Graph-Based Framework for Evaluating the Feasibility of Transition to Maintainomics

Part of the Studies in Big Data book series (SBD, volume 8)


Maintenance is a powerful support function for ensuring equipment productivity, availability and safety. Nowadays, growing concern for timeliness, accuracy and the ability to offer tracking information led to the augmentation of e-technologies’ applications within maintenance management, i.e., e-maintenance. However, like any other information and communication (ICT)-based operation, massive data sets (i.e., big data) are generated from videos, audios, images, search queries, historic records, sensors, etc. Inevitably, e-maintenance needs to consider how to extract useful value from those raw and/or fused data as an important aspect before it can be adopted in any industry. This book chapter presents an overview of the e-maintenance data challenge. The main contribution of the article is the application of graph-theoretic approach (GTA) to the problem of finding an improved insight in the factors that determine the feasibility of maintainomics, i.e., data-centric maintenance. With such a concept, the maintenance-services can be upgraded from the low level of operations to the higher levels of planning and decision making.


e-Maintenance Maintainomics Graph-theoretic approach (GTA) Feasibility index of transition (FIT) Power plant Innovative computational intelligence 


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© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Center for Asset Integrity Management (C-AIM), Department of Mechanical and Aeronautical Engineering, Faculty of Engineering, Built Environment and Information TechnologyUniversity of PretoriaPretoriaSouth Africa

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