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Publications
Santos, P., Pato, M.P.M., Datia, N. and Sobral, J. (2024), How NLP and visual analytics can improve asset management, Artificial Intelligence and Visualization: Advancing Visual Knowledge Discovery. Studies in Computational Intelligence, Volume 1126, B. Kovalerchuk, K. Nazemi, R. Andonie, N. Datia, E. Bannissi (Eds.), Springer, Switzerland, pp 423-441
Asset management is a complex process involving the coordination of several disciplines to ensure physical assets are maintained, upgraded, and operated correctly. In an attempt to deal with such complexity, Vanier [ 39] describes asset management as the successful implementation of data collection related to six questions: (i) What do you own? (ii) What is it worth? (iii) What is deferred maintenance? (iv) What is its condition? (v) What is the remaining service life? (vi) What do you fix first? The data source needed to answer most of the above questions are documents called Work Order (WO). WOs provide all the relevant information regarding a situation with an asset and outline the steps involved in completing them. Creating and managing WOs enables rigorous control of assets during their life cycle. Analysing WOs is crucial to any business. It helps to ensure that all tasks are completed efficiently and on time while also providing valuable insights into the current state of operations. By reviewing WOs, businesses can identify fields needing improvement or potential opportunities to increase productivity.
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