Computer-aided maintenance : methodologies and practices
Jay K. Lee, Ben Wang · Kluwer Academic Pub. eBooks · 1999
List of contributors. Preface. Part One: Methodologies. 1. Fundamentals of maintenance G.M. Knapp, B. Wang. 2. Fundamentals of sensory systems for maintenance engineering J. Lee, et al. 3. Related work on machine monitoring and diagnostics Hsin Hao Huang, B. Wang. 4. Parametric modeling methods: theory and a case study J. Spoerre, B. Wang. 5. Machine performance estimation and reliability modeling Chang-Ching Lin, B. Wang. 6. Design methodology for self-maintenance machines Y. Umeda, et al. 7. Integrated prognostics, maintenance, and life extending control of continuous-time production processes A. Ray, S. Phoha. 8. Integrated automated root cause identification fuzzy neural network reasoning for quality control F. Tadayon, J. Lee. 9. Activity-based costing (ABC) A.S. Tsai. 10. Life cycle maintenance management S. Takata. 11. Life extension of operating machinery using the National Information Infrastructure (NII) S. Phoha, A. Ray. Part Two: Case Examples. 12. Case Example 1: Motor incipient fault detection using artificial neural network and fuzzy logic technologies Mo-yuen Chow, et al. 12. Case Example 2: Data analysis for diagnostics and process monitoring of automotive engines B.D. Bryant, K.A. Marko. 14. Case Example 3: Measurement of machine performance degradation using a neural network model J. Lee. 15. Case Example 4: Detection and isolation of faults in the stamping process using the Haar transform C.K.H. Koh, W.J. Williams. 16. Case Example 5: Fault monitoring in manufacturing systems using template models L.E. Holloway. 17. Case Example 6: In-process diagnostics of tool failure in milling K. Mori. 18. Case Example 7: Monitoring and predicting surface roughness and bore tolerance in end-milling A. Chukwujekwu Okafor. Index.