DISTRIBUTED ARTIFICIAL-INTELLIGENCE IN MANUFACTURING SYSTEMS CONTROL

This research uses a Distributed Artificial Intelligence (DAI) framewo rk to efficiently utilize the infrastructure available for process pla nning in a batch processing PWB assembly facility. The DAI approach. d ecomposes the entire production control task into several sub-tasks. T hen, the sub-tasks are implemented by the basic elements of the DAI sy stem called 'intelligent agents'. By working collectively, the intelli gent agents of the DAI system can arrive at a solution for the problem . The DAI system initially proposes all possible solutions generated b y the intelligent agents. Then, a fuzzy coordination technique is util ized to evaluate the solutions and to find the most appropriate one fo r shopfloor implementation. Using inputs such as the short-term produc tion plan, design data, shopfloor observation data, and CAD informatio n, the DAI system provides applicable production plans with ranks for the feasibility of current assembly activities.