Experiments toward a practical implementation of an intelligent kanban system

Authors:
James Z. M. Zhang;James Brusey;Robert B. Johnston
Affiliations:
Department of Information System, University of Melbourne, Australia;Institute for Manufacturing, University of Cambridge, UK;Department of Information System, University of Melbourne, Australia
Venue:
HoloMAS'05 Proceedings of the Second international conference on Holonic and Multi-Agent Systems for Manufacturing
Year:
2005

Citing 4
Cited 0

Reference architecture for holonic manufacturing systems: PROSA

Computers in Industry - Special issue on manufacturing systems
Wasp-like Agents for Distributed Factory Coordination

Autonomous Agents and Multi-Agent Systems
Intelligent Kanban: Evaluation of a Supply Chain MAS Application Using Benchmarking

EEE '05 Proceedings of the 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'05) on e-Technology, e-Commerce and e-Service
Pengi: an implementation of a theory of activity

AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 1

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents laboratory experiments to test a bottom up approach to production control and supply chain management. Built upon the successful traditional kanban (Card) system, the new intelligent system associates a kanban agent to each physical kanban. Instead of relying on demand forecast and planning, kanban agents reason about their own movements to adapt to changing demands. After previous simulations results of the intelligent system showed significant performance improvements over the traditional system, we further use the Auto-ID Laboratory at Cambridge University to test the feasibility of the idea in a realistic manufacturing environment. The results from the experiments demonstrated the superiority on several performance measures of the intelligent system compared to the traditional system used as a benchmark. Moreover, the implementation of the experiments exposed several real world constraints not shown in the simulation study and practical solutions were adopted to address these.