Max Robotics — Global Service Robot Directory + US Certification

About

Nitin Kumar Sahu is a leading researcher in advanced manufacturing and decision science, specializing in multi-criteria decision-making (MCDM) for industrial equipment selection. His work focuses on developing robust evaluation models that integrate grey system theory, cluster analysis, and weighted aggregation operators to solve complex manufacturing challenges. Sahu’s most influential paper, "Robot selection based on grey‐MULTIMOORA approach" (2013), with 65 citations, provides a pioneering decision-support framework that couples grey set theory with the MULTIMOORA method, enabling industries to objectively assess and select industrial robots under uncertainty. He further advanced this field with his 2020 study on advanced manufacturing machine tool evaluation, which leverages grey relational analysis and knowledge-based clustering to optimize machine selection under objective-grey information—a contribution cited 21 times. His 2018 work on cluster-based robot appraisement (11 citations) and 2017 analysis of logistic handling system economic values (4 citations) extend his expertise to logistic robots and material handling systems, offering practical tools for cost-effective production. Sahu’s research bridges theoretical MCDM advancements with real-world manufacturing needs, empowering industries to enhance productivity and quality through informed equipment choices.