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Design and analysis of a rule-based knowledge system supporting intelligent dispatching and its application in the TFT-LCD industry

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Abstract

As flexibility and agility become key success factors of a competitive manufacturing enterprise, the ability to support the short term decision making of manufacturing planning, scheduling, and dispatching becomes a critical issue. This research presents a rule-based knowledge system run on the Java Expert System Shell (JESS) platform to addresses how engineering knowledge can be dynamically represented and efficiently utilized in job dispatching. The knowledge system, called Intelligent Dispatching Decision Support System (IDDSS), is designed and implemented using the rule-based inference and reasoning approach. The distinctive technical contributions of IDDSS focus on three critically integrated elements: (1) a visualized rule editor, (2) a knowledge object data gateway, and (3) an embedded application component. Furthermore, a case study of the thin-film transistor liquid-crystal display (TFT-LCD) panel repair line is applied to demonstrate the rule-based knowledge system for agile TFT-LCD repair job dispatching.

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References

  1. Xu Y, Yen DC, Lin B, Chou DC (2002) Adopting customer relationship management technology. Ind Manage Data Syst 102(8):442–452

    Article  Google Scholar 

  2. Santhanam R, Elam J (1998) A survey of knowledge-based systems research in decision sciences (1980–1995). J Oper Res Soc 49(5):445–457

    Article  Google Scholar 

  3. Wagner WP, Najdawi MK, Chung QB (2001) Selection of knowledge acquisition techniques based upon the problem domain characteristics of production and operations management expert systems. Expert Syst 18(2):76–87

    Article  Google Scholar 

  4. Chtourou H, Masmoudi W, Maalej A (2005) An expert system for manufacturing systems machine selection. Expert Syst Appl 28:461–467

    Article  Google Scholar 

  5. Metaxiotis KS, Psarras JE (2003) Expert systems in business: applications and future directions for the operations researcher. Ind Manage Data Syst 103(5):361–368

    Article  Google Scholar 

  6. Xuewen C, Siyu Z, Jun C, Xueyu R (2005) Research of knowledge-based hammer forging design support system. Int J Adv Manuf Technol 27(1–2):25–32

    Article  Google Scholar 

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

    Article  Google Scholar 

  8. Bielawski L, Lewand R (1998) Expert systems development: building PC-based applications. QED Information Sciences, Inc, Wellesley, Massachusetts

  9. Souza MAF, Ferreira MAGV (2002) Designing reusable rule-based architectures with design patterns. Expert Syst Appl 23(4):395–403

    Article  Google Scholar 

  10. Wagner WP, Otto J, Chung QB (2002) Knowledge acquisition for expert systems in accounting and financial problem domains. Knowl-Based Syst 15(8):439–447

    Article  Google Scholar 

  11. Zhang WY, Tor SB, Britton GA (2001) A prototype knowledge-based system for conceptual synthesis of the design process. Int J Adv Manuf Technol 17:549–557

    Article  Google Scholar 

  12. Tor SB, Britton GA, Zhang WY (2005) A knowledge-based blackboard framework for stamping process planning in progressive die design. Int J Adv Manuf Technol 26(7–8):774–783

    Article  Google Scholar 

  13. Chiang ATA, Trappey AJC, Ku CC (2006) Using knowledge-based intelligent reasoning to support dynamic collaborative design. Int J Adv Manuf Technol 34:421–433

    Article  Google Scholar 

  14. Ozbayrak M, Bell R (2003) A knowledge-based decision support system for the management of parts and tools in FMS. Decis Support Syst 35:487–515

    Article  Google Scholar 

  15. Ho KKL, Lu M (2005) Web-based expert system for class schedule planning using JESS. Proceedings of the 2005 IEEE International conference on information reuse and integration, Las Vegas, Nevada, pp 166–171

  16. Abou-Ali MG, Khamis M (2003) TIREDDX: an integrated intelligent defects diagnostic system for tire production and service. Expert Syst Appl 24(3):247–259

    Article  Google Scholar 

  17. Liu SC, Liu SY (2003) An efficient expert system for machine fault diagnosis. Int J Adv Manuf Technol 21(9):691–698

    Article  Google Scholar 

  18. Chan CW (2005) An expert decision support system for monitoring and diagnosis of petroleum production and separation processes. Expert Syst Appl 29(1):131–143

    Article  Google Scholar 

  19. Yao YH, Lin GYP, Trappey AJC (2006) Using knowledge-based intelligent reasoning to support dynamic equipment diagnosis and maintenance. Int J Enterprise Inform Syst 2(1):17–29

    Google Scholar 

  20. Ngai EWT, Cheng TCE (2001) A knowledge-based system for supporting performance measurement of AMT projects: a research agenda. Int J Oper Prod Manage 1(1–2):223–232

    Article  Google Scholar 

  21. Rao MP, Miller DM, Lin B (2005) PET: an expert system for productivity analysis. Expert Syst Appl 29(2):300–309

    Article  Google Scholar 

  22. Duan Y, Edwards JS, Xu MX (2005) Web-based expert systems: benefits and challenges. Inf Manage 42(6):799–811

    Article  Google Scholar 

  23. Friedman-Hill, EJ (2001) JESS, the expert system shell for Java platform, version 6. Sandia National Laboratories, Livermore, California

  24. Eriksson H (2003) Using JessTab to integrate protégé and jess. IEEE Intell Syst 18(2):43–50

    Article  MathSciNet  Google Scholar 

  25. Hung SW (2006) Competitive strategies for Taiwan’s thin film transistor-liquid crystal display (TFT-LCD) industry. Technol Soc 28:349–361

    Article  MathSciNet  Google Scholar 

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Correspondence to Amy J. C. Trappey.

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Trappey, A.J.C., Lin, G.Y.P., Ku, C.C. et al. Design and analysis of a rule-based knowledge system supporting intelligent dispatching and its application in the TFT-LCD industry. Int J Adv Manuf Technol 35, 385–393 (2007). https://doi.org/10.1007/s00170-007-1177-7

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  • DOI: https://doi.org/10.1007/s00170-007-1177-7

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