Michael Eder
Papers
5
Total Citations
34
H-Index
4
About
Michael Eder is an emerging researcher specializing in the performance analysis and optimization of robotic compact storage and retrieval systems (RCS/RS), a rapidly expanding technology in modern automated warehousing and logistics. His work addresses a critical gap in the field: despite thousands of RCS/RS installations worldwide, rigorous analytical frameworks for predicting and optimizing system throughput have been largely absent. Eder's major contributions include developing both simulation-based and analytical methodologies to evaluate RCS/RS performance across a variety of configurations, including systems with multiple robots, multiple picking stations, varying stack heights, and class-based access structures. His 2023 simulation study, which has garnered 10 citations, laid important groundwork by examining multi-robot configurations serving a single picking station. Subsequent analytical models expanded this foundation to accommodate more complex real-world scenarios, including relocation strategies and scalable station layouts, each accumulating between 7 and 9 citations within a remarkably short timeframe. Collectively, Eder's research provides warehouse designers and logistics engineers with practical, mathematically grounded tools for planning and scaling RCS/RS installations. His rapidly growing citation record, spanning just two years, signals meaningful and timely contributions to the field of intelligent automated storage systems.
Research Focus
Key Achievements
Top Papers
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