Towards Context-Aware Supervision for Logistics Asset Management: Concept Design and System Implementation
Innovations of information and communication technology (ICT) open plenty opportunities to promote internal operation efficiency and external service level in logistics. As current logistics developments tend to be more complex in operation and large in scale, recent practices start to pay more attentions on improving asset (e.g. equipment and infrastructure) management performance with new ICT development. One of the primary concern is to improve system robustness and reliability. It not only requires the supervision system be capable of diagnosing the condition of the system, but also proficient to find the intrinsic relationship between different conditions and resources thus lead to an integrated decision making process. Moreover, recent ICT innovations, such as WSN and IOT, could record and deliver system descriptors (physical measurements, virtual resources, operational configurations) in real time. Such large-stream and heterogeneous data requires an integrated framework to process and management. To address such challenges, in this paper, a novel concept of context-aware supervision is proposed. An intelligent system with integration of semantic web and agent technology is developed, which aims at providing condition-monitoring and maintenance decisions to relevant user. A generic ontology-agent based framework will be illustrated. The developed system will be applied for the supervision of a large-scale material handling system-belt conveying system as a proof-of-concept.
KeywordsLogistics asset management Context-awareness Ontology-agent integration System supervision
This research is supported by the China Scholarship Council under Grant 201307720072.
- 3.De La Cruz, A.L., Veeke, H.P.M., Lodewijks, G.: Prognostics in the control of logistics systems. In: Proceedings of IEEE International Conference on Service Operations and Logistics, and Informatics, pp. 1–5 (2006)Google Scholar
- 6.Winters, L.S., Gorman, M.M., Tolk, A.: Next generation data interoperability: it’s all about the metadata. In: IEEE Fall Simulation Interoperability Workshop (2006)Google Scholar
- 7.Clark, T., Jones, R.: Organisational interoperability maturity model for C2. In: Proceedings of the 1999 Command and Control Research and Technology Symposium (1999)Google Scholar
- 10.Arnaiz, A., Iung, B., Adgar, A., Naks, T., Tohver, A., Tommingas, T., Levrat, E.: Information and communication technologies within E-maintenance. In: E-maintenance, pp. 39–60. Springer, London (2010)Google Scholar
- 11.Pistofidis, P., Emmanouilidis, C., Papadopoulos, A., Botsaris, P.N.: Modeling the semantics of failure context as a means to offer context-adaptive maintenance support. In: Proceedings of Second European Conference of the Prognostics and Health Management Society, pp. 8–10. PHME (2014)Google Scholar
- 20.Kumar, U., Ahmadi, A., Verma, A.K., Varde, P.: Current Trends in Reliability, Availability, Maintainability and Safety: An industry Perspective. Springer, Switzerland (2015)Google Scholar
- 22.Krummenacher, R., Strang, T.: Ontology-based context modelling. In: Proceedings (2007)Google Scholar
- 23.Schmohl, R., Baumgarten, U.: A generalized context-aware architecture in heterogeneous mobile computing environments. In: Proceedings of the Fourth International Conference on Wireless and Mobile Communications, ICWMC 2008, pp. 118–124 (2008)Google Scholar
- 24.Staab, S., Studer, R.: Handbook on Ontologies. Springer Science & Business Media (2013)Google Scholar
- 34.Lodewijks, G., Ottjes, J.A.: Application of fuzzy logic in belt conveyor monitoring and control. BeltCon 13, 2–3 (2005)Google Scholar
- 35.Pang, Y., Lodewijks, G.: A remote intelligent belt conveyor inspection tool. In: Proceedings of 11th International Congress Bulk Materials Storage, Handling and Transportation. Newcastle, Australia (2013)Google Scholar
- 36.Feng, F., Pang, Y., Lodewijks, G.: An intelligent context-aware system for logistics asset supervision service. In: Proceedings of 2016 Federated Conference on Computer Science and Information Systems (FedCSIS), pp. 1147–1152. Gdansk, Poland (2016)Google Scholar