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Metals & Mining

Flotation optimisation using AI

Key facts


increased extraction rate


energy consumption

Next Steps
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Top business benefits

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Waste reduction

AI-powered applications allow you to optimise the amount the consumables (water and reagents) used in the flotation process and reduce the amount of waste products and pollutants as a result

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Anomaly detection

Predicts and prevents cavitation in cyclone feed pumps using AI analytics that monitor equipment, conduct a root-cause analysis, and provide actionable insights on how to avoid cavitation events

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Online monitoring

A plug-and-play platform with a user-friendly dashboard, this solution provides fast and clear insights, and can be easily scaled-up to enhance visibility across entire production

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Increased concentrate quality

Quality control and detection, as well as anomaly detection applications, help you reach a higher and more consistent production quality

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Flotation optimisation

Optimises every stage of the flotation process

Using AI and machine learning technology, this solution optimises the entire flotation process, from increasing recovery to minimising waste and preventing cavitation. 

Main features

  • Features unique data analysis technology and a self-learning system that adapts to changing conditions

  • Materials tracking application grants complete transparency of the feed ores journey through the supply chain

  • Anomaly detection applications detect and prevent cavitation events before they occur, and help you mitigate future ones

  • Uses data collected from virtual sensors to make actionable recommendations to operators on how to optimise flotation at every stage

  • Compatible with I&C systems in order for AI applications to operate manufacturing equipment automatically

Deployed by

In more detail

Full description

Inefficient flotation operations give rise to a number of issues, like cavitation, which can compromise equipment and result in costly periods of downtime.

This plug-and-play solution uses AI-powered technology to optimise every stage of flotation. With its cutting-edge applications and machine learning technology, it collects, examines, and displays a range of data sources on a single dashboard. This means you can easily oversee production and make informed decisions on how to optimise specific areas. 

The challenge

Flotation has many challenging elements, including cavitation, low recovery rates, increased energy consumption, and variable concentrate consistency. These issues become even more pronounced during complex flotation processes, where multiple mineral ores are being treated at once or when ores are highly variable in contents such as sulphides.

Here, it becomes difficult to monitor all the different reagents, wet circuits, and vessels that are required for each individual ore, and challenges can quickly escalate into serious operational issues. When undetected, cavitation, for example, leads to overflowing sumps, performance degradation, increased energy consumption, defective pumps, and periods of operational downtime.

The approach

Providing unified data management and virtual analysers that increase visibility across processes, this solution improves the transparency and optimisation of flotation processes, no matter the scale. 

Through its range of AI applications and data sources, operators can easily identify specific issues like cavitation events, mineral consumption, or equipment health. 

Automated machine learning technology then analyses these issues and provides operators with actionable insights into how to address them in the present and avoid them in the future. 

The bottom line? Increased throughput and recovery, higher production quality, resource optimisation, and less downtime.

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