Presenting a Model for Robot evaluation and Ranking by Grey MuLTIMOORA | ||
| Journal of Engineering Management and Soft Computing | ||
| مقاله 7، دوره 7، شماره 1 - شماره پیاپی 12، مهر 2021، صفحه 147-170 اصل مقاله (763.4 K) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.22091/jemsc.2016.763 | ||
| نویسندگان | ||
| Ahmadreza Ghasemi* 1؛ Meysam Shahbazi2؛ Hamidreza Aghashahi1 | ||
| 1Assistant Prof., Faculty of Management and Accounting, Farabi College, University of Tehran, Qom, Iran. | ||
| 2MSc. Student in Industrial Management , Faculty of Management and Accounting, Farabi College, University of Tehran, | ||
| چکیده | ||
| Regarding Proliferation of Robot brands and models and contributing criteria in evaluation of them, using a powerful model to Robots evaluation and ranking is very important. This research try to find key contributing factor in Robots evaluation and present an efficient model to Robot selection. To achieve mentioned goal, in the first step main robot performance criteria identified by experts. In addition 5 popular Robot in Irankhodro automotive industry were identified. Next criteria weights were calculated by Grey Entropy method. Sellers training, quality of services, are the main important criteria’s and v.s precision and degree of freedom are least important criteria. In addition by synthesizing three Grey MOORA approaches, KOKA, ABB, Motoman, Fanuc and Hyundai are the result ranking. | ||
| کلیدواژهها | ||
| Grey MOORA؛ Industrial Robot؛ MULTIMOORA | ||
| عنوان مقاله [English] | ||
| -ارائه مدلی برای اولویتبندی و گزینش رباتها در خطوط تولیدی پیوسته با بهرهگیری از روش مالتی مورای خاکستری | ||
| نویسندگان [English] | ||
| احمدرضا قاسمی1؛ میثم شهبازی2؛ حمیدرضا آقاشاهی1 | ||
| 1استادیار گروه صنعت و فناوری پردیس فارابی دانشگاه تهران، قم، ایران. | ||
| 2کارشناس ارشد گروه صنعت و فناوری پردیس فارابی دانشگاه تهران، قم، ایران. | ||
| چکیده [English] | ||
| تعدد مدلها و برندهای ربات، تکثر شاخصهایی که برای انتخاب یک ربات مطرح است و نیز هزینه بسیار بالای انتخاب ربات نامناسب، توجیه مناسبی برای بهرهگیری از یک مدل تصمیمگیری قوی بمنظور انتخاب و ارزیابی رباتها است. پژوهش حاضر با هدف شناسایی شاخصهای کلیدی و با اهمیت در گزینش رباتها و همچنین ارائه یک مدل تصمیمگیری کارآمد برای انتخاب ربات انجام شده است. بدینمنظور، در گام نخست شاخصهای مؤثر در انتخاب ربات با استفاده از نظر خبرگان شناسایی شده و همچنین 5 ربات پرکاربرد در شرکت خودروسازی «ایرانخودرو» بعنوان گزینههای اولویتبندی مشخص شدند. با بررسی نتایج پرسشنامهها، وزن هر شاخص با روش آنتروپی خاکستری محاسبه شد و شاخص «آموزش فروشنده» و «کیفیت خدمات فروشندگان» بعنوان مهمترین شاخصها در انتخاب ربات صنعتی و شاخص «درجه آزادی» و «دقت» کماهمیتترین شاخصها در مسئله انتخاب ربات شناخته شدند. همچنین با استفاده از تجمیع نتایج هر سه رویکرد روش مورا ربات «کوکا» اولویت اول و ربات «ای بی بی» و «موتومن» و «فانوک» اولویتهای دوم تا چهارم و ربات «هیوندای» در اولویت آخر قرار گرفت. | ||
| کلیدواژهها [English] | ||
| اولویتبندی, ربات صنعتی, مورای خاکستری, مالتی مورا | ||
| مراجع | ||
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Attri, R., & Grover, S. (2014). Decision making over the production system life cycle: MOORA method. International Journal of System Assurance Engineering and Management, 5(3), 320-328. Balezentis, A., Balezentis, T., & Brauers, W. K. (2012). MULTIMOORA-FG: A multi-objective decision making method for linguistic reasoning with an application to personnel selection. Informatica, 23(2), 173-190. Bhattacharyya, O., & Chakraborty, S. (2015). Q-analysis in Materials Selection. Decision Science Letters, 4(1), 51-62. Brauers, W. K. M., & Zavadskas, E. K. (2012). Robustness of MULTIMOORA: a method for multi-objective optimization. Informatica, 23(1), 1-25. Brauers, W. K. M., Zavadskas, E. K., Turskis, Z., & Vilutiene, T. (2008). Multi‐objective contractor's ranking by applying the Moora method. Journal of Business Economics and Management, 9(4), 245-255. Chakraborty, S. (2011). Applications of the MOORA method for decision making in manufacturing environment. The International Journal of Advanced Manufacturing Technology, 54(9-12), 1155-1166. Chatterjee, P., Athawale, V. M., & Chakraborty, S. (2010). Selection of industrial robots using compromise ranking and outranking methods. 1Robotics and Computer-Integrated Manufacturing, 26(5), 483-489. Das Adhikary, D., Kumar Bose, G., Bose, D., & Mitra, S. (2014). Multi criteria FMECA for coal-fired thermal power plants using COPRAS-G. International Journal of Quality & Reliability Management, 31(5), 601-614. Datta, S., Sahu, N., & Mahapatra, S. (2013). Robot selection based on grey-MULTIMOORA approach. Grey Systems: Theory and Application, 3(2), 201-232. Farzamnia, E., & Babolghani, M. B. (2014). GROUP DECISION-MAKING PROCESS FOR SUPPLIER SELECTION USING MULTIMOORA TECHNIQUE UNDER FUZZY ENVIRONMENT. Kuwait Chapter of the Arabian Journal of Business and Management Review, 3(11A), 203. Gadakh, V. S. (2010). Application of MOORA method for parametric optimization of milling process. International Journal of Applied Engineering Research, 1(4), 743. Gorener, A., Dinçer, H., & Hacioglu, U. (2013). Application of Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) Method for Bank Branch Location Selection. Gorener, A., Dinçer, H., & Hacioglu, U. (2013). Application of Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) Method for Bank Branch Location Selection. Jafarnezhad, A. Ghasemi, A. 2010. Technology Acquisition Strategy in Science and Technology Park of University of Tehran, Management Information Technology, 1, 34-51. . (In Persian). Jolly, K. G., Kumar, R. S., & Vijayakumar, R. (2010). Intelligent task planning and action selection of a mobile robot in a multi-agent system through a fuzzy neural network approach. Engineering Applications of Artificial Intelligence, 23(6), 923-933. Kalibatas, D., & Turskis, Z. (2015). Multicriteria evaluation of inner climate by using MOORA method. Information technology and control, 37(1). Karande, P., & Chakraborty, S. (2012). A Fuzzy-MOORA approach for ERP system selection. Decision Science Letters, 1(1), 11-21. Karande, P., & Chakraborty, S. (2012). Application of multi-objective optimization on the basis of ratio analysis (MOORA) method for materials selection. Materials & Design, 37, 317-324. Kildiene, S. (2013). Assessment of opportunities for construction enterprises in European Union member states using the MULTIMOORA method. Procedia Engineering, 57, 557-564. Kim, G., Jong, Y., Liu, S., & Shong, C. R. (2012). Hybrid Grey Interval Relation Decision-Making in Artistic Talent Evaluation of Player. arXiv preprint arXiv:1207.3855. Kumar Sahu, A., Datta, S., & Sankar Mahapatra, S. (2014). Supply chain performance benchmarking using grey-MOORA approach: An empirical research. Grey Systems: Theory and Application, 4(1), 24-55. Kumar, R., & Garg, R. K. (2010). Optimal selection of robots by using distance based approach method. Robotics and Computer-Integrated Manufacturing, 26(5), 500-506. Mehregan, M. 2007. Multi Objective Decision Making, Collegiate Center Pub. Tehran. (In Persian). Mohamadi, A. Molaei, N. (2010). Application of Multi Criteria Decision Making in Companies’ Performance Assessment, Industerial Management Journal, 1, 34-51. (In Persian). Momeni, M. 2010. New issuse in operation research, Faculty of Management of University of Tehran Pub. Tehran (In Persian). Parameshwaran, R., Kumar, S. P., & Saravanakumar, K. (2015). An integrated fuzzy MCDM based approach for robot selection considering objective and subjective criteria. Applied Soft Computing, 26, 31-41 Rao, R. V., & Padmanabhan, K. K. (2006). Selection, identification and comparison of industrial robots using digraph and matrix methods. Robotics and Computer-Integrated Manufacturing, 22(4), 373-383. Rashid, T., Beg, I., & Husnine, S. M. (2014). Robot selection by using generalized interval-valued fuzzy numbers with TOPSIS. Applied Soft Computing, 21, 462-468. Sarucan, A., Baysal, M. E., Kahraman, C., & Engin, O. (2011). A hierarchy grey relational analysis for selecting the renewable electricity generation technologies. In Proceedings of the world congress on engineering, 2, 1149-1154. Stankevičienė, J., & Sviderskė, T. (2012). Country risk assessment based on MULTIMOORA. In 7th International Scientific Conference “Business and Management 2012” May 10-11, 2012, Vilnius, Lithuania. Stanujkic, D., Magdalinovic, N., Stojanovic, S., & Jovanovic, R. (2012). Extension of ratio system part of MOORA method for solving decision-making problems with interval data. Informatica, 23(1), 141-154. Taghifard, M. Malek,A. 2010. Using Grey Decision Making method to Key Performance Criteria Ranking and Strategic Planning improvement, Industerial Management Studies, 22, 135-166. . (In Persian). Turskis, Z., & Zavadskas, E. K. (2010). A novel method for multiple criteria analysis: grey additive ratio assessment (ARAS-G) method. Informatica, 21(4), 597-610. Yuzhong, Y., & Liyun, W. (2007, September). Grey entropy method for green supplier selection. In Wireless Communications, Networking and Mobile Computing, 2007. WiCom 2007. International Conference on (pp. 4682-4685). IEEE. Zhang, X., & Liu, P. (2010). Method for multiple attribute decision-making under risk with interval numbers. International Journal of Fuzzy Systems, 12(3), 237-242. | ||
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