Data-Driven Modelling: Towards Interpreting and Understanding Process Evolution of In-Service Engineering Projects

  • Lei ShiEmail author
  • Linda Newnes
  • Steve Culley
  • James Gopsill
  • Chris Sinder
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 467)


Product service plays an essential role in day-to-day operations of nowadays manufacturing industries. However, the changing demands of the market/customers, the increasing complexity of product functionalities and the extended product lifecycles present challenges to related In-Service projects. In order to handle the increasing number of projects and to control the costs and resource consumptions, it is critical to improve the efficiency and automation of process management. Within this context, this paper introduces some data-driven approaches to interpret and represent changes of project process over time in an automatic manner. These approaches aim to help project actors improve their understanding of process structure and the efficiency of process management, and also enable them to investigate process changes from more dynamic perspectives. To evaluate the approaches, a dataset from an aerospace organisation is considered in this paper.


In-Service Engineering project process Process management Process evolution 



The research reported in this paper is funded by Engineering and Physical Sciences Research Council (EP/K014196/1). The authors would like to thank the industrial collaborators and their engineers for their input and support on this project.


  1. 1.
    Gebauer, H., Krempl, R., Fleisch, E.: Service development in traditional product manufacturing companies. Eur. J. Innov. Manag. 11(2), 219–240 (2008)CrossRefGoogle Scholar
  2. 2.
    Mont, O.K.: Clarifying the concept of product–service system. J. Cleaner Prod. 10(3), 237–245 (2002)CrossRefGoogle Scholar
  3. 3.
    Neely, A., Benedettini, O., Visnjic, I.: The servitization of manufacturing: further evidence. In: 18th European Operations Management Association Conference (2011)Google Scholar
  4. 4.
    Baines, T.S., Lightfoot, H.W., Evans, S., Neely, A., Greenough, R., Peppard, J., Roy, R., Shehab, E., Braganza, A., Tiwari, A., Alcock, J.R., Angus, J.P., Bastl, M., Cousens, A., Irving, P., Johnson, M., Kingston, J., Lockett, H., Martinez, V., Michele, P., Tranfield, D., Walton, I.M., Wilson, H.: State-of-the-art in product-service systems. Proc. Inst. Mech. Eng., Part B: J. Eng. Manuf. 221(10), 1543–1552 (2007)CrossRefGoogle Scholar
  5. 5.
    Kreye, M., Goh, Y.M., Newnes, L.B.: Uncertainty in through life costing within the concept of product service systems: a game theoretic approach. In: DS 58-7: Proceedings of ICED 09, The 17th International Conference on Engineering Design, vol. 7, Design for X/Design to X, Palo Alto, CA, USA, 24−27 August 2009Google Scholar
  6. 6.
    Carey, E., Culley, S., Weber, F.: Establishing key elements for handling in-service information and knowledge. In: The 19th International Conference on Engineering Design, ICED13, Seoul, South Korea (2013)Google Scholar
  7. 7.
    Xie, Y., Culley, S., Weber, F.: Applying context to organize unstructured information in aerospace industry. In: DS 68-6: Proceedings of the 18th International Conference on Engineering Design (ICED 11), Impacting Society Through Engineering Design, vol. 6, Design Information and Knowledge, Lyngby/Copenhagen, Denmark, 15−19 August 2011 (2011)Google Scholar
  8. 8.
    Van den Bergh, J., Thijs, S., Viaene, S.: Focusing on BPM’s human factor: an interview with Els Van Keymeulen of Schoenen Torfs. Transforming Through Processes. SpringerBreifs in Business Process Management, pp. 41–43. Springer International Publishing, Switzerland (2014)CrossRefGoogle Scholar
  9. 9.
    Han, Y., Kauranen, A., Kristola, E., Merinen, J.: Human interaction management–adding human factors into business processes management. Special report for information systems integration, Helsinki University (2007)Google Scholar
  10. 10.
    Bettis-Outland, H.: Decision-making’s impact on organizational learning and information overload. J. Bus. Res. 65(6), 814–820 (2012)CrossRefGoogle Scholar
  11. 11.
    Pfeffer, J., Sutton, R.I.: The Knowing-doing Gap: How Smart Companies Turn Knowledge into Action. Harvard Business Press, Brighton (2013)Google Scholar
  12. 12.
    Vandermerwe, S., Rada, J.: Servitization of business: adding value by adding services. Eur. Manage. J. 6(4), 314–324 (1988)CrossRefGoogle Scholar
  13. 13.
    Ming, X.G., Yan, J.Q., Wang, X., Li, S., Lu, W.F., Peng, Q., Ma, Y.: Collaborative process planning and manufacturing in product lifecycle management. Comput. Ind. 59(2), 154–166 (2008)CrossRefGoogle Scholar
  14. 14.
    Hicks, B.: The language of collaborative engineering projects. In: DS 75-6: Proceedings of the 19th International Conference on Engineering Design (ICED13), Design for Harmonies, vol. 6, Design Information and Knowledge. Seoul, Korea (2013)Google Scholar
  15. 15.
    Huls, D.: Current Market Outlook 2014−2033. Boeing Commercial Airplanes, USA (2014)Google Scholar
  16. 16.
    van der Aalst, W.M., ter Hofstede, A.H., Weske, M.: Business process management: a survey. In: Aalst, W.M., Hofstede, A.H., Weske, M. (eds.) BPM 2003. LNCS, vol. 2678, pp. 1–12. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  17. 17.
    Davenport, T.H.: Process Innovation: Reengineering Work Through Information Technology. Harvard Business Press, Brighton (2013)Google Scholar
  18. 18.
    Laguna, M., Marklund, J.: Business Process Modeling, Simulation and Design. CRC Press, Boca Raton (2013)Google Scholar
  19. 19.
    Banuelas Coronado, R., Antony, J.: Critical success factors for the successful implementation of six sigma projects in organisations. TQM Mag. 14(2), 92–99 (2002)CrossRefGoogle Scholar
  20. 20.
    Melão, N., Pidd, M.: A conceptual framework for understanding business processes and business process modelling. Inf. Syst. J. 10(2), 105–129 (2000)CrossRefGoogle Scholar
  21. 21.
    Grambow, G., Oberhauser, R., Reichert, M.: Event-driven exception handling for software engineering processes. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds.) BPM Workshops 2011, Part I. LNBIP, vol. 99, pp. 414–426. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  22. 22.
    Weijters, A., Van der Aalst, W.: Process mining: discovering workflow models from event-based data. In: Belgium-Netherlands Conference on Artificial Intelligence. Citeseer (2001)Google Scholar
  23. 23.
    Chen, H., Chiang, R.H., Storey, V.C.: Business intelligence and analytics: from big data to big impact. MIS Q. 36(4), 1165–1188 (2012)Google Scholar
  24. 24.
    Shi, L., Gopsill, J.A., Newnes, L., Culley, S.: A sequence-based approach to analysing and representing engineering project normality. In: 2014 IEEE 26th International Conference on Tools with Artificial Intelligence (ICTAI), pp. 967–973. Limassol, Cyprus (2014)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2016

Authors and Affiliations

  • Lei Shi
    • 1
    Email author
  • Linda Newnes
    • 1
  • Steve Culley
    • 1
  • James Gopsill
    • 2
  • Chris Sinder
    • 2
  1. 1.Department of ManufacturingUniversity of BathBathUK
  2. 2.Department of ManufacturingUniversity of BristolBristolUK

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