Surajit Sharma
Papers
2
Total Citations
21
H-Index
2
About
Surajit Sharma is a leading researcher in the field of robotic assembly automation, with a primary focus on optimizing assembly sequences for efficiency and stability. His work centers on the application of computational intelligence, particularly ant colony optimization (ACO), to solve complex manufacturing challenges. Sharma’s most influential contribution, "Generation of optimized robotic assembly sequence using ant colony optimization" (2008), with 19 citations, pioneered the use of ACO to minimize assembly costs by optimizing operations, motions, and direction changes. This work laid the foundation for cost-effective automated assembly systems. He further advanced the field with his novel approach in "Correct assembly sequence for robotic assembly using motion instability and part contact-level graphs" (2009), which introduced directional part contact-level graphs to generate stable precedence constraints, ensuring correct and reliable assembly sequences. By integrating motion instability analysis with contact-level data, Sharma’s research addresses critical gaps in automated assembly, enhancing both precision and robustness. His contributions are essential for students and researchers exploring intelligent manufacturing, offering practical solutions for reducing costs and improving assembly quality in robotics.
Research Focus
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Top Papers
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