Towards context-aware supervision for logistics asset management

Concept design and system implementation

Conference paper (2017)

Authors

F. Feng Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering
Y. Pang Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering
G. Lodewijks Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering
Research Group
Transport Engineering and Logistics (Mechanical, Maritime and Materials Engineering) (TU Delft)
Context-awareness Logistics asset management Ontology-agent integration System supervision
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Published Date

2017

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Marine and Transport Technology

Research Group

Transport Engineering and Logistics

Abstract

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.