Advertisement

Failure Cause Analysis of Machine Tools

Chapter
Part of the Springer Series in Advanced Manufacturing book series (SSAM)

Keywords

Machine Tool Causality Relation Fault Diagnosis Flexible Manufacturing System Cause Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alexander SM, Vaidya CM, Graham JH (1993) Model for the diagnosis of CIM equipment. Computer-Electronics Engineering 19:175–183CrossRefGoogle Scholar
  2. Angeli C, Chatzinkikoraou A (1985) An expert system approach to fault diagnosis in hydraulic systems. Expert Systems 12:323–329CrossRefGoogle Scholar
  3. BREU-CT-91-0463 (1992) MIRAM-Machine management for increasing the reliability, availability, and maintainability. Heckler & Koch, University of WalesGoogle Scholar
  4. Clark GE, Paasch RK (1997) Diagnostic modeling and diagnosability evaluation of mechanical systems. Journal of Mechanical Design 119:57–67.Google Scholar
  5. Czichos H (1980) Systems Approach to the analysis of wear problems. In: International Conference on Friction, Lubrication, and Wear in Engineering, Melbourne, AustraliaGoogle Scholar
  6. Czichos H (1978) Tribology-a systems approach to science and technology of friction, lubrication, and wear. Tribology Series-I, Elsevier, AmsterdamGoogle Scholar
  7. Das K, Lashkari RS, Sengupta S (2007) Reliability consideration in the design and analysis of cellular manufacturing systems. International Journal of Production Economics 105:243–262CrossRefGoogle Scholar
  8. Drake PR, Pan D (1996) Multiple fault diagnosis for a machine tool’s flood coolant system using a neural network. International Journal of Machine Tools & Manufacture 36:1247–1251CrossRefGoogle Scholar
  9. Freyermuth B (1991) Knowledge based incipient fault diagnosis of industrial robots. In: Safeprocess 91, Baden-Baden, Germany, pp 31–37Google Scholar
  10. Fussell JB (1975) A review of fault tree analysis with emphasis on limitations. In: Proc. IFAC 6th World Congress, BostonGoogle Scholar
  11. Fussel JB (1976) Fault tree analysis concepts and techniques. In: Henley EI, Lynn IW (eds) Generic techniques in systems and reliability assessment, Noordhoff International, LeydenGoogle Scholar
  12. Gandhi OP, Agrawal VP (1994) A digraph approach to system wear evaluation and analysis. Journal of Tribology 116:268–274CrossRefGoogle Scholar
  13. Gandhi OP, Agrawal VP (1996) Failure cause analysis-a structural approach. Journal of Pressure Vessel Technology 118:434–440Google Scholar
  14. Holloway LE, Krogh BH (1990) Fault detection and diagnosis in manufacturing system: a behavioral model approach. In: Proc. 2nd International Conference on CIM, Troy, New YorkGoogle Scholar
  15. Hu W, Starr AG, Leung AYT (1991) Two diagnostic models for PLC controlled flexible manufacturing systems. International Journal of Machine Tools & Manufacture 39:1979–1991CrossRefGoogle Scholar
  16. Hu W, Starr AG, Zhou Z, Leung AYT (2000) A systematic approach to integrated fault diagnosis of flexible manufacturing systems. International Journal of Machine Tools & Manufacture 40:1587–1602CrossRefGoogle Scholar
  17. Huang JT, Liao YS (2000) A wire-EDM maintenance and fault diagnosis expert system integrated with an artificial neural network. International Journal of Production Research 38:2459–2470CrossRefGoogle Scholar
  18. Isermann R (1991) Fault diagnosis of machines via parameter estimation and knowledge processing. Safeprocess 91, Baden-Baden, Germany, pp 121–134Google Scholar
  19. Ishida Y, Adachi N, Tokumaru H (1985) A topological approach to failure diagnosis of large scale system. IEEE Transactions on Systems, Man, and Cybernetics 20:129–141.MathSciNetGoogle Scholar
  20. Johansson KE (1981) Field monitoring of NC machines-a systems approach. In: Innovation for Maintenance Technology Improvements, MFPG 3rd Meeting, National Bureau of Standards, New YorkGoogle Scholar
  21. Kegg RL (1984) On line process diagnostics. CIRP Annals 33:469–473Google Scholar
  22. Keller AZ, Perera VD (1981) Reliability analysis of CNC machine tools. In: Proc. 3rd National Conference on Reliability, MacclesfieldGoogle Scholar
  23. Kilmartin BR, Hannan RG (1981) An in-company study of NC machine utilization and its improvement by a systems approach. International Journal of Production Research 19:289–300Google Scholar
  24. Kokowa M, Miyazaki S, Shingai S (1983) Fault location using digraph and inverse direction search with application. Automatica 19:729–735CrossRefGoogle Scholar
  25. Kokowa M, Shingai S (1982) Failure propagating simulation and non-failure path search in network systems. Automatica 18:335–341CrossRefGoogle Scholar
  26. Kwon HD, Burdekin M (1998) Adjustment of CNC machine tool controller setting values by an experimental method. International Journal of Machine Tools & Manufacture 38:1045–1065CrossRefGoogle Scholar
  27. Lee J (1995) Machine performance monitoring and proactive maintenance in computer integrated manufacturing: review and perspective. International Journal of Computer 1ntegratedManufacturing 8:370–380Google Scholar
  28. Lee J, Kramer BM (1993) Analysis of machine degradation using a neural network approach. Journal of Manufacturing Systems 12:379–387Google Scholar
  29. Luis AFG, Gilberto HR, Rocio PV, Rene DJRT, Wbaldo LT (2006) Sensorless tool failure monitoring system for drilling machines. International Journal of Machine Tools and Manufacture 46:381–386CrossRefGoogle Scholar
  30. Majstorovic V, Milacic V (1990) Expert system for diagnosis and maintenance. Maintenance 5:19–22Google Scholar
  31. Marczewsky R (1988) An expert system for machine tool diagnosis. In: Proc. Of 2nd Engineering Society of Detroit Conference on Expert Systems, DetroitGoogle Scholar
  32. Martin KF (1994) A review by discussion of condition monitoring and fault diagnosis in machine tools. International Journal of Machine Tools & Manufacture 34:527–551CrossRefGoogle Scholar
  33. Martin KF, Hoh SM, Thorpe P (1990) Fault diagnosis of hard faults. In: International Conference on Manufacturing Systems and Environment, Japan Society of Mechanical Engineers, TokyoGoogle Scholar
  34. Marzi MH, Martin KF (1990) Artificial neural network condition monitoring and fault diagnosis. In: Proc. ASME International Conference on Neural Networks, San Diego, CAGoogle Scholar
  35. NCSR (1988) CNC machining center. AMTA Reliability Publications, RisleyGoogle Scholar
  36. Poltavets OF (1994) Diagnostics in the machine tool: purpose, state, and prospects. Russian Engineering Research 14:6–8Google Scholar
  37. Puetz RD, Eichhorn S (1987) Expert systems for fault diagnosis of CNC machines. In: Sviram D, Adey RD (eds) Knowledge-based expert systems for engineering. Computational Mechanics Publications, LondonGoogle Scholar
  38. Rao SB (1997) Metal cutting machine tool design. Journal of Manufacturing Science and Engineering 119:713–716Google Scholar
  39. Rao RV, Gandhi OP (2002) Failure cause analysis of machine tools using digraph and matrix methods. International Journal of Machine Tools & Manufacture 42:521–528CrossRefGoogle Scholar
  40. Sethi VK, Agrawal VP (1993) Hierarchical classification of kinematic chains: a multigraph approach. Mechanism and Machine Theory 28:601–614CrossRefGoogle Scholar
  41. Stewart E (1977) A survey of machine tool breakdowns. MTIRA Research Report No.63, In: Proc. of National Conference on Reliability, MacclesfieldGoogle Scholar
  42. Williams JH (1990) Transfer function techniques and fault location. Research Studies Press, Reading, MAGoogle Scholar
  43. Ye N, Zhao B (1996) Hybrid intelligent system for fault diagnosis of advanced manufacturing systems. International Journal of Production Research 34:555–576zbMATHGoogle Scholar
  44. Yoshikawa H (1982) Multi-purpose modelling of mechanical systems-morphological model as a mesomode. In: Bjorke OP, Franksen OI (eds) System structures in engineering economic design and production. Tapir Publishers, TrondheimGoogle Scholar
  45. Zeng L, Wang HP (1991) Machine fault classification: a fuzzy set approach. International Journal of Advanced Manufacturing Technology 6:83–94CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2007

Personalised recommendations