Abstract
This paper introduces a modified fuzzy technique (FUZZY TOPSIS) for the selection of best Industrial robot according to the assigned performance rating. Both conflicting quantitative and qualitative evaluation criteria are considered during the selection process. A collective index is prepared using weighted average method for preparing the ranking of rule base. Triangular and Gaussian membership function is used to describe the weight of each criterion (input parameters) and rating of each alternatives (ranking of robots). From comparison study, it is found that the Gaussian membership function is most effective for closeness measurement as its surface plot shows a good agreement with the output result. This approach confirms that the fuzzy membership function is a suitable decision making tool for the Manufacturing decisions with an object lesson in the robot selection process.
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Nayak, S., Pattanayak, S., Choudhury, B.B., Kumar, N. (2020). Selection of Industrial Robot Using Fuzzy Logic Approach. In: Behera, H., Nayak, J., Naik, B., Pelusi, D. (eds) Computational Intelligence in Data Mining. Advances in Intelligent Systems and Computing, vol 990. Springer, Singapore. https://doi.org/10.1007/978-981-13-8676-3_20
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DOI: https://doi.org/10.1007/978-981-13-8676-3_20
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