VisioRed: A Visualisation Tool for Interpretable Predictive Maintenance

TL;DR

VisioRed is a visualization tool designed to enhance interpretability of machine learning models used in predictive maintenance for industrial equipment, aiding timely decision-making to prevent failures.

Contribution

The paper introduces VisioRed, a novel visualization tool that integrates interpretability features into predictive maintenance models based on time-series data.

Findings

Improves understanding of machine learning decisions in maintenance

Facilitates timely and informed maintenance actions

Enhances trust in predictive models

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.