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Quebec Iron Ore (MFQ)

Quebec Iron Ore optimizes its mining operations with AVEVA solutions

Quebec Iron Ore (QIO) uses AVEVA PI System, AVEVA Operations Control and AVEVA Predictive Analytics to optimize operations at its open-pit mine in Quebec, where it produces 7.4 Mtpa of high-grade iron ore concentrate (66.2% Fe). The company lacked the data management capabilities to generate operational reports efficiently, its Phase II expansion required greater asset reliability, and ore lost all traceability as soon as it left the mine. With AVEVA, QIO unifies its data from mine to port, has a robust architecture to collect, visualize and analyze operations and assets, increases its real-time visibility and shortens the time between detecting an event and resolving it, ensuring full product traceability.

Objectives

  • Reduce reaction times from event to resolution
  • Create a robust data architecture to collect, visualize, and analyze asset operations and data
  • Increase real-time visibility of operations from pit to port

Solutions

  • AVEVA PI System
  • AVEVA Operations Control
  • AVEVA Predictive Analytics

Results

  • Teams can perform their own analysis and generate more detailed reports
  • Real-time asset analytics tools have made assets more reliable for Phase II expansion
  • Unified data management tools provide the database to achieve a complete visualization from pit to port

Testimonials

"Having a solid database improves the availability of our data and gives operators the power to visualize analytics."
Nicolas Toupin
Programmer, Business Intelligence

FAQ

How does AVEVA supervise an iron ore mine in an extreme northern environment?
Quebec Iron Ore (MFQ), located on the Côte-Nord of Quebec, uses AVEVA SCADA and System Platform to supervise iron ore extraction and concentration in demanding climatic conditions. Industrial supervision centralizes data from the mine, the concentrator and the port facilities. The platform ensures operational continuity despite extreme temperatures and remoteness, giving teams complete visibility across the entire mining value chain.
What role does AVEVA System Platform play in an integrated mining operation?
AVEVA System Platform acts as the industrial operating system at MFQ, unifying monitoring of the mine, concentrator, transportation and port operations. Object-oriented modeling makes it possible to standardize processes, capture best practices and simplify maintenance. This approach is particularly valuable in the mining sector, where operational complexity and the geographic spread of assets require a robust, scalable platform.
How can SCADA monitoring remain reliable in extreme cold?
Mining in a northern climate involves specific constraints: extreme temperatures, frozen sensors and difficult communications. AVEVA SCADA is designed to run on resilient architectures with redundancy and local storage. At MFQ, the solution maintains continuous data collection and visualization, ensuring operational safety and productivity, even in winter. This robustness is an essential criterion in Arctic and subarctic regions.
What business benefits does industrial monitoring bring to a mining operator?
For MFQ, AVEVA SCADA and System Platform make it possible to optimize production throughput, reduce unplanned shutdowns, improve ore traceability and make performance indicators more reliable. Centralized monitoring also facilitates collaboration with logistics partners and steelmaking customers. In a cyclical, competitive iron ore market, these operational gains and this industrial agility are a decisive competitive advantage.
Why is business intelligence strategic in the mining sector?
Beyond pure monitoring, AVEVA allows MFQ to use operational data to manage industrial performance: cost-per-ton analysis, energy consumption optimization and maintenance planning. This business intelligence, powered by reliable real-time data, supports strategic decisions and financial communication. It is a pillar of digital transformation in the mining sector, where competitiveness depends on the ability to turn data into value.