DISTRIBUTED ARTIFICIAL-INTELLIGENCE IN MANUFACTURING SYSTEMS CONTROL

This research uses a Distributed Artificial Intelligence (DAI) framework to efficiently utilize the infrastructure available for process planning in a batch processing PWB assembly facility. The DAI approach. decomposes the entire production control task into several sub-tasks. Then, the sub-tasks are implemented by the basic elements of the DAI system called 'intelligent agents'. By working collectively, the intelligent agents of the DAI system can arrive at a solution for the problem. The DAI system initially proposes all possible solutions generated by the intelligent agents. Then, a fuzzy coordination technique is utilized to evaluate the solutions and to find the most appropriate one for shopfloor implementation. Using inputs such as the short-term production plan, design data, shopfloor observation data, and CAD information, the DAI system provides applicable production plans with ranks for the feasibility of current assembly activities.