Priyank Gupta
Papers
1
Total Citations
5
H-Index
1
About
Priyank Gupta is a researcher whose work sits at the intersection of industrial engineering, decision science, and advanced manufacturing. His primary research focuses on multi-criteria decision-making (MCDM) models for optimizing complex industrial processes, particularly in the selection and evaluation of automation technologies. His most-cited paper, "Selection of industrial arc welding robot using integrated PIPRECIA-TOPSIS model" (2023), introduces a novel hybrid framework that combines the PIPRECIA method with TOPSIS to systematically rank robotic systems based on technical, economic, and operational criteria. This contribution is significant for manufacturing firms seeking to automate welding processes with high precision and cost-efficiency. With 5 citations to this work, Gupta’s research is gaining traction among engineers and operations researchers. His work stands out for its practical applicability—bridging theoretical MCDM models with real-world industrial challenges. By providing a structured, transparent approach to robot selection, Gupta helps reduce subjectivity in procurement decisions, ultimately supporting smarter, data-driven automation in smart factories.
Research Focus
Key Achievements
Top Papers
- 1