A HYBRID MULTI-CRITERIA DECISION MAKING METHOD FOR ROBOT SELECTION IN FLEXIBLE MANUFACTURING SYSTEM

Advancement of the manufacturing system is governed by robots which improve the productquality and decrease market availability period. Different robots have been used for the pick and dropthe operation of components in flexible manufacturing systems (FMS). Each robot have their advantagesand disadvantages therefore, selection of the most suitable robot is significantly important. The selectionof robots based on various criteria is a multi-decision making problem (MCDM). In this study sevenrobots (R1, R2, R3, R4, R5, R6, R7) are ranked using the proposed approach on the basis of five criteriaviz. load capacity (LC), memory capacity (MC), manipulator reach (MR), maximum tip speed (MTS), andrepeatability (RE) by employing hybrid Criteria Importance Through Inter criteria Correlation(CRITIC) and Multi-attributive border approximation area comparison (MABAC) methods. Weights ofcriteria were obtained using correlation coefficient and standard deviation method whereas, the rankingof alternative was done using hybrid CRITIC and MABAC method. As a result of this study, robot R3acquired the first rank whereas, R1 occupied the last rank which showed that R3 is the most suitablerobot for the pick and place operation in FMS. Besides, Ranking comparison was also done with otherMCDM methods.

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[1] R. Kumar and R. K. Garg, "Optimal selection of robots by using distance-based approach method," Robotics and Computer-Integrated Manufacturing, vol. 26, no. 5, pp. 500–506, Oct. 2010, doi: 10.1016/j.rcim.2010.03.012.
[2] R. V. Rao, B. K. Patel, and M. Parnichkun, "Industrial robot selection using a novel decision-making method considering objective and subjective preferences," Robotics and Autonomous Systems, vol. 59, no. 6, pp. 367–375, Jun. 2011, doi: 10.1016/j.robot.2011.01.005.
[3] D. E. Koulouriotis and M. K. Ketipi, "Robot evaluation and selection Part A: an integrated review and annotated taxonomy," Int J Adv Manuf Technol, vol. 71, no. 5–8, pp. 1371–1394, Mar. 2014, doi: 10.1007/s00170-013-5525-5.
[4] M. K. Ketipi, D. E. Koulouriotis, and E. G. Karakasis, "Robot evaluation and selection Part B: a comparative analysis," Int J Adv Manuf Technol, vol. 71, no. 5–8, pp. 1395–1417, Mar. 2014, doi: 10.1007/s00170-013-5526-4.
[5] P. P. Bhangale, V. P. Agrawal, and S. K. Saha, "Attribute based specification, comparison and selection of a robot," Mechanism and Machine Theory, vol. 39, no. 12, pp. 1345–1366, Dec. 2004, doi: 10.1016/j.mechmachtheory.2004.05.020.
[6] P. Chatterjee, V. Manikrao Athawale, and S. Chakraborty, "Selection of industrial robots using compromise ranking and outranking methods," Robotics and Computer-Integrated Manufacturing, vol. 26, no. 5, pp. 483–489, Oct. 2010, doi: 10.1016/j.rcim.2010.03.007.
[7] A. Kentli and A. K. Kar, "A satisfaction function and distance measure based multi-criteria robot selection procedure," International Journal of Production Research, vol. 49, no. 19, pp. 5821–5832, Oct. 2011, doi: 10.1080/00207543.2010.530623.
[8] Y. Fu, M. Li, H. Luo, and G. Q. Huang, "Industrial robot selection using stochastic multicriteria acceptability analysis for group decision making," Robotics and Autonomous Systems, vol. 122, p. 103304, Dec. 2019, doi: 10.1016/j.robot.2019.103304.
[9] D. Diakoulaki, G. Mavrotas, and L. Papayannakis, "Determining objective weights in multiple criteria problems: The critic method," Computers & Operations Research, vol. 22, no. 7, pp. 763– 770, Aug. 1995, doi: 10.1016/0305-0548(94)00059-H.
[10] D. I. Božanić, D. S. Pamučar, and S. M. Karović, "Application the MABAC method in support of decision-making on the use of force in a defensive operation," Tehnika, vol. 71, no. 1, pp. 129–136, 2016.
[11] D. Pamučar, Ž. Stević, and E. K. Zavadskas, "Integration of interval rough AHP and interval rough MABAC methods for evaluating university web pages," Applied Soft Computing, vol. 67, pp. 141– 163, 2018.
[12] D. Pamučar and G. Ćirović, "The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC)," Expert systems with applications, vol. 42, no. 6, pp. 3016–3028, 2015.
[13] Wakeel, S., Bingol, S., Bashir, M. N., & Ahmad, S. (2020). Selection of sustainable material for the manufacturing of complex automotive products using a new hybrid Goal Programming Model for Best Worst Method–Proximity Indexed Value method. Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications, 1464420720966347.
[14] Wakeel, S., Ahmad, S., Bingol, S., Bashir, M. N., Paçal, T. C., & Khan, Z. A. (2020, August). Supplier Selection for High-Temperature Die Attach by hybrid Entropy-Range of Value MCDM Technique: A Semiconductor Industry. In 2020 21st International Conference on Electronic Packaging Technology (ICEPT) (pp. 1-5). IEEE