Atul Kumar Sahu
Papers
3
Total Citations
36
H-Index
3
About
Dr. Atul Kumar Sahu is a distinguished researcher in advanced manufacturing and industrial decision-making, with a focus on multi-criteria evaluation models under uncertainty. His work primarily addresses the appraisal of complex manufacturing systems, including advanced machine tools, industrial robots, and logistic handling equipment, using grey relational analysis and cluster-based aggregation approaches. Dr. Sahu’s most cited paper, “Exploitation of the advanced manufacturing machine tool evaluation model under objective-grey information” (2020, 21 citations), introduces a knowledge-based cluster integrated with grey relational analysis to optimize machine selection for cost-effective, high-quality production. His 2018 study on robot appraisement (11 citations) develops a weighted geometric aggregation operator to guide economical robot procurement in logistics. Additionally, his 2017 work on logistic system valuation (4 citations) underscores the critical role of material handling in industrial productivity. Collectively, Dr. Sahu’s contributions provide robust frameworks for engineers and managers navigating the trade-offs between performance, cost, and uncertainty in manufacturing environments. His research is instrumental for students and practitioners seeking systematic, data-driven tools for technology selection and operational efficiency.
Research Focus
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Top Papers
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