Abstract
Business Process Management (BPM) is an accepted discipline and its importance for industrial automation is recognized by all players today. The complexity of modern management process will lead to chaos without a well-designed and effective BPM. Today, several tools exist, both commercial and open-source, but the selection of the appropriate tool for each organization could be a hard work. The first result of these research is a state-of-the-art of Intelligent Business Process Management Suites and a compared analysis of their features in order to choose the most suitable for processes’ management in a renewable energy power plant. The second research finding is the expliting of BPMN approach to simplify the processes of a Wind Farm company. Process flow optimization had a positive impact both on processes’ efficacy and efficiency and then on the business value proposition. A relevant result of the study was also the definition of some typical maintenance related processes and of maintenance management metrics based on specific KPIs.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
The Institute of Asset Management: IAM asset management maturity guide v1.1. Technical report, The Institute of Asset Management, June 2016. http://www.theiam.org/
Trapani, N., Macchi, M., Fumagalli, L.: Risk driven engineering of prognostics and health management systems in manufacturing. IFAC-PapersOnLine 48(3), 995–1000 (2015). http://www.sciencedirect.com/science/article/pii/S2405896315004528. 15th IFAC Symposium on Information Control Problems in Manufacturing. https://doi.org/10.1016/j.ifacol.2015.06.213
Reliabilityweb.com: Research report on asset management practices, investments and challenges 2014–2019. Technical report (2015). https://reliabilityweb.com/articles/entry/asset_management_practices_investments_and_challenges_2014-2019/. Accessed 10 May 2019
Allweyer, T.: BPMN 2.0: Introduction to the Standard for Business Process Modeling. Books on Demand (2016). https://books.google.it/books?id=sowaDAAAQBAJ
Gabryelczyk, R.: Exploring BPM adoption factors: insights into literature and experts knowledge. In: Ziemba, E. (ed.) AITM/ISM -2018. LNBIP, vol. 346, pp. 155–175. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-15154-6_9
Ciaramella, A., Cimino, M.G., Lazzerini, B., Marcelloni, F.: Using BPMN and tracing for rapid business process prototyping environments, pp. 206–212 (2009). https://doi.org/10.5220/0002005002060212
Jasiulewicz-Kaczmarek, M., Waszkowski, R., Piechowski, M., Wyczółkowski, R.: Implementing BPMN in maintenance process modeling. In: Świątek, J., Borzemski, L., Wilimowska, Z. (eds.) ISAT 2017. AISC, vol. 656, pp. 300–309. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-67229-8_27
Carchiolo, V., Catalano, G., Malgeri, M., Pellegrino, C., Platania, G., Trapani, N.: BPM tools for asset management in renewable energy power plants. In: Proceedings of the 2019 Federated Conference on Computer Science and Information Systems, FedCSIS 2019, pp. 645–649 (2019). https://doi.org/10.15439/2019F110
Gartner: Magic quadrant for intelligent business process management suites. Technical report. Gartner (2019). https://www.gartner.com/en/documents/3899484. Accessed 10 May 2019
IBM Corporation: Understanding the impact and value of enterprise asset management. Technical report (2016). https://www.ibm.com/downloads/cas/XJRD7M1Z. Accessed 10 May 2019
Accenture: The future of onshore wind operations and maintenance. Technical report. Accenture (2017). https://www.accenture.com/us-en/insight-future-onshore-wind-operations-maintenance. Accessed 10 May 2019
Shafiee, M., Sørensen, J.D.: Maintenance optimization and inspection planning of wind energy assets: models, methods and strategies. Reliab. Eng. Syst. Saf. 192, 105993 (2019). https://doi.org/10.1016/j.ress.2017.10.025
Wang, J., Zhao, X., Guo, X.: Optimizing wind turbine’s maintenance policies under performance-based contract. Renewable Energy 135, 626–634 (2019). https://doi.org/10.1016/j.renene.2018.12.006
BPMN.io. https://bpmn.io/. Accessed 04 Dec 2019
Business process modeling. https://cawemo.com/. Accessed 04 Dec 2019
Workflow and decision automation platform. https://camunda.com/. Accessed 04 Dec 2019
Bizagi - digital process automation and BPM. https://bizagi.com/. Accessed 04 Dec 2019
Appian: low-code enterprise application development. https://www.appian.com/. Accessed 04 Dec 2019
Open sourcebusiness automation. https://www.activiti.org/. Accessed 04 Dec 2019
Han, Y.B., Sun, J.Y., Wang, G.L., Li, H.F.: A cloud-based BPM architecture with user-end distribution of non-compute-intensive activities and sensitive data. J. Comput. Sci. Technol. 25(6), 1157–1167 (2010). https://doi.org/10.1007/s11390-010-9396-z
jBPM - open source business automation toolkit. https://www.jbpm.org. Accessed 04 Dec 2019
Kissflow - digital workplace. https://kissflow.com/. Accessed 04 Dec 2019
Quickflow - business agility in the cloud. http://www.quickflows.com/html/solutions.html. Accessed 04 Dec 2019
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Carchiolo, V., Catalano, G., Malgeri, M., Pellegrino, C., Platania, G., Trapani, N. (2020). Modelling and Optimization of Wind Farms’ Processes Using BPM. In: Ziemba, E. (eds) Information Technology for Management: Current Research and Future Directions. AITM ISM 2019 2019. Lecture Notes in Business Information Processing, vol 380. Springer, Cham. https://doi.org/10.1007/978-3-030-43353-6_6
Download citation
DOI: https://doi.org/10.1007/978-3-030-43353-6_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-43352-9
Online ISBN: 978-3-030-43353-6
eBook Packages: Computer ScienceComputer Science (R0)