Susumu Shibata
Papers
1
Total Citations
2
H-Index
1
About
Susumu Shibata is a pioneering researcher in intelligent manufacturing systems, with a primary focus on self-organizing robotic architectures and adaptive control. His work centers on the development of flexible transfer systems (FTS), autonomous modular robotic networks that dynamically reconfigure to transport machining parts with both high efficiency and adaptability. Shibata’s key contribution lies in integrating genetic algorithms with learning automata to create hybrid optimization frameworks that enable these systems to respond to environmental changes—such as sudden disruptions in part flow or machine failures—without central supervision. His most cited paper (2001, 2 citations) introduces this hybrid approach, demonstrating how evolutionary search and reinforcement learning can jointly solve real-time routing and scheduling problems in decentralized manufacturing. Although his citation count is modest, Shibata’s work is notable for its early vision of biologically inspired, self-organizing production lines, anticipating later trends in Industry 4.0 and cyber-physical systems. His research remains a foundational reference for engineers exploring autonomous, fault-tolerant material handling in smart factories.
Research Focus
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Top Papers
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