Andreas Kuhnle
Papers
1
Total Citations
51
H-Index
1
About
Andreas Kuhnle is a leading researcher in production planning and control, with a focus on remanufacturing, disassembly systems, and intelligent automation. His work bridges operations management and artificial intelligence, particularly through the application of reinforcement learning to complex, flexible manufacturing environments. Kuhnle’s most cited paper, “Modelling and condition-based control of a flexible and hybrid disassembly system with manual and autonomous workstations using reinforcement learning” (2022, 51 citations), addresses the critical challenge of disassembly—a relatively underexplored area compared to assembly—by proposing a novel control framework that integrates manual and autonomous workstations. This contribution is pivotal for advancing sustainable manufacturing, as it enables efficient resource recovery and waste reduction. Kuhnle’s research has significant implications for the circular economy, offering practical solutions for industries aiming to reduce emissions and conserve natural resources. His work is widely recognized for its methodological rigor and real-world applicability, making him a key figure in the evolving field of smart remanufacturing and hybrid production systems.
Research Focus
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Top Papers
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