VisioRed: A Visualisation Tool for Interpretable Predictive Maintenance
This work addresses the need for interpretable AI in high-risk industrial scenarios, though it appears incremental as it focuses on visualization rather than novel model development.
The paper tackles the problem of making predictive maintenance models interpretable in industrial settings by introducing a visualization tool that displays model-derived information from time-series data, aiming to enhance decision-making and prevent financial losses.
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.