Abstract
In the domain of industry warehousing, automated storage and retrieval systems (ASRS) consist of warehouse racks and stacker cranes that operate in a cartesian coordinate system to achieve a desired product flow. These systems maximize their throughput when the devices are operated at their maximum velocity and acceleration constraints. From a product lifecycle management viewpoint, operations with adaptive parameters could reduce energy consumption while meeting temporal constraints. In this paper, we investigate the applicability of two AI tools for sustainable lifecycle management of a stacker crane. We formulate parts of the lifecycle management as a data and AI problem.
We divide warehouse management to two categories: Resource allocation and operation optimization. Finally, we perform empirical validation through a warehouse management simulation environment. Our findings benefit lifecycle management strategies and operations of ASRS, contributing to more sustainable industry practices.
We divide warehouse management to two categories: Resource allocation and operation optimization. Finally, we perform empirical validation through a warehouse management simulation environment. Our findings benefit lifecycle management strategies and operations of ASRS, contributing to more sustainable industry practices.
| Original language | English |
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| Title of host publication | Proceedings of 3rd European Symposium on Artificial Intelligence in Manufacturing |
| Publisher | Springer |
| Number of pages | 8 |
| Publication status | Accepted/In press - 2025 |
| MoE publication type | A4 Article in a conference publication |
| Event | 3rd European Symposium on Artificial Intelligence in Manufacturing, ESAIM 2025 - Donostia-San Sebastian, Spain Duration: 8 Oct 2025 → 8 Oct 2025 |
Publication series
| Series | Lecture Notes in Mechanical Engineering |
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| ISSN | 2195-4356 |
Conference
| Conference | 3rd European Symposium on Artificial Intelligence in Manufacturing, ESAIM 2025 |
|---|---|
| Country/Territory | Spain |
| City | Donostia-San Sebastian |
| Period | 8/10/25 → 8/10/25 |
Funding
This work has been supported by the project “Digital assets and tools for Circular value chains and manufacturing products” (DaCapo), which has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No. ID: 101091780. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union o HADEA. Neither the European Union nor the granting authority can be held responsible for them.
Keywords
- sustainability
- data
- product lifecycle
- automated warehousing
