Self-organizing manufacturing control: an industrial application of agent technology

We present an auction-based approach to manufacturing control. Workpieces auction off their current task, while machines bid for tasks. When awarding a machine, a workpiece takes into account not only the machine's current work in process, but also the outgoing flow of materials. If a machine's outgoing stream is blocked, eventually the machine will not accept a new workpiece, thus blocking its input stream as well. As a result a capacity bottleneck is automatically propagated in the opposite direction of the material flow. A unique feature of this mechanism is that it does not pre-suppose any specific material flow; the current capacity bottleneck is always propagated in the opposite direction of the actual flow, no matter what this flow looks like. This paper includes a detailed analysis of the mechanism, including a formal proof of its freedom of deadlocks. DaimlerChrysler evaluated the new control approach as a bypass to an existing manufacturing line. A suite of performance tests demonstrated the industrial feasibility and the benefits of the approach.

[1]  Peter Wegner,et al.  Interactive , 2021, Encyclopedia of the UN Sustainable Development Goals.

[2]  Joseph G. Maley Managing the flow of intelligent parts , 1988 .

[3]  H. Van Dyke Parunak From Chaos to Commerce: Practical Issues and Research Opportunities in the Nonlinear Dynamics of Decentralized Manufacturing Systems , 1999 .

[4]  Ronald Schoop,et al.  Agent-oriented material flow control system based on DCOM , 2000, Proceedings Third IEEE International Symposium on Object-Oriented Real-Time Distributed Computing (ISORC 2000) (Cat. No. PR00607).

[5]  Hal R. Varian,et al.  Economic Mechanism Design for Computerized Agents , 1995, USENIX Workshop on Electronic Commerce.

[6]  Michael J. Shaw,et al.  Task Bidding and Distributed Planning in Flexible Manufacturing , 1985, CAIA.

[7]  Tamás Kis,et al.  Controlling Distributed Manufacturing Systems by a Market Mechanism , 1996, ECAI.

[8]  Duncan McFarlane,et al.  Rationales for Holonic Manufacturing Control , 1999 .

[9]  Tuomas Sandholm,et al.  Distributed rational decision making , 1999 .

[10]  H. Van Dyke Parunak,et al.  An Architecture for Heuristic Factory Control , 1986, 1986 American Control Conference.