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The Convergence between Predictive Maintenance and Augmented Reality to Aid Renewable Energy Equipment Availability
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DOI: https://doi.org/10.15866/irea.v2i5.1916
Abstract
The maintenance area makes permanent challenges to research and develop new methodologies and later to transfer that knowledge to optimize the maintenance interventions and the equipment performance. The introduction of new technologies in the maintenance field, like 3D models, Geographic Information Systems (GIS) and Augmented Reality, permitting simplify the interventions, help training, making remote interventions and more easily locating geographically the technical assets. The focus of the present paper is the wind generators field where the distance between the maintenance management department and each wind generators farm emphasizes the importance of precedent technologies. Additionally, the easy location of each wind generator is a major question that is easily answered through GIS (Geographic Information System).
This paper deals with wind generators, through a methodology that aims to optimize the cycles of production and, consequently, reduce the production of energy based on fossil resources. The methodology presented is based on-condition techniques with prediction.
The new developments will be later incorporated in the information system, because they are developed in a modular way, in order to add new capacities to an integrated maintenance management system called SMIT (Terology Integrated Modular System). This system was designed to be the base information system, and can incorporate new tools in order to be always up-to-date. Its implementation is through client-server, browser or cloud computing, but also having the capacity to receive new tools, as GIS, 3D models or Augmented Reality. With these new tools and, particularly the last one, it makes possible improving the quality of maintenance interventions, minimize their intervention times, and expanding knowledge to a larger number of maintenance technicians through the possibility of training in a virtual environment. This means that will help to use less hardware and energy resources, including the equipment themselves and, by consequence, it also helps to increase the environmental perspective.
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