Metals & Mining

AI-based predictive maintenance that reduces unplanned plant downtime

Key facts

over20%higher asset utilisation
under3 mthsto achieve ROI
under6 mthssetup
Next Steps
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Top business benefits

<3 months typical ROI

2-6 months typical setup

Increased asset utilisation and uptime

Increased mine throughput

Improved asset health and maintenance

Reduced unplanned downtime events

Mobile or fixed plant capabilities

In more detail

Full description

Unplanned plant downtime is a major issue. Unexpected failures in equipment have a disruptive impact and of course a costly consequence in reduced production.

This advanced AI-based predictive solution improves preventative maintenance, thus reducing plant failures, lost production, spare parts use, and labour costs, all whilst increasing throughput.

The challenge

Throughput depends on plant machinery functioning at peak uptime, and whilst planned maintenance is an essential process in overall performance, unplanned downtime is highly disruptive and very costly. Equipment needs to run as reliably as possible to maximise throughput and final product output.

Many issues can be predicted with the right technology and datasets, combined with advanced AI models, in the fast-developing area of predictive maintenance.

The approach

This advanced AI platform, which has been used in a wide variety of applications across many industries, has delivered highly reliable predictive maintenance recommendations for large and small mills.

Small customisations are typically used to fit the customer dataset used to power the model, and the solution uses proprietary artificial neural networks with advanced explainability features and AutoML for scaling.

Customers are required to have sufficient sensors and stored data (3-5 years) for the equipment and a downtime accounting system to record and store malfunctions. The team will then work with the customer on data integration and input into the system.

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