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Journal of Intelligent Manufacturing

Erschienen in:

17.12.2015

Cyber physical process monitoring systems

verfasst von: Jeff Morgan, Garret E. O’Donnell

Erschienen in: Journal of Intelligent Manufacturing | Ausgabe 6/2018

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Abstract

Manufacturing process monitoring systems is evolving from centralised bespoke applications to decentralised reconfigurable collectives. The resulting cyber-physical systems are made possible through the integration of high power computation, collaborative communication, and advanced analytics. This digital age of manufacturing is aimed at yielding the next generation of innovative intelligent machines. The focus of this research is to present the design and development of a cyber-physical process monitoring system; the components of which consist of an advanced signal processing chain for the semi-autonomous process characterisation of a CNC turning machine tool. The novelty of this decentralised system is its modularity, reconfigurability, openness, scalability, and unique functionality. The function of the decentralised system is to produce performance criteria via spindle vibration monitoring, which is correlated to the occurrence of sequential process events via motor current monitoring. Performance criteria enables the establishment of normal operating response of machining operations, and more importantly the identification of abnormalities or trends in the sensor data that can provide insight into the quality of the process ongoing. The function of each component in the signal processing chain is reviewed and investigated in an industrial case study.

Vorheriger Artikel Review, analysis and synthesis of prognostic-based decision support methods for condition based maintenance

Nächster Artikel Rule and branch-and-bound algorithm based sequencing of machining features for process planning of complex parts

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Abrishambaf, R., Hashemipour, M., & Bal, M. (2011). Integration of wireless sensor networks into the distributed intelligent manufacturing within the framework of IEC 61499 function blocks. In 2011 IEEE international conference on systems, man, and cybernetics (SMC). doi:10.1109/ICSMC.2011.6084204.

Alahakoon, D., & Yu, X. (2015). Smart electricity meter data intelligence for future energy systems: A survey. IEEE Transactions on Industrial Informatics. doi:10.1109/TII.2015.2414355.

Brazel, E., Hanley, R., Cullinane, R., & O’Donnell, G. E. (2013). Position-oriented process monitoring in freeform abrasive machining. The International Journal of Advanced Manufacturing Technology, 69(5–8), 1443–1450. doi:10.1007/s00170-013-5111-x.CrossRef

Calvo, I., Etxeberria-Agiriano, I., & Noguero, A. (2012). Distribution middleware technologies for cyber physical systems. In 2012 9th international conference on remote engineering and virtual instrumentation (REV). doi:10.1109/REV.2012.6293151.

Colombo, A. W., Mendes, J. M., Leitao, P., & Karnouskos, S. (2012). Service-oriented SCADA and MES supporting petri nets based orchestrated automation systems. In IECON 2012—38th annual conference on ieee industrial electronics society. doi:10.1109/IECON.2012.6389076.

Cugola, G., & Margara, A. (2012). Complex event processing with T-REX. Journal of Systems and Software, 85, 1709–1728. doi:10.1016/j.jss.2012.03.056.CrossRef

Diaz, N., Helu, M., Jarvis, A., Tönissen, S., Dornfeld, D., & Schlosser, R. (2009). Strategies for minimum energy operation for precision machining. The Proceedings of MTTRF 2009 Annual Meeting, 1, 6. doi:10.1007/978-3-642-19692-8.

Eckstein, M., & Mankova, I. (2012). Monitoring of drilling process for highly stressed aeroengine components. Procedia CIRP, 1(1), 587–592. doi:10.1016/j.procir.2012.04.104.CrossRef

Evans, P., & Annunziata, M. (2012). Industrial internet: Pushing the boundaries of minds and machines. General Electric. http://www.ge.com/docs/chapters/Industrial_Internet.pdf.

Ferreira, L., Putnik, G., Cunha, M., Putnik, Z., Castro, H., Alves, C., et al. (2013). Cloudlet architecture for dashboard in cloud and ubiquitous manufacturing. Procedia CIRP, 12, 366–371. doi:10.1016/j.procir.2013.09.063.CrossRef

Gao, R., Wang, L., Teti, R., Dornfeld, D., Kumara, S., Mori, M., et al. (2015). Cloud-enabled prognosis for manufacturing. CIRP Annals-Manufacturing Technology. doi:10.1016/j.cirp.2015.05.011.

Giret, A., & Botti, V. (2004). Holons and agents. Journal of Intelligent Manufacturing. doi:10.1023/B:JIMS.0000037714.56201.a3.

He, Y., Liu, B., Zhang, X., Gao, H., & Liu, X. (2012). A modeling method of task-oriented energy consumption for machining manufacturing system. Journal of Cleaner Production, 23, 167–174. doi:10.1016/j.jclepro.2011.10.033.CrossRef

Herlufsen, H., Gade, S., & Zaveri, H. K. (2008). Analyzers and signal generators. Handbook of Noise and Vibration Control, 470–485. doi:10.1002/9780470209707.ch40.

Hon, K. K. B. (2005). Performance and evaluation of manufacturing systems. CIRP Annals-Manufacturing Technology, 54(2), 139–154. doi:10.1016/S0007-8506(07)60023-7. http://www.sciencedirect.com/science/article/pii/S0007850607600237.

Izaguirre, J. A. G., Lobov, A., & Lastra, J. L. M. (2011). OPC-UA and DPWS interoperability for factory floor monitoring using complex event processing. In 2011 9th IEEE international conference on industrial informatics (INDIN). Glendale, AZ: IEEE. doi:10.1109/INDIN.2011.6034874.

Kehoe, B., Patil, S., Abbeel, P., & Goldberg, K. (2015). A survey of research on cloud robotics and automation. IEEE Transactions on Automation Science and Engineering, 12(2), 1–12. doi:10.1109/TASE.2014.2376492. http://www.scopus.com/inward/record.url?eid=2-s2.0-84924680020&partnerID=tZOtx3y1.

Li, Y., Liu, Q., Xiong, J., & Wang, J. (2015). Research on data-sharing and intelligent CNC machining system. In 2015 IEEE international conference on mechatronics and automation (ICMA). doi:10.1109/ICMA.2015.7237557.

Lilly, J. H. (2010). Fuzzy control and identification. Hoboken: Wiley.CrossRef

Lindgren, P., Pietrzak, P., & Makitaavola, H. (2013). Real-time complex event processing using concurrent reactive objects. In 2013 IEEE international conference on industrial technology (ICIT). Cape Town: IEEE. doi:10.1109/ICIT.2013.6505984.

Liu, M., Ma, J., Lin, L., Ge, M., Wang, Q., & Liu, C. (2014). Intelligent assembly system for mechanical products and key technology based on internet of things. Journal of Intelligent Manufacturing, 1–29, doi:10.1007/s10845-014-0976-6.

Mitchell, H. B. (2007). Multi-Sensor data fusion: An introduction. doi:10.1007/978-3-540-71559-7.

Monostori, L. (2014). Cyber-physical production systems: Roots, expectations and R&D challenges. Procedia CIRP, 17, 9–13. doi:10.1016/j.procir.2014.03.115.CrossRef

Morgan, J., & O’Donnell, G. E. (2014a). The cyber physical implementation of cloud manufacturing monitoring systems. In 9th CIRP conference on intelligent computation in manufacturing engineering. Capri: Elsevier.

Morgan, J., & O’Donnell, G. E. (2014b). A service oriented reconfigurable process monitoring system-enabling cyber physical systems. Journal of Machine Engineering, 14(2), 116–129.

Morgan, J., & O’Donnell, G. E. (2015). Enabling a ubiquitous and cloud manufacturing foundation with field-level service-oriented architecture. In International Journal of Computer Integrated Manufacturing. doi:10.1080/0951192X.2015.1032355.

Morgan, J., O’Driscoll, E., & O’Donnell, G. E. (2013). Data interoperability for reconfigurable manufacturing process monitoring systems. Journal of Machine Engineering, 13(1), 64–79.

Neto, L., Reis, J., Guimaraes, D., & Goncalves, G. (2015). Sensor cloud: Smart component framework for reconfigurable diagnostics in intelligent manufacturing environments. In 2015 IEEE 13th international conference on industrial informatics (INDIN). doi:10.1109/INDIN.2015.7281991.

Paarmann, L. (2003). Design and analysis of analog filters: A signal processing perspective. Dordrecht: Kluwer.

Pietrzak, P., Lindgren, P., & Makitaavola, H. (2012). Towards a lightweight CEP engine for embedded systems. In IECON 2012—38th annual conference on IEEE industrial electronics society. doi:10.1109/IECON.2012.6389134.

Pinto, J., Marco Mendes, J., Leitão, P., Colombo, A. W., Bepperling, A., & Restivo, F. (2009). Decision support system for Petri nets enabled automation components. In IEEE international conference on industrial informatics (INDIN) (pp. 289–294). doi:10.1109/INDIN.2009.5195819.

Pople, S. (1999). Electromagnetic induction. In S. Pople (Ed.), Advanced physics through diagrams (pp. 78–79). Oxford: Oxford Universoty Press.

Savio, D., Karnouskos, S., Wuwer, D., & Bangemann, T. (2008). Dynamically optimized production planning using cross-layer SOA. In 32nd annual IEEE international computer software and applications, 2008. COMPSAC ’08. Turku: IEEE. doi:10.1109/COMPSAC.2008.219.

Schmitt, R., Bittencourt, J. L., & Bonefeld, R. (2011). Modelling machine tools for self-optimisation of energy consumption. In Glocalized solutions for sustainability in manufacturing—Proceedings of the 18th CIRP international conference on life cycle engineering (pp. 253–257). doi:10.1007/978-3-642-19692-8-44.

Song, K., Seniuk, G. T. G., Kozinski, J. A., Zhang, W., & Gupta, M. M. (2015). An innovative fuzzy-neural decision analyzer for qualitative group decision making. International Journal of Information Technology & Decision Making, 14(03), 659–696. doi:10.1142/S0219622015500029.

Tan, L., & Jiang, J. (2013). Digital signal processing systems, basic filtering types, and digital filter realizations. In Digital signal processing: Fundamentals and applications. doi:10.1016/B978-0-12-415893-1.00006-8.

Tao, F., Zuo, Y., Da Xu, L., & Zhang, L. (2014). IoT-based intelligent perception and access of manufacturing resource toward cloud manufacturing. IEEE Transactions on Industrial Informatics. doi:10.1109/TII.2014.2306397.

Teti, R., Jemielniak, K., O’Donnell, G., & Dornfeld, D. (2010). Advanced monitoring of machining operations. CIRP Annals-Manufacturing Technology, 59, 717–739.CrossRef

Trentesaux, D. (2009). Distributed control of production systems. Engineering Applications of Artificial Intelligence, 22(7), 971–978. doi:10.1016/j.engappai.2009.05.001. http://www.sciencedirect.com/science/article/pii/S0952197609000797.

Trout, C. M. (2010). Essentials of electric motors and controls. Burlington: Jones and Bartlett Publishers.

Vachtsevanos, G., Lewis, F., Roemer, M., Hess, A., & Wu, B. (2007). Intelligent fault diagnosis and prognosis for engineering systems. doi:10.1002/9780470117842.

Vijayaraghavan, A., & Dornfeld, D. (2010). Automated energy monitoring of machine tools. CIRP Annals-Manufacturing Technology, 59(1), 21–24. doi:10.1016/j.cirp.2010.03.042.CrossRef

Walzer, K., Rode, J., Wünsch, D., & Groch, M. (2008). Event-driven manufacturing: Unified management of primitive and complex events for manufacturing monitoring and control. In IEEE international workshop on factory communication systems—Proceedings, WFCS (pp. 383–391). doi:10.1109/WFCS.2008.4638734.

Wang, X., Wong, T. N., & Wang, G. (2012). Service-oriented architecture for ontologies supporting multi-agent system negotiations in virtual enterprise. Journal of Intelligent Manufacturing, 23(4), 1331–1349. doi:10.1007/s10845-010-0469-1.CrossRef

Zhang, W. J., & van Luttervelt, C. A. (2011). Toward a resilient manufacturing system. CIRP Annals-Manufacturing Technology, 60(1), 469–472. doi:10.1016/J.Cirp.2011.03.041.CrossRef

Titel: Cyber physical process monitoring systems
verfasst von: Jeff Morgan
Garret E. O’Donnell
Publikationsdatum: 17.12.2015
Verlag: Springer US
Erschienen in: Journal of Intelligent Manufacturing / Ausgabe 6/2018
Print ISSN: 0956-5515
Elektronische ISSN: 1572-8145
DOI: https://doi.org/10.1007/s10845-015-1180-z

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