Abstract
The changing nature of manufacturing, in recent years, is evident in industries willingness to adopt network connected intelligent machines in their factory development plans. While advances in sensors and sensor fusion techniques have been significant in recent years, the possibilities brought by Internet of Things create new challenges in the scale of data and its analysis. The development of audit trail style practice for the collection of data and the provision of comprehensive framework for its processing, analysis and use should be an important goal in addressing the new data analytics challenges for maintenance created by internet connected devices. This paper proposes that further research should be conducted into audit trail collection of maintenance data and the provision of a comprehensive framework for its processing analysis and use. The concept of ‘Human in the loop’ is also reinforced with the use of audit trails, allowing streamlined access to decision making and providing the ability to mine decisions.
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
Similar content being viewed by others
References
Abreu, R., Bobrow, D.G., Eldardiry, H., Feldman, A., Hanley, J., Honda, T., de Kleer, J., Perez, A., Archer, D., Burke, D.: Diagnosing advanced persistent threats: a position paper. In: DX@ Safeprocess, pp. 193–200 (2015)
Duncan, R.A.K., Whittington, M.: Enhancing cloud security and privacy: the power and the weakness of the audit trail. In: Westphall, C.B., Lee, Y.W., Rass, S. (eds.) Cloud Computing 2016: The Seventh International Conference on Cloud Computing, GRIDs, and Virtualization, IARIA, p. 137 (2016)
German Federal Government: The new high-tech strategy innovations for Germany (2016). https://www.bmbf.de/pub/HTS_Broschuere_eng.pdf. Accessed 16 Mar 2018
Grangel-González, I., Halilaj, L., Auer, S., Lohmann, S., Lange, C., Collarana, D.: An RDF-based approach for implementing Industry 4.0 components with administration shells. In: 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA), pp. 1–8. IEEE (2016)
Haider, A.: Asset lifecycle data governance framework. In: Proceedings of the 7th World Congress on Engineering Asset Management (WCEAM 2012), pp. 287–296. Springer, Cham (2015)
Henßen, R., Schleipen, M.: Interoperability between OPC UA and AutomationML. Procedia CIRP 25, 297–304 (2014)
Imran, M., Hlavacs, H., Haq, I.U., Jan, B., Khan, F.A., Ahmad, A.: Provenance based data integrity checking and verification in cloud environments. PLoS ONE 12(5), e0177576 (2017)
Kubler, S., Yoo, M.-J., Cassagnes, C., Framling, K., Kiritsis, D., Skilton, M.: Opportunity to leverage information-as-an-asset in the IoT – the road ahead. In: 3rd International Conference on Future Internet of Things and Cloud, pp. 64–71 (2015)
Lee, J., Bagheri, B.: Cyber-physical systems in future maintenance. In: 9th WCEAM Research Papers, pp. 299–305. Springer, Cham (2015)
Lin, S., Gao, J., Koronios, A., Chanana, V.: Developing a data quality framework for asset management in engineering organisations. Int. J. Inf. Qual. 1(1), 100–126 (2007)
Liyanage, J.P., Lee, J., Emmanouilidis, C., Ni, J.: Integrated e- Maintenance and intelligent maintenance systems. In: Handbook of Maintenance Management and Engineering, pp. 499–539 (2009)
Lomotey, R.K., Pry, J.C., Chai, C.: Traceability and visual analytics for the Internet-of-Things (IoT) architecture. World Wide Web 21(1), 7–32 (2018)
MIMOSA Machinery Information Management Open Systems Alliance (2017). http://www.mimosa.org/. Accessed 16 Mar 2018
Kans, M., Galar, D., Thaduri, A.: Maintenance 4.0 in railway transportation industry. In: Proceedings of the 10th World Congress on Engineering Asset Management (WCEAM 2015), pp. 317–331. Springer, Cham (2015)
Karray, M.H., Morello, B.C., Zerhouni, N.: Towards a maintenance semantic architecture. In: 4th World Congress of Engineering Asset Management, WCEAM09, Athens, Greece (2009)
Moreau, L., Clifford, B., Freire, J., Futrelle, J., Gil, Y., Groth, P., Kwasnikowska, N., Miles, S., Missier, P., Myers, J., Plale, B.: The open provenance model core specification (v1.1). Fut. Gener. Comput. Syst. 27(6), 743–756 (2011)
Payan, A.P., Gavrilovski, A., Jimenez, H., Mavris, D.N.: Review of proactive safety metrics for rotorcraft operations and improvements using model-based parameter synthesis and data fusion. In: AIAA Infotech@ Aerospace, San Diego, California, USA, 4–8 January 2016, p. 2133 (2016)
Pistofidis, P., Emmanouilidis, C., Papadopoulos, A., Botsaris, P.N.: Management of linked knowledge in industrial maintenance. Ind. Manag. Data Syst. 116(8), 1741–1758 (2016)
Turner, C.J., Tiwari, A., Olaiya, R., Xu, Y.: Business process mining: from theory to practice. Bus. Process Manag. J. 18(3), 493–512 (2012)
Vaughn, R.B., Farrell, J., Henning, R., Knepper, M., Fox, K.: Sensor fusion and automatic vulnerability analysis. In: Proceedings of the 4th International Symposium on Information and Communication Technologies, Trinity College Dublin, pp. 230–235 (2005)
Vergidis, K., Turner, C., Alechnovic, A., Tiwari, A.: An automated optimisation framework for the development of re-configurable business processes: a web services approach. Int. J. Comput. Integr. Manuf. 28(1), 41–58 (2015)
Woodall, P., Gao, J., Parlikad, A., Koronios, A.: Classifying data quality problems in asset management. In: Engineering Asset Management-Systems, Professional Practices and Certification, pp. 321–334. Springer, Cham (2015)
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
Turner, C.J., Emmanouilidis, C., Tomiyama, T., Tiwari, A., Roy, R. (2020). Intelligent Decision Support for Maintenance: A New Role for Audit Trails. In: Liyanage, J., Amadi-Echendu, J., Mathew, J. (eds) Engineering Assets and Public Infrastructures in the Age of Digitalization. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-48021-9_44
Download citation
DOI: https://doi.org/10.1007/978-3-030-48021-9_44
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-48020-2
Online ISBN: 978-3-030-48021-9
eBook Packages: EngineeringEngineering (R0)