VisioRed: A Visualisation Tool for Interpretable Predictive Maintenance
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 decision-making 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.
Cite
Text
Paraschos et al. "VisioRed: A Visualisation Tool for Interpretable Predictive Maintenance." International Joint Conference on Artificial Intelligence, 2021. doi:10.24963/IJCAI.2021/713Markdown
[Paraschos et al. "VisioRed: A Visualisation Tool for Interpretable Predictive Maintenance." International Joint Conference on Artificial Intelligence, 2021.](https://mlanthology.org/ijcai/2021/paraschos2021ijcai-visiored/) doi:10.24963/IJCAI.2021/713BibTeX
@inproceedings{paraschos2021ijcai-visiored,
title = {{VisioRed: A Visualisation Tool for Interpretable Predictive Maintenance}},
author = {Paraschos, Spyridon and Mollas, Ioannis and Bassiliades, Nick and Tsoumakas, Grigorios},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2021},
pages = {5004-5007},
doi = {10.24963/IJCAI.2021/713},
url = {https://mlanthology.org/ijcai/2021/paraschos2021ijcai-visiored/}
}