteria decision making model applying axiomatic fuzzy set theory, Applied Mathematical Modelling, 36(2012) 5046–5058.
- [17] Karsak, E. E., Sener, Z., Dursun, M. Robot selection using a fuzzy regression-based decision-making approach. International Journal of Production Research, 50(2012)23, 6826-6834.
- [18] Vahdani, B., Tavakkoli-Moghaddam, R., Mousavi, S. M., Ghodratnama, A. Soft computing based on new interval-valued fuzzy modified multi-criteria decision-making method. Applied Soft Computing, 13(2013) 165–172.
- [19] Ghorabaee, M.K., Developing an MCDM method for robot selection with interval type-2 fuzzy sets, Robotics and Computer-Integrated Manufacturing 37 (2016) 221–232
- [20] Ic Y.T., Yurdakul, M., Dengiz, B., Development of a decision support system for robot selection, Robotics and Computer-Integrated Manufacturing 29 (2013) 142–157.
- [21] Yi-Xi, You, J-X., Zhao, X., Liu, H-C., An integrated linguistic MCDM approach for robot evaluation and selection with incomplete weight information, International Journal of Production Research, 54(2016)18, 5452-5467.
- [22] Kumar, D., Datta, S., Mahapatra, S.S., "Application of TODIM (Tomada de Decisión Inerativa Multicritero) for industrial robot selection", Benchmarking: An International Journal, 23(2016)7, 1818-1833.
- [23] Breaza, R.E., Bologa, O., Racza, S.G., Selecting industrial robots for milling applications using AHP, Procedia Computer Science, 122 (2017) 346–353.
- [24] Agrawal, V.P., Kohli V., and Gupta S., Computer aided robot selection: the multi-attribute decision making approach, International Journal of Production Research, 29(1991)1629-1644.
- [25] Parkan Ç., Ming-Lu W., Decision -making and performance measurement models with application to robot selection, Computers and Industrial Eng., 36(1999)503-523.
- [26] Chen, C.T., Extensions of the TOPSIS for group decision-making under fuzzy environment, Fuzzy Sets and Systems, 114(2000)1-9.
- [27] Tsaur,S., H., Chang T.Y., Yen C.H. The evaluation of airline service quality by fuzzy MCDM, Tourism Management, 23(2002)107-115.
- [28] Jee D.H., Kong K.J., A method for optimal material selection aided with decision making theory, Materials and Design , 21(2000)199-206.