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An Anytime, Scalable and Complete Algorithm for Embedding a Manufacturing Procedure in a Smart Factory

Published: October 2, 2025 | arXiv ID: 2510.01770v1

By: Christopher Leet, Aidan Sciortino, Sven Koenig

Potential Business Impact:

Helps factories with many machines work better.

Business Areas:
Intelligent Systems Artificial Intelligence, Data and Analytics, Science and Engineering

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.

Country of Origin
🇺🇸 United States

Page Count
8 pages

Category
Computer Science:
Robotics