Artificial Intelligence: AI Platform For Predictive Maintenance Of Static Mining Assets

August 18, 2021 | Artificial Intelligence, News

Static but strategic mining assets such as conveyor lines, pipelines and buildings also need predictive maintenance.

Engineering firm Norda Stelo and clean energy startup BEAP are collaborating on a $1.2 million project to improve the life and dependability of static mining assets using artificial intelligence (AI). The project is being supported by Investissement Québec as mandatary of the Government of Québec. (Yahoo Finance)

Reduction in costs

There is little real time data collected around static assets in the mining industry such as pipelines and buildings. So the problem is how to train a machine learning algorithm on the nuances of maintenance of these assets.

BEAP and Norda Stelo will design a platform that will collect and assimilate the data gathered during asset inspections, and then merge it with human engineering knowledge to create a data base for the AI models to learn from.

Tablets or smartphones would be used to input inspection reports that are currently stored in non-standard formats, are usually handwritten and stored in decentralized locations.

The system will then generate maintenance reports that guide the client in risk management and decision-making regarding the service and maintenance of the assets.

Failure rates will thus reduce drastically, thereby boosting production and avoiding adverse environmental consequences such as spills and safety incidents.

“We have developed a method for collecting and processing information that provides structured data for artificial intelligence analysis,” explained Benoit Moffet Bédard, President and Co-founder of BEAP. “We can thus improve our understanding of asset health by helping tools already in place. That knowledge enables mining companies to improve asset monitoring and simplify the operational process.”

There could be a wealth of such ‘static’ data available from the 22 mines, 14 smelters and refineries and 16 plants currently in operation in Québec.

Predictive alerts for the maintenance of these assets could help reduce maintenance costs and cut down on mine down time. As a result, production levels could improve by as much 20% to 25%.

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