Gaurav Sapkota

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About

Gaurav Sapkota is a rising figure in the field of multi-criteria decision-making (MCDM) and industrial robotics optimization. His research primarily focuses on applying advanced mathematical frameworks to solve complex engineering selection problems, particularly in the automation and manufacturing sectors. Sapkota’s most notable contribution is the application of the novel MEREC (Method based on the Removal Effects of Criteria) technique to the multi-criteria selection of optimal spray-painting robots. This work, published in 2022 and garnering 80 citations, addresses the critical challenge of choosing the most efficient robotic model for industrial coating tasks, considering factors like cost, precision, and energy consumption. By demonstrating how MEREC can streamline decision-making for practitioners, his research has provided a replicable model for equipment selection in smart factories. Beyond this flagship study, Sapkota’s work contributes to the broader discourse on integrating MCDM tools with Industry 4.0 technologies. His findings are particularly valuable for engineers and researchers seeking objective, data-driven methods to enhance automation efficiency, making him a key voice in the optimization of robotic systems for real-world industrial applications.