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Informatics Platform for Designing and Deploying e-Manufacturing Systems

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Collaborative Design and Planning for Digital Manufacturing

Abstract

e-Manufacturing is a transformation system that enables manufacturing operations to achieve near-zero-downtime performance, as well as to synchronise with the business systems through the use of informatics technologies. To successfully implement an e-manufacturing system, a systematic approach in designing and deploying various computing tools (algorithms, software and agents) with a scalable hardware and software platform is a necessity. In this chapter, we will first give an introduction to an e-manufacturing system including its fundamental elements and requirements to meet the changing needs of the manufacturing industry in today’s globally networked business environment. Second, we will introduce a methodology for the design and development of advanced computing tools to convert data to information in manufacturing applications. A toolbox that consists of modularised embedded algorithms for signal processing and feature extraction, performance assessment, diagnostics and prognostics for diverse machinery prognostic applications, will be examined. Further, decision support tools for reduced response time and prioritised maintenance scheduling will be discussed. Third, we will introduce a reconfigurable, easy to use, platform for various applications. Finally, case studies for smart machines and other applications will be used to demonstrate the selected methods and tools.

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References

  1. Koc, M., Ni, J. and Lee, J., 2002, “Introduction to e-manufacturing,” In Proceedings of the 5th International Conference on Frontiers of Design and Manufacturing.

    Google Scholar 

  2. Kelle, P. and Akbulut, A., 2005, “The role of ERP tools in supply chain information sharing, cooperation, and cost optimisation,” International Journal of Production Economics, 9394 (Special Issue), pp. 41–52.

    Article  Google Scholar 

  3. Akkermans, H.A., Bogerd, P., Yucesan, E. and Van Wassenhove, L.N., 2003, “The impact of ERP on supply chain management: exploratory findings from a European Delphi study,” European Journal of Operational Research, 146(2), pp. 284–301.

    Article  MATH  Google Scholar 

  4. Da, T. (ed.), 2004, Supply ChainsA Manager's Guide, Addison-Wesley, Boston, MA.

    Google Scholar 

  5. Andersen, H. and Jacobsen, P., 2000, Customer Relationship Management: A Strategic Imperative in the World of E-Business, John Wiley & Sons Canada, Toronto.

    Google Scholar 

  6. Cheng, F.T., Shen, E., Deng, J.Y. and Nguyen, K., 1999, “Development of a system framework for the computer-integrated manufacturing execution system: a distributed object-oriented approach,” International Journal of Computer Integrated Manufacturing, 12(5), pp. 384–402.

    Article  Google Scholar 

  7. Lee, J., 2003, “E-manufacturing – fundamental, tools, and transformation,” Robotics and Computer-Integrated Manufacturing, 19(6), pp. 501–507.

    Article  Google Scholar 

  8. Koc, M. and Lee, J., 2002, “E-manufacturing and e-maintenance – applications and benefits,” In International Conference on Responsive Manufacturing, Gaziantep, Turkey.

    Google Scholar 

  9. Ge, M., Du, R., Zhang, G.C. and Xu, Y.S., 2004, “Fault diagnosis using support vector machine with an application in sheet metal stamping operations,” Mechanical Systems and Signal Processing, 18(1), pp. 143–159.

    Article  Google Scholar 

  10. Li, Z.N., Wu, Z.T., He, Y.Y. and Chu, F.L., 2005, “Hidden Markov model-based fault diagnostics method in speed-up and speed-down process for rotating machinery,” Mechanical Systems and Signal Processing, 19(2), pp. 329–339.

    Article  Google Scholar 

  11. Wu, S.T. and Chow, T.W.S., 2004, “Induction machine fault detection using SOM-based RBF neural networks,” IEEE Transactions on Industrial Electronics, 51(1), pp. 183–194.

    Article  Google Scholar 

  12. Wang, J.F., Tse, P.W., He, L.S. and Yeung, R.W., 2004, “Remote sensing, diagnosis and collaborative maintenance with web-enabled virtual instruments and miniservers,” International Journal of Advanced Manufacturing Technology, 24(9–10), pp. 764–772.

    Google Scholar 

  13. Chen, Z., Lee, J. and Qiu, H., 2005, “Intelligent infotronics system platform for remote monitoring and e-maintenance,” International Journal of Agile Manufacturing, 8(1), pp. 3–11.

    Google Scholar 

  14. Qu, R., Xu, J., Patankar, R., Yang, D., Zhang, X. and Guo, F., 2006, “An implementation of a remote diagnostic system on rotational machines,” Structural Health Monitoring, 5(2), pp. 185–193.

    Article  Google Scholar 

  15. Han, T. and Yang, B.S., 2006, “Development of an e-maintenance system integrating advanced techniques,” Computers in Industry, 57(6), pp. 569–580.

    Article  MathSciNet  Google Scholar 

  16. Chau, P.Y.K. and Tam, K.Y., 2000, “Organisational adoption of open systems: a ‘technology-push, need-pull’ perspective,” Information & Management, 37(5), pp. 229–239.

    Article  Google Scholar 

  17. Lee, J., 1995, “Machine performance monitoring and proactive maintenance in computer-integrated manufacturing: review and perspective,” International Journal of Computer Integrated Manufacturing, 8(5), pp. 370–380.

    Article  Google Scholar 

  18. Lee, J., 1996, “Measurement of machine performance degradation using a neural network model,” Computers in Industry, 30(3), pp. 193–209.

    Article  Google Scholar 

  19. MIMOSA, www.mimosa.org.

    Google Scholar 

  20. Djurdjanovic, D., Lee, J. and Ni, J., 2003, “Watchdog Agent – an infotronics-based prognostics approach for product performance degradation assessment and prediction,” Advanced Engineering Informatics, 17(3–4), pp. 109–125.

    Article  Google Scholar 

  21. Jardine, A.K.S., Lin, D. and Banjevic, D., 2006, “A review on machinery diagnostics and prognostics implementing condition-based maintenance,” Mechanical Systems and Signal Processing, 20(7), pp. 1483–1510.

    Article  Google Scholar 

  22. Sun, Z. and Chang, C.C., 2002, “Structural damage assessment based on wavelet packet transform,” Journal of Structural Engineering, 128(10), pp. 1354–1361.

    Article  Google Scholar 

  23. Yan, J. and Lee, J., 2005, “Degradation assessment and fault modes classification using logistic regression,” Transactions of the ASME, Journal of Manufacturing Science and Engineering, 127(4), pp. 912–914.

    Article  Google Scholar 

  24. Lemm, J.C., 1999, “Mixtures of Gaussian process priors,” In IEEE Conference Publication.

    Google Scholar 

  25. Ocak, H. and Loparo, K.A., 2005, “HMM-based fault detection and diagnosis scheme for rolling element bearings,” Transactions of the ASME, Journal of Vibration and Acoustics, 127(4), pp. 299–306.

    Article  Google Scholar 

  26. Huang, S.H., Hao, X. and Benjamin, M., 2001, “Automated knowledge acquisition for design and manufacturing: the case of micromachined atomizer,” Journal of Intelligent Manufacturing, 12(4), pp. 377–391.

    Article  Google Scholar 

  27. Liu, J., Ni, J., Djurdjanovic, D. and Lee, J., 2004, “Performance similarity based method for enhanced prediction of manufacturing process performance,” In American Society of Mechanical Engineers, Manufacturing Engineering Division, MED.

    Google Scholar 

  28. Govers, C.P.M., 1996, “What and how about quality function deployment (QFD),” International Journal of Production Economics, 4647, pp. 575–585.

    Article  Google Scholar 

  29. ReVelle, J. (ed.), 1998, The QFD Handbook, John Wiley and Sons.

    Google Scholar 

  30. Carnero, M.C., 2005, “Selection of diagnostic techniques and instrumentation in a predictive maintenance program: a case study,” Decision Support Systems, pp. 539–555.

    Google Scholar 

  31. Tse, P.W., Peng, Y.H. and Yam, R., 2001, “Wavelet analysis and envelope detection for rolling element bearing fault diagnosis – their effectiveness and flexibilities,” Journal of Vibration and Acoustics, 123(3), pp. 303–310.

    Article  Google Scholar 

  32. Qiu, H. and Lee, J., 2004, “Feature fusion and degradation detection using selforganising map,” In Proceedings of the 2004 International Conference on Machine Learning and Applications.

    Google Scholar 

  33. DeJong, C., 2008, “Faster cutting: cut in balance,” www.autofieldguide.com.

    Google Scholar 

  34. Al-Shurafa, A.M., 2003, “Determination of balancing quality limits,” www.plantmaintenance.com.

    Google Scholar 

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Lee, J., Liao, L., Lapira, E., Ni, J., Li, L. (2009). Informatics Platform for Designing and Deploying e-Manufacturing Systems. In: Wang, L., Nee, A. (eds) Collaborative Design and Planning for Digital Manufacturing. Springer, London. https://doi.org/10.1007/978-1-84882-287-0_1

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  • DOI: https://doi.org/10.1007/978-1-84882-287-0_1

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84882-286-3

  • Online ISBN: 978-1-84882-287-0

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