9358158 Yih The goal of this research project is to develop and apply intelligent decision aids to improve system performance in high variety and low volume manufacturing environments. Two critical areas to enhance the automation capability and intelligent decision making in such environments are knowledge based systems and machine learning. Specifically, this research project is intended to establish an efficient channel between the knowledge base and the knowledge source that may include human expert knowledge, simulation results, solutions from mathematical models, and experimental data. To achieve this goal, a learning based approach is gather data on the relationship between decisions and systems behavior, and continuously modify the knowledge with available new information. There are three phases involved in the planned research: (1) information selection and representation; (2) rule generation; and (3) learning algorithms. This research may results in intelligent decision aids that provide high quality and precise decisions in a timely manner to achieve production goals in manufacturing systems. This research may be applied to other decision problems in manufacturing if the parameters defining state conditions can be digitized, equipment replacement, troubleshooting, maintenance, material handling equipment dispatching, job assignment, tool management, and facility design. ***
