Sehijpal Singh

Papers

Total Citations

200

H-Index

About

Dr. Sehijpal Singh is a distinguished researcher in industrial engineering and decision science, with a specialized focus on multi-criteria decision-making (MCDM) techniques and their application to manufacturing systems. His most impactful work, "Selection of industrial arc welding robot with TOPSIS and Entropy MCDM techniques" (2021), has garnered over 200 citations, establishing him as a leading voice in the integration of mathematical modeling with real-world industrial challenges. Dr. Singh’s major contribution lies in advancing the use of TOPSIS and entropy-based methods to optimize complex selection processes—particularly in robotics and automation—enabling industries to make more efficient, data-driven decisions. His research bridges theoretical rigor and practical utility, offering engineers and managers robust frameworks for technology assessment. Beyond this seminal paper, his work continues to influence fields such as supply chain management, sustainable manufacturing, and quality engineering. Dr. Singh’s achievements reflect a career dedicated to solving pressing industrial problems through innovative, quantitative approaches, making him a valuable resource for students and researchers seeking to understand how MCDM tools can transform operational efficiency and strategic planning in modern manufacturing.