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Self-Management Process in S-Maintenance Platform

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Engineering Asset Management 2011

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

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Abstract

E-maintenance systems are considered as platforms integrating various systems in the maintenance scope, but these platforms provide only the services provided by their integrated systems. S-maintenance platform is built in the aim to provide dynamic services thanks to its core components, especially its knowledge base. This paper focus the exploitation of the s-maintenance architecture’s components to define two new processes that we called self management and self learning processes. These processes allow the automatic acquirement and integration of knowledge in the knowledge base and the dynamic evolution of the platform behavior.

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References

  1. Li Y, Chun L, Nee A, Ching Y (2005) An agent-based platform for web enabled equipment predictive maintenance. Proceedings of IAT’05 IEEE/WIC/ACM international conference on intelligent agent technology, Compie`gne, France

    Google Scholar 

  2. Chebel-Morello B, Karray M H, Zerhouni N (2010) New perspectives of Maintenance systems: “towards s-maintenance”. In: Proceedings of the IMS2010 Summer School on sustainable manufacturing. Zurich

    Google Scholar 

  3. Karray MH, Chebel-Morello B, Lang C, Zerhouni N (2011) A component based system for S-maintenance. In: Proceedings of 9th IEEE International Conference on industrial informatics, pp 519–526

    Google Scholar 

  4. Ganek AG, Corbi TA (2003) The dawning of the autonomic computing era. IBM Syst J 42(1):5–18

    Article  Google Scholar 

  5. Leondes CT (2000) Knowledge—based systems: techniques and applications. Academic Press

    Google Scholar 

  6. Poole D, Mackworth A, Goebel R (1998) Computational intelligence: a logical approach. Oxford University Press

    Google Scholar 

  7. Nilsson J (1998) Introduction to machine learning: an early draft of a proposed textbook. Available from http://robotics.stanford.edu/people/nilsson/mlbook.html, pp 175–188

  8. Robin (2010) Machine learning overview. Available from http://intelligence.worldofcomputing.net/machine-learning/machine-learning-overview.html

  9. Xu CS, Xu ZM, Xiao PD, Zhou ZY, Liu SX, Jiang ZH (1995) A self-learning system and its application in fault diagnosis. In: Proceedings of the instrumentation and measurement technology conference

    Google Scholar 

  10. Lowe G, Shirinzadeh B (2005) A knowledge-base self-learning system. In: Proceedings of the (483) ACIT–automation, control, and applications

    Google Scholar 

  11. Ganek AG, Corbi TA (2003) The dawning of the autonomic computing era. IBM Syst J 42(1):5–18

    Article  Google Scholar 

  12. Haydarlou AR, Oey MA, Overeinder BJ, Brazier FMT (2006) Using semantic web technology for self-management of distributed object-oriented systems. In: Proceedings of the 2006 IEEE/WIC/ACM international conference on web intelligence (WI-06). Hong Kong, China

    Google Scholar 

  13. http://en.wikipedia.org/wiki/Workers%27_self-management 2010

  14. Karray MH, Chebel-Morello B, Zerhouni N (2011) A formal ontology for industrial maintenance. In: Proceedings of the 5th terminology & ontology: theories and applications conference 2011

    Google Scholar 

  15. Chalupsky H, MacGregor RM, Russ T (2010) PowerLOOM manual: powerful knowledge representation and reasoning with delivery in Common-Lisp, Java, and C++ Version: 1.48

    Google Scholar 

  16. http://en.wikipedia.org/wiki/View_%28database%29

  17. Quinlan JR (1986) Induction of decision trees. Mach Learn 1(1):81–106

    Google Scholar 

  18. Quinlan JR (1993) C4.5: programs for machine learning. Morgan Kaufmann, San Francisco

    Google Scholar 

  19. Breiman L, Friedman J, Olshen R, Stone C (1984) Classification and regression trees. Chapman and Hall/CRC, Monterey, CA

    MATH  Google Scholar 

  20. Utgoff P (1989) Incremental induction of decision trees. Mach Learn 4(2):161–186

    Article  Google Scholar 

  21. Bouckaert RR, Frank W, Hall M, Kirkby R, Reutemann P, Seewald A, Scuse D. WEKA Manual for Version 3-6-4. The University of Waikato

    Google Scholar 

  22. Ml Breen (2005) Experience of using a lightweight formal specification method for a commercial embedded system product line. Requirements Eng J 10(2):161–172. doi:10.1007/s00766-004-0209-1

    Article  Google Scholar 

  23. Kohavi R, Quinlan (2002) Decision-tree discovery. In: Klosgen W, Zytkow JM (eds) Handbook of data mining and knowledge discovery. Oxford University Press, Chapter 16.1.3, pp 267–276

    Google Scholar 

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Acknowledgments

This work was carried out and funded in the framework of SMAC project (Semantic-maintenance and life cycle), supported by Interreg IV program between France and Switzerland.

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Correspondence to C. Lang .

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Appendices

Appendix A

See Table 44.6

Table 44.6 Data dictionary of the processes model concept name

Appendix B

The following PowerLOOM instructions present the Knowledge base containing the part of the ontology shown above concerning process management. Each UML class is translated into a PowerLOOM concept using the "DEFCONCEPT" command. Associations and attributes of classes are translated into a PowerLOOM relation or function using the "DEFFUNCTION" and "DEFRELATION" commands. The command "ASSERT" is used to define different instances of concepts and relations.

  • (DEFCONCEPT Task)

  • (DEFCONCEPT Process-Pattern (?T Task))

  • (DEFCONCEPT Maintenance-Type (?PT Process-Pattern))

  • (DEFCONCEPT Step)

  • (DEFCONCEPT First-Step (?S Step))

  • (DEFCONCEPT Transition)

  • (DEFCONCEPT Next-Step (?S Step))

  • (DEFCONCEPT Constraint)

  • (Defrelation (StepInPut ((?T Transition) (?NS Step)))

  • (Defrelation (hasFirstStep ((?MT Maintenance-Type) (?FS First-Step)))

  • (Defrelation (StepOutPut ((?FS Step) (?T Transition)))

  • (Defrelation (Refrences ((?S Step) (?T Task)))

  • (Assert (Maintenace-Type Conditional-Maintenance)

  • (Assert (Maintenace-Type Predective-Maintenance)

  • (Assert (Maintenace-Type Systematic-Maintenance)

  • (Assert (Maintenace-Type Systematic-Maintenance)

  • (Assert (Step Monitoring-Process)

  • (Assert (Step Prognostic)

  • (Assert (Step Scheduling-Process)

  • (Assert (Management-Process)

  • (Assert (Transition Alarm)

  • (Assert (Transition RUL)

  • (Assert (Transition Notification-Date)

  • (ASSERT (hasFirstStep Conditional-Maintenance Monitoring-Process))

  • (ASSERT (hasFirstStep Predective-Maintenance Prognostic))

  • (ASSERT (hasFirstStep Systematic-Maintenance Scheduling-Process))

  • (ASSERT (StepOutPut Monitoring-Process Alarm))

  • (ASSERT (StepOutPut Prognostic RUL))

  • (ASSERT (StepOutPut Scheduling-Process Notification-Date))

  • (ASSERT (StepInPut RUL Management-Process))

  • (ASSERT (StepInPut Alarm Management-Process))

  • (ASSERT (StepInPut Notification-Date Management-Process))

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Karray, M.H., Morello, B.C., Lang, C., Zerhouni, N. (2014). Self-Management Process in S-Maintenance Platform. In: Lee, J., Ni, J., Sarangapani, J., Mathew, J. (eds) Engineering Asset Management 2011. Lecture Notes in Mechanical Engineering. Springer, London. https://doi.org/10.1007/978-1-4471-4993-4_44

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  • DOI: https://doi.org/10.1007/978-1-4471-4993-4_44

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  • Print ISBN: 978-1-4471-4992-7

  • Online ISBN: 978-1-4471-4993-4

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