Abstract
The presentation will demonstrate that comprehensive digital interventions can contribute to the mining sector's sustainability goals by reducing the carbon footprint of haulage operations, creating a pathway toward greener fleet management while the transition to BEV is ongoing.
The mining sector contributes, based on conservative estimations, over 1% of the global economy’s carbon footprint, with haulage fleets accounting for a 50-80% share of these emissions. Diesel-powered mining trucks can consume up to 350 liters per hour, emitting approximately 900 kg of CO₂e per hour of operation. Although transitioning to battery electric vehicles (BEV) presents an opportunity to decarbonize mining, BEV currently represents only 1.2% of truck sales worldwide. In this context, there is an urgent need to leverage alternative strategies to reduce emissions, such as leveraging digital asset performance management (APM) technologies to optimize fuel consumption in diesel fleets.
SYMX.AI has developed a digitization platform tailored for mobile mining fleets, integrating IoT data acquisition from vehicles with advanced analytics engines for real-time data analysis. This system has been rigorously tested and applied in various mining operations, addressing critical sustainability metrics, including reductions in CO₂e emissions and operational waste. At the maximum projected capacity, the system can decrease fuel consumption by up to 9%. A recent deployment at a gold mine in Canada demonstrated the platform’s efficacy, yielding a 4.3% reduction in fuel consumption across a subset of trucks and a corresponding decrease in idle times by 3.1%. These improvements translate into measurable CO₂ savings and validate the feasibility of APM technology as a practical tool in decarbonization strategies.
The deployment underscores the value of digital data integration in achieving holistic equipment dispatch management that accounts for both production optimization and fuel efficiency. This also exemplifies a dispatch model designed not solely for production targets but also to prioritize decarbonization, reducing overall environmental impact. Furthermore, these findings reveal a critical opportunity to expand on technological innovations, such as real-time fuel consumption analytics relative to haul road conditions, to optimize factors like idling. SYMX.AI is actively developing algorithms to enhance these capabilities.
To effectively mitigate carbon footprints in the present, we propose a multi-pronged approach that includes:
- Advanced Technology Integration – Deploying IoT and APM platforms to track and manage fuel consumption metrics in real time.
- Data-driven Decision-making – Enabling collaboration between dispatch teams and sustainability leaders to establish a culture where operational decisions are informed by fuel efficiency and carbon reduction goals.
- Robust Measurement Systems – Establishing frameworks that ensure continuous tracking and reporting of progress, validating the impact of emission reduction efforts.