HRD - 9628685 Shirkhodaie Tennessee State University The College of Engineering and Technology at Tennessee State University proposes an instructional research activity to develop intelligent fault diagnostic tools for advanced predictive and preventative maintenance of manufacturing systems. The significant impact of this dual purpose project is four fold. First, it will support the college's effort to implement a maintenance engineering program at the graduate level. Secondly, it will strengthen the College's research capability to undertake maintenance projects of mutual interest to industry, Federal Government and funding research organizations. Finally, it will expand the College's research capabilities in one of its major core competencies, that of intelligent health monitoring of structures, and mechanical/thermal fluid systems. For this purpose, a 30-month, four phase project is proposed to develop and test intelligent fault diagnostic tools for advanced predictive and preventative maintenance of manufacturing systems. The research goal of the proposed project is to develop advanced predictive maintenance tools which can detect a potential maintenance problem (i.e., dry bearing) 25 to 50 percent sooner than traditional diagnostic techniques. In addition to detecting a potential problem, the proposed tools will identify the source of the potential problem and propose a corrective measure(s). Phase 1 research will focus on development of neural network based fault detection tools for pump-motor sets found in manufacturing systems. Phase 2 research objective is to add intelligent diagnostic capabilities to the neural network based fault detection tools. Artificial intelligence and fuzzy logic will be incorporated to make the tool intelligent with the capability to identify the source of a potential problem and recommend a corrective action(s). Phase 3 research will focus on testing the developed tools in a simulated, real world, manufacturing en vironment. This proof-of-concept testing will compare fault detection and identification rates using conventional techniques to that of intelligent fault diagnostic tools. Phase 4 involves the concurrent modernization of the College's Vibration Laboratory. It is in this laboratory that the advanced predictive tools will be tested. The proposed four phase research project will be completed over a 30-month period at a cost $150,000.00. At the completion of the proposed instructional research project the College of Engineering and Technology will have in place a maintenance engineering program at the graduate level, with predictive and preventative maintenance as a core instructional focus, in addition to proven analytical techniques for developing intelligent diagnostic tools with a Vibration Laboratory for testing the developed tools.
