Papers
4
Total Citations
72
H-Index
3
About
Dr. BB Biswal is a leading researcher in robotic assembly and manufacturing automation, with a focus on optimizing complex industrial processes. His work centers on assembly sequence planning, trajectory optimization, and robotic grasping—critical areas for enhancing efficiency in modern manufacturing. Dr. Biswal’s major contributions include developing novel algorithms to solve multi-objective optimization problems in assembly, such as using stability graphs for stable assembly subset identification and applying metaheuristic methods like the Teaching-Learning-Based Optimization (TLBO) algorithm for time-jerk trajectory planning of welding robots. His most cited paper, “Optimal robotic assembly sequence planning using stability graph through stable assembly subset identification” (2019), has garnered 37 citations, reflecting its impact on reducing computational complexity in assembly sequencing. He has also advanced robotic grasping quality through hybrid algorithms like the Nelder-Mead Bat Algorithm. With a total of over 70 citations across his key works, Dr. Biswal’s research provides practical solutions for high-productivity, low-cost manufacturing, making him a notable figure in the field of industrial robotics and optimization.
Research Focus
Key Achievements
Top Papers
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- 3Robotic Optimal Assembly Sequence Using Improved Cuckoo Search Algorithm6 citations · 2018
- 4