提出可扩展的完整算法，解决百台以上机器工厂的生产流程部署问题。
An Anytime, Scalable and Complete Algorithm for Embedding a Manufacturing Procedure in a Smart Factory
- 基于交通系统建模，设计可随时输出解的循环嵌入求解器
- 在真实工业场景中成功部署超百台机器的制造流程
- 适合大规模智能工厂的生产调度与自动化部署
现代自动化工厂越来越多地使用可编程机器矩阵（如3D打印机）和可编程运输系统（如桌面机器人车队）来执行制造流程。将制造流程嵌入智能工厂需完成两项任务：(a) 将每个工序分配至具体机器，(b) 规定代理如何在机器间运输零件。该问题称为智能工厂嵌入（SFE）问题。现有SFE求解器仅能处理几十台机器规模的工厂，而现代智能工厂可能包含数百台机器。本文提出首个高度可扩展的SFE解决方案——基于交通系统的任意时间循环嵌入求解器（TS-ACES），证明其完全性，并在基于真实工业场景的实例上实现超过百台机器的可扩展部署。
原文摘要 · Abstract (English)
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.
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