S. Paraschos, I. Mollas, N. Bassiliades, G. Tsoumakas, "VisioRed: A Visualisation Tool for Interpretable Predictive Maintenance", Proc. 30th International Joint Conference on Artificial Intelligence (IJCAI-21), Demo Track, pp. 5004-5007, 19-26 August 2021, Montreal (Virtual).

Author(s): S. Paraschos, I. Mollas, N. Bassiliades, G. Tsoumakas

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Appeared In: Proc. 30th International Joint Conference on Artificial Intelligence (IJCAI-21), Demo Track, pp. 5004-5007, 19-26 August 2021, Montreal (Virtual).

Keywords: Explainable AI, Interpretable Machine Learning, Predictive maintenance, Prescriptive maintenance

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Abstract: The use of machine learning rapidly increases in high-risk scenarios where decisions are required, for example in healthcare or industrial monitoring equipment. In crucial situations, a model that can offer meaningful explanations of its decisionmaking is essential. In industrial facilities, the equipment’s well-timed maintenance is vital to ensure continuous operation to prevent money loss. Using machine learning, predictive and prescriptive maintenance attempt to anticipate and prevent eventual system failures. This paper introduces a visualisation tool incorporating interpretations to display information derived from predictive maintenance models, trained on time-series data.

See Also: AI4EU Project