Canadian Manufacturing

BEAP and Norda Stelo form a collaboration to explore AI in the mining industry

by CM Staff   

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BEAP and Norda Stelo propose to develop a platform allowing them to perform predictive maintenance of static assets in the mining sector.

From Left to right : «Ms Sophie Boisvert, Vice President Ressources et Industry at Norda Stelo, Ms Lucie Lecours, Minister for the Economy, Ministère de l’Économie et de l’Innovation of Quebec, Mr Benoit M. Bédard Ing., President and Co-Founder at» (CNW Group/BEAP)

QUÉBEC — BEAP, a clean technology startup, and Norda Stelo, an engineering firm, are joining forces to introduce artificial intelligence into the mining industry. The $1.2 million project, supported by Investissement Québec as mandatary of the Government of Québec, seeks to solve a major issue for this industry: how to use artificial intelligence to predict failures and the lifecycle of a series of static assets, such as pipeline networks, conveyor lines and buildings.

BEAP and Norda Stelo propose to develop a platform allowing them to perform predictive maintenance of static assets in the mining sector, which have very little, or no data captured in real time.

This platform merges the data gathered during asset inspections and maintenance with human engineering knowledge, which will lead to machine learning models to improve the precision of predictions.

For the mining sector, predictive and even prescriptive maintenance of strategic assets may allow a considerable reduction of maintenance costs and favour 20% to 25% production growth, hopefully permitting a better return on investment.

This digital innovation could find application potential in 22 mines, 14 smelters and refineries and 16 plants currently in operation in Québec. In the medium term, this solution would be deployed in the energy sector, which already faces the same asset management issues, not to mention the foreign export potential.

“This project is especially dear to us. Our team concentrates on preventing the negative economic, environmental, and human consequences of unexpected failures. We have developed a method for collecting and processing information that provides structured data for artificial intelligence analysis. 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,” explains Benoit Moffet Bédard, President and Co-founder of BEAP.

The mining industry has embarked on an ambitious and strategic path by adopting technology that favours a high level of autonomy. Optimal analysis of equipment data by artificial intelligence allows generation of a large volume of relevant information for sustainable asset management.

Currently, most maintenance operations are based on the knowledge of experienced personnel without being scanned or secure. By using analytical techniques to increase comprehension and scanning of asset data, the mine raises the level of monitoring and comprehension of its operational process.


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