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

Leet, Christopher, Sciortino, Aidan, Koenig, Sven

arXiv.org Artificial Intelligence 

Abstract-- 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. T o 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. I. INTRODUCTION Flexible manufacturing is a key objective of the modern manufacturing industry [1]. A smart factory is flexible if it can be easily reconfigured to produce different products.