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About

Siba Sankar Mahapatra is a researcher specializing in multi-criteria decision making (MCDM) and intelligent selection systems, with a particular focus on industrial robotics and manufacturing optimization. His work bridges operations research and applied engineering, developing sophisticated mathematical frameworks to help industries navigate complex decision-making challenges. Mahapatra's most significant contribution lies in advancing MCDM methodologies for industrial robot selection — a critical challenge as manufacturers face an increasingly diverse marketplace of robotic solutions. His highly cited 2015 paper on multi-criteria robot selection (71 citations) established robust frameworks for evaluating robots across competing performance attributes. He has consistently pushed boundaries by integrating emerging mathematical tools, including grey numbers, fuzzy set theory, interval-valued trapezoidal fuzzy numbers, and the TODIM and VIKOR methods, into practical decision-support systems that handle both subjective and objective criteria under uncertainty. His extensions of the TODIM framework — incorporating generalised fuzzy numbers and grey number theory — demonstrate a sustained commitment to making decision-making tools more flexible and realistic for real-world industrial environments. Across his body of work, Mahapatra has accumulated over 100 citations, reflecting meaningful influence within the industrial engineering and operations management research communities.