RPMGlobal said it plans to leverage IMAFS's predictive algorithms by integrating these with its asset management system, AMT, enabling firms to optimise procurement and management of critical parts and components.

The deal was first announced in October 2020 and involved a one-off payment of C$1.3 million (US$1.01 million) on completion.

IMAF's cloud-based solution uses AI to analyse inventory data from corporate Enterprise Resource Planning (ERP) systems, to calculate the optimal timeframe for inventory orders, costs and order frequency.

AMT uses a Dynamic Life Cycle Costing engine that forecasts, in real-time, every maintenance event for a piece of equipment, at a component level, until the end of its economic life.

"We are excited to be utilising AI technologies to improve the efficiency of mining operations across the asset management function," said RPMGlobal chief executive Richard Mathews.

RPMGlobal pointed to past success using IMAF software, noting that one operation was able to reduce 78% of stockouts for items with high usage, while concurrently reducing stock levels by 14%. Another operation was able to reduce global inventory by 15% within the first 10 months.

"The ability to optimise production and identify opportunities for improvement across the mining value chain is proving a key competitive advantage in this dynamic operating landscape," he added.