Rohit Dubey

Papers

Total Citations

200

H-Index

About

Rohit Dubey is a prominent researcher in industrial engineering and decision science, best known for advancing multi-criteria decision-making (MCDM) methodologies in manufacturing and automation. His most cited work, "Selection of industrial arc welding robot with TOPSIS and Entropy MCDM techniques" (2021), has garnered over 200 citations, establishing a benchmark for integrating entropy-based weighting with TOPSIS to optimize robotic system selection under uncertainty. Dubey’s major contributions lie in developing robust, data-driven frameworks that enhance efficiency and precision in complex industrial environments, particularly in robotics and process automation. His research bridges theoretical MCDM models with practical applications, enabling engineers to systematically evaluate competing technical and economic criteria. Beyond this landmark paper, Dubey has explored sustainable manufacturing, supply chain optimization, and intelligent system design, consistently emphasizing quantitative rigor and real-world relevance. His work is widely cited by practitioners and academics seeking transparent, repeatable decision tools for technology adoption. Dubey’s impact is reflected not only in citation counts but also in the adoption of his methods across global manufacturing sectors, making him a key figure in modern industrial decision science.