An Anytime, Scalable and Complete Algorithm for Embedding a Manufacturing Procedure in a Smart Factory
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866908573320085504 |
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| author | Leet, Christopher Sciortino, Aidan Koenig, Sven |
| author_facet | Leet, Christopher Sciortino, Aidan Koenig, Sven |
| contents | Modern automated factories increasingly run manufacturing procedures using a matrix of programmable machines, such as 3D printers, interconnected by a programmable transport system, such as a fleet of tabletop robots. To embed a manufacturing procedure into a smart factory, an operator must: (a) assign each of its processes to a machine and (b) specify how agents should transport parts between machines. The problem of embedding a manufacturing process into a smart factory is termed the Smart Factory Embedding (SFE) problem. State-of-the-art SFE solvers can only scale to factories containing a couple dozen machines. Modern smart factories, however, may contain hundreds of machines. We fill this hole by introducing the first highly scalable solution to the SFE, TS-ACES, the Traffic System based Anytime Cyclic Embedding Solver. We show that TS-ACES is complete and can scale to SFE instances based on real industrial scenarios with more than a hundred machines. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2510_01770 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | An Anytime, Scalable and Complete Algorithm for Embedding a Manufacturing Procedure in a Smart Factory Leet, Christopher Sciortino, Aidan Koenig, Sven Robotics Modern automated factories increasingly run manufacturing procedures using a matrix of programmable machines, such as 3D printers, interconnected by a programmable transport system, such as a fleet of tabletop robots. To embed a manufacturing procedure into a smart factory, an operator must: (a) assign each of its processes to a machine and (b) specify how agents should transport parts between machines. The problem of embedding a manufacturing process into a smart factory is termed the Smart Factory Embedding (SFE) problem. State-of-the-art SFE solvers can only scale to factories containing a couple dozen machines. Modern smart factories, however, may contain hundreds of machines. We fill this hole by introducing the first highly scalable solution to the SFE, TS-ACES, the Traffic System based Anytime Cyclic Embedding Solver. We show that TS-ACES is complete and can scale to SFE instances based on real industrial scenarios with more than a hundred machines. |
| title | An Anytime, Scalable and Complete Algorithm for Embedding a Manufacturing Procedure in a Smart Factory |
| topic | Robotics |
| url | https://arxiv.org/abs/2510.01770 |