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A troubleshooting process planning using knowledge base and distributed database approach

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Abstract

This study introduces an approach of knowledge acquisition and modeling for troubleshooting process planning. It is essential for constructing a knowledge base can be maintained and shared. A knowledge base should not merely be a set of rules but a framework of troubleshooting that can be controlled and customized by rules. For the construction of a knowledge base, identifying the types of knowledge components to be included is a prerequisite. To identify the knowledge units, this study employs a modeling approach consisting of three sub-models: object model, functional model, and dynamic model. In addition, mechanisms for maintaining dependency relations of the troubleshooting descriptions at different locations and reasoning using the knowledge at different locations are also developed. The system is implemented using an object oriented programming language. The proposed approaches are applied to the troubleshooting process planning in automotive braking system.

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References

  1. Hsu JY, Lin YH, Wei ZY (2008) Competition policy for technological innovation in an era of knowledge-based economy. Knowl-Based Syst 21(8):826–832

    Article  Google Scholar 

  2. Huin SF, Luong LHS, Abhary K (2003) Knowledge-based tool for planning of enterprise resources in ASEAN SMEs. Robot Comput-Integr Manuf 19(5):409–414

    Article  Google Scholar 

  3. Cheung CF, Chan YL, Kwok SK, Lee WB, Wang WM (2006) A knowledge-based service automation system for service logistics. J Manuf Tech Manag 17(6):750–771

    Article  Google Scholar 

  4. Halevi G, Wang K (2007) Knowledge based manufacturing system (KBMS). J Intell Manuf 18(4):467–474

    Article  Google Scholar 

  5. Liang JS (2008) The troubleshooting task implementation in automotive chassis using virtual interactive technique and knowledge-based approach. J Netw Comput Appl 31(4):712–734

    Article  Google Scholar 

  6. Liang JS (2010) A web-based automotive refrigeration troubleshooting system applying knowledge engineering approach. Comput Ind 61(1):29–43

    Article  Google Scholar 

  7. Angel IC, Chatzinikolaou A (1995) An expert system approach to fault diagnosis in hydraulic systems. Expert Systems 12:323–329

    Article  Google Scholar 

  8. Stefano A, Bello L, Mirabella O (1997) Virtual plant: a distributed environment for distance monitoring and control of industrial plants. In: Proceedings of IEEE Intelligent Engineering Systems, Budapest, Hungary, 445–449

  9. Lee J (1997) Strategy and challenges on remote diagnostics and maintenance for manufacturing equipment. In: Proceedings of the Annual Symposium on Reliability and Maintainability, Philadelphia, PA, USA, 368–370

  10. Simeu-Abazi Z, Bouredji Z (2006) Monitoring and predictive maintenance: modeling and analyse of fault latency. Comput Ind 57(6):504–515

    Article  Google Scholar 

  11. Denkena B, Kowalski MSP, Molcho G, Zipori Y (2007) Knowledge management in process planning. CIRP Annals: Manuf Tech 56(1):175–180

    Article  Google Scholar 

  12. Hong G, Deyi X, Tu Y (2010) Rapid identification of the optimal product configuration and its parameters based on customer-centric product modeling for one-of-a-kind production. Comput Ind 61(3):270–279

    Article  Google Scholar 

  13. Shah JJ, Mantyla M (1995) Parametric and feature-based CAD/CAM. Wiley, New York

    Google Scholar 

  14. Hameri AP, Nihtila J (1998) Product data management—exploratory study on state-of-art in one-of-a-kind industry. Comput Ind 35(1):195–206

    Article  Google Scholar 

  15. Salomons OW, Houten FJAM, Kals HJJ (2002) Review of research in feature-based design. Journal of Manufacturing System 12(2):113–132

    Article  Google Scholar 

  16. Lee HC, Jhee WC, Park HS (2007) Generative CAPP through projective feature recognition. Comput Ind Eng 53(2):241–246

    Article  Google Scholar 

  17. Dean PR, Tu YL, Xue D (2008) A framework for generating product production information for mass customization. Int J Adv Manuf Technol 38(11–12):1244–1259

    Article  Google Scholar 

  18. Yao S, Han X, Yang Y, Rong Y, Huang SH, Yen DW, Zhang G (2007) Computer-aided manufacturing planning for mass customization: part 1, framework. Int J Adv Manuf Technol 32(1):194–204

    Article  Google Scholar 

  19. Kiritsis D (1995) A review of knowledge-based expert systems for process planning: methods and problems. Int J Adv Manuf Technol 10(4):240–262

    Article  Google Scholar 

  20. Pan M, Rao Y (2009) An integrated knowledge based system for sheet metal cutting-punching combination processing. Knowl-Based Syst 22(5):368–375

    Article  Google Scholar 

  21. Callan R (2003) Artificial Intelligence. Macmillan, Basingstoke

    Google Scholar 

  22. Liao SH (2005) Expert system methodologies and applications—a decade review from 1995 to 2004. Expert Syst Appl 28(1):93–103

    Article  Google Scholar 

  23. Harmelen FV, Lifschitz V, Porter B (2007) Handbook of knowledge representation (Foundations of artificial intelligence). Elsevier, San Diego

    Google Scholar 

  24. Hu CJ, Li ZZ, Zheng L, Li N, Wen PH (2008) An XML-based implementation of manufacturing route sheet documents for context-sensitive and web-based process planning. Int J Computer Integr Manuf 21(6):647–656

    Article  Google Scholar 

  25. Khodja SA, Perry N, Bernard A (2008) Processing knowledge to support knowledge-based engineering systems specification. Concurr Eng 16(1):89–101

    Article  Google Scholar 

  26. Wellmana MP, Robert JSB, Goldmana P (2009) From knowledge bases to decision models. Cambridge University Press, Cambridge

    Google Scholar 

  27. Russell SJ, Norvig P (2003) Artificial Intelligence: a modern approach. Prentice Hall, Englewood Cliffs

    Google Scholar 

  28. Yang KH, Olson D, Kim J (2004) Comparison of first order predicate logic, fuzzy logic and non-monotonic logic as knowledge representation methodology. Expert Syst Appl 27(4):501–519

    Article  MATH  Google Scholar 

  29. Huhns MN, Singh MP (1998) Readings in agents. Morgan Kaufmann, San Francisco

    Google Scholar 

  30. Bliznakov PI, Shah JJ, Jeon DK, Urban SD (1995) Design information system infrastructure to support collaborative design in a large organization. In: Proceeding of ASME Design Engineering Technical Conference, Boston, USA, 1–8

  31. Adamides ED (1995) Coordination of distributed production resources for responsibility-based manufacturing. J Intell Manuf 6:415–427

    Article  Google Scholar 

  32. Pahng F, Senin N, Wallace D (1998) Distribution modeling and evaluation of product design problems. Comput-Aided Des 30(6):411–423

    Article  Google Scholar 

  33. Reidsema C, Szczerbicki E (1997) Multi-agent systems for concurrent engineering. Syst Anal Model Simul 28(1–4):257–279

    MATH  Google Scholar 

  34. Danesh MR, Jin Y (1999) AND: an agent-based decision network for concurrent design and manufacturing. In: Proceedings of the ASME Design Engineering Technical Conferences, Las Vegas, Nevada, USA

  35. Leitao P (2009) Agent-based distributed manufacturing process planning and scheduling: a state-of-the-art survey. Eng Appl Artif Intell 22(7):979–991

    Article  Google Scholar 

  36. Gadh R, Sonthi R (1998) Geometric shape abstractions for internet-based virtual prototyping. Comput-Aided Des 30(6):473–486

    Article  MATH  Google Scholar 

  37. Tso SK, Lau HCW, Ho JKL, Zhang WJ (1999) A framework for developing agent-based collaborative service-support system in a manufacturing information network. Eng Appl Artif Intell 12:43–57

    Article  Google Scholar 

  38. Dormaz DN, Khoshnevis B (1997) Process planning knowledge representation an object-oriented data model. Int J Computer Integr Manuf 10(1–4):92–104

    Google Scholar 

  39. Younis MA, Wahab MA (1997) A CAPP expert system for rotational components. Comput Ind Eng 33(3–4):509–512

    Article  Google Scholar 

  40. Chen CH, Rao Z (2008) MRM: a matrix representation and mapping approach for knowledge acquisition. Knowl-Based Syst 21(4):284–293

    Article  Google Scholar 

  41. Liang JS (2009) Development for a web-based EDM laboratory in manufacturing engineering. Int J Computer Integr Manuf 22(2):83–99

    Article  Google Scholar 

  42. Shirasu H, Sashida H (1998) Integrating a state transition diagram with call processing program using a dataflow technique. Syst Comput Jpn 28(8):17–24

    Article  Google Scholar 

  43. Mori T, Yasumura Y, Uehara K (2008) Negotiation system considering personality by state transition diagram and text classification. IEICE Tech Rep 107(480):75–80, NLC2007-100

    Google Scholar 

  44. Object manager group, UML-state diagram, Available from: http://www.uml.org/, [Accessed in 10 Dec. 2009]

  45. Allamaraju S, Beust C, Wilcox M, Tyagi S, Johnson R, Watson G, Williamson A, Davies J, Nagappan R, Longshaw A, Sarang PG, Jewell T, Toussaint A (2001) Professional Java Server Programming J2EE, 13th edn. Wrox, Hoboken

    Google Scholar 

  46. Broemmer D (2002) J2ee Best Practices (Ad) W/Ws. Wiley, Hoboken

    Google Scholar 

  47. Sun Developer Network, Java EE Reference at a Glance, Available from: http://java.sun.com/javaee/reference/, [Accessed in 5, July, 2009]

  48. Free Java Books, www.freeprogrammingresources.com. Available from: http://www.freeprogrammingresources.com/javabook.html, [Accessed in 10, July, 2009]

  49. Reilly D, Reilly M (2002) Java Network Programming and Distributed Computing. Addison-Wesley, Boston

    Google Scholar 

  50. Harold ER (2004) Java Network Programming 2nd Edition. O’Reilly, Cambridge

    Google Scholar 

  51. The Java Tutorials, All about Sockets. Available from: http://java.sun.com/docs/books/tutorial/networking/, [Accessed in 10, July, 2009]

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Authors and Affiliations

  1. Department of Vehicle Engineering, Yung-Ta Institute of Technology and Commerce, 316, Chung Shan Road, Linlo, PingTung Hsien, Taiwan, 909

    Janus S. Liang

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  1. Janus S. Liang
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Correspondence to Janus S. Liang.

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Liang, J.S. A troubleshooting process planning using knowledge base and distributed database approach. Int J Adv Manuf Technol 54, 701–719 (2011). https://doi.org/10.1007/s00170-010-2952-4

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  • DOI: https://doi.org/10.1007/s00170-010-2952-4

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