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

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

Keywords:

Robot Selection, MCDM Model CRITIC Model, MABAC Method, VIKOR,

PDF

___

[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