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Execution and evaluation of enterprise models in IEM/MO2GO based on Petri net

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A Correction to this article was published on 20 March 2018

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Abstract

Because the growth of internet of things (IOT) technology, stakeholders who come from different research areas (information modeling area, dynamic process modeling area, and so on) will very easily and simultaneously evaluate and control the manufacturing process from all over the world. Therefore, there is an urgent need for a comprehensive enterprise modeling methodology with the integration of information modeling and dynamic process modeling method. However, it is known that there is limited research on the realization of a modeling methodology that can simultaneously handle information modeling and dynamic process modeling. The method for object-oriented business process optimization (MO2GO) system performs modeling in terms of information and process. However, the process modeling part in this system is static. Meanwhile, the Petri net mathematical modeling language has strong dynamic simulation capability. Thus, our main contribution is to analyze the characteristics of Petri net, which would be helpful to the dynamic process modeling realization in the MO2GO system, and integrate Petri net engine into the MO2GO system to allow a static process model to become dynamic. In here, the system can not only display a simulated manufacturing process but also calculate actual information (time and cost) for a final manufactured product. Therefore, it is possible for the system to handle both information modeling and dynamic process modeling. Finally, the MO2GO system will be more competitive in the future industry.

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Change history

  • 20 March 2018

    The original version of this article contained a mistake.

References

  1. Gubbi J, Buyya R, Marusic S et al (2013) Internet of things (IoT): a vision, architectural elements, and future directions[J]. Futur Gener Comput Syst 29(7):1645–1660

    Article  Google Scholar 

  2. Handbook of Research on Estimation and Control Techniques in E-learning Systems[M]. IGI Global, 2015.

  3. Qiao L, Kao S, Zhang Y (2011) Manufacturing process modelling using process specification language[J]. Int J Adv Manuf Technol 55(5–8):549–563

    Article  Google Scholar 

  4. Krogstie J, Sindre G, Jørgensen H (2006) Process models representing knowledge for action: a revised quality framework[J]. Eur J Inf Syst 15(1):91–102

    Article  Google Scholar 

  5. Turner BN, Strong R, Gold SA (2014) A review of melt extrusion additive manufacturing processes: I. Process design and modeling[J]. Rapid Prototyp J 20(3):192–204

    Article  Google Scholar 

  6. Chryssolouris G (2013) Manufacturing systems: theory and practice, Springer Science and Business Media

  7. Chryssolouris G, Anifantis N, Karagiannis S (1998) An approach to the dynamic modelling of manufacturing systems. Int J Prod Res 36(2):475–483

    Article  MATH  Google Scholar 

  8. Faris H, Sheta AF, Öznergiz E (2016) MGP–CC: a hybrid multigene GP–cuckoo search method for hot rolling manufacture process modelling[J]. Syst Sci Control Eng 4(1):39–49

    Article  Google Scholar 

  9. Berio G, Vernadat F (2001) Enterprise modelling with CIMOSA: Functional and organizational aspects. Prod Plan Control 12(2):128–136

    Article  Google Scholar 

  10. Petersen SA, Krogstie J (2013) The World Out There: From Systems Modelling to Enterprise Modelling. In Enterprise,Business-Process and Information Systems Modelling, 456–465, Springer Berlin Heidelberg

  11. Lirong S, Jing L, Meimei X (2014) Embedded in the society: on social enterprise model from enterprise production factors. Henan Soc Sci

  12. Kosanke K, Vernadat F, Zelm M (2015) Means to enable enterprise interoperation: CIMOSA object capability profiles and CIMOSA collaboration view. Annu Rev Control 39:94–101

    Article  Google Scholar 

  13. Mendling J (2007) Detection and prediction of errors in EPC business process models, Doctoral dissertation, Wirtschaftsuniversität Wien

  14. Accorsi R, Lehmann A (2012) Automatic information flow analysis of business process models, in international conference on business process management, 172–187. Springer, Berlin Heidelberg

    Google Scholar 

  15. White SA (2004) Introduction to BPMN, IBM Cooperation, 2(0), 0

  16. Cecil J (2001) Computer-aided fixture design–a review and future trends. Int J Adv Manuf Technol 18(11):790–793

    Article  Google Scholar 

  17. Petri CA, Reisig W (2008) Petri net. Scholarpedia 3(4):6477

    Article  Google Scholar 

  18. Kosanke K, Vernadat F, Zelm M (1999) CIMOSA: enterprise engineering and integration. Comput Ind 40(2):83–97

    Article  Google Scholar 

  19. Mendling J, Nüttgens M (2006) EPC markup language (EPML): an XML-based interchange format for event-driven process chains (EPC), Information Systems and e-Business Management 4(3):245–263

  20. Dorador JM, Young RI (2000) Application of IDEF0, IDEF3 and UML methodologies in the creation of information models. Int J Comput Integr Manuf 13(5):430–445

    Article  Google Scholar 

  21. Williams T (1998) The Purdue enterprise reference architecture and methodology (PERA), handbook of life cycle engineering: concepts, models, and technologies, 289

  22. Jordan D, Evdemon J, Alves A, Arkin A, Askary, S., Barreto, C., ... and Guízar, A. (2007) Web services business process execution language version 2.0. OASIS standard, 11(120):5

  23. Ng T, Palaneeswaran E, Kumaraswamy M (2012) Costs and benefits of ISO9000-based quality management systems to construction contractors. Constr Econ Build 8(2):23–29

    Google Scholar 

  24. Mertins K, Jochem R (2001) Integrated enterprise modelling: A method for the management of change. Prod Plan Control 12(2):137–145

    Article  Google Scholar 

  25. Mertins K, Jochem R (2005) Architectures, methods and tools for enterprise engineering. Int J Prod Econ 98(2):179–188

    Article  Google Scholar 

  26. Bhagwat R, Sharma MK (2007) Performance measurement of supply chain management: a balanced scorecard approach. Comput Ind Eng 53(1):43–62

    Article  Google Scholar 

  27. Liu S, Zeng R, Sun Z, He X (2014) Bounded model checking high level petri nets in pipe+ verifier,In International Conference on Formal Engineering Methods, 348–363,Springer International Publishing

  28. Gay DM (2015) The AMPL modeling language: an aid to formulating and solving optimization problems, in numerical analysis and optimization, 95–116, Springer international publishing

  29. Lucas SM, Reynolds TJ (2005) Learning deterministic finite automata with a smart state labeling evolutionary algorithm. IEEE Trans Pattern Anal Mach Intell 27(7):1063–1074

    Article  Google Scholar 

  30. Bisschop J, Roelofs M (2006) Aimms-User's guide, Lulu. Com

  31. Yan R, Jackson LM, Dunnett SJ (2017) Automated guided vehicle mission reliability modelling using a combined fault tree and Petri net approach. Int J Adv Manuf Technol, 1–13

  32. Bernus P, Mertins K, Schmidt GJ (Eds) (2013) Handbook on architectures of information systems, Springer Science and Business Media

  33. Ott M (1994) Conceptual design and implementation of a graphical workflow-modelling editor in the context of distributed groupware-databases, University of Padeborn

  34. Liu X, Xu X, Deng S (2009) A petri-net-based simulation and optimization approach for IEM and EI, in interoperability for enterprise software and applications China, 2009, 129-134, IESA'09. International Conference on IEEE

  35. Raedts I, Petkovic M, Usenko YS, van der Werf JME, Groote JF, Somers LJ (2007) Transformation of BPMN models for behaviour analysis, MSVVEIS, 2007, 126–137

  36. Production line, Toyota Company, http://www.toyotavn.com.vn/en/production/production-line/

  37. Rossi A, Lamonaca G, Pinacci P et al (2012) Development of a dynamic model of a palladium membrane reactor for water gas shift[J]. Energy Procedia 23:161–170

    Article  Google Scholar 

  38. Enstone LJ, Clark MF (2006) BPMN and simulation[J]. Lanner Group Limited

  39. Semanco P, Marton D (2013) Simulation tools evaluation using theoretical manufacturing model[J]. Acta Polytech Hung 10(2):193–204

    Google Scholar 

  40. Elder M (2014) DES view on simulation modelling: SIMUL8[J]. Discrete- Event Simulation and System Dynamics for Management Decision Making, 199–214

  41. Sedláček M (2017) The use of simulation models in solving the problems of merging two plants of the company[J]. Open Eng 7(1):31–36

    Google Scholar 

  42. Van Der Aalst WMP (2013) Business process management: a comprehensive survey[J]. ISRN Softw Eng, 2013

  43. Peterson JL (1981) Petri net theory and the modeling of systems[J]

  44. Reisig W (2012) A primer in Petri net design[M]. Springer Science & Business Media

  45. Gou H, Huang B, Liu W, et al (2001) Modeling distributed business processes of virtual enterprises based on the object-oriented approach and Petri nets[C]//Systems, Man, and Cybernetics, IEEE international conference on. IEEE, 2001, 3: 2052–2057

  46. Dong M, Chen FF (2005) Petri net-based workflow modelling and analysis of the integrated manufacturing business processes[J]. Int J Adv Manuf Technol 26(9–10):1163–1172

    Article  Google Scholar 

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Correspondence to Guangying Jin.

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The original version of this article was revised: Frank Walter has been corrected to Frank-Walter Jäkel.

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Jin, G., Jäkel, FW. Execution and evaluation of enterprise models in IEM/MO2GO based on Petri net. Int J Adv Manuf Technol 96, 4517–4537 (2018). https://doi.org/10.1007/s00170-018-1764-9

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  • DOI: https://doi.org/10.1007/s00170-018-1764-9

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