Bijan Sarkar
Papers
2
Total Citations
9
H-Index
2
About
Bijan Sarkar is a researcher whose work sits at the intersection of manufacturing engineering, decision science, and intelligent automation. His scholarly contributions center on the development and application of multi-criteria decision-making (MCDM) methodologies, particularly in the context of industrial robot selection — a notoriously complex challenge in modern manufacturing environments. Sarkar has been instrumental in advancing analytical frameworks that help decision-makers navigate the growing complexity introduced by rapidly evolving robotic technologies and competing performance criteria. Among his most recognized contributions is his 2012 work proposing a novel multiplicative model for multi-criteria analysis tailored to robot selection, which acknowledged the compounding difficulties manufacturers face as robotic systems incorporate increasingly sophisticated features. Building on this foundation, his 2020 research introduced a De Novo approach to robot selection for material handling, further refining the analytical toolkit available to industrial engineers and operations researchers. While his citation counts remain modest — with his top works garnering between 4 and 5 citations — his research addresses a genuinely practical and pressing concern in manufacturing optimization. His work offers valuable methodological guidance for students and practitioners seeking rigorous, systematic approaches to automation decision-making in competitive industrial settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2