McLaren is a Formula 1 motor racing legendary team but its sustainable technology and expertise is now being used by PT Pamapersada Nusantara (PAMA) in Indonesia to improve its vehicles’ sustainability credentials, according to a report in Global Mining Review
From lithium and cobalt for electric vehicle batteries, to bauxite and cadmium for solar panels, mining will play an integral role in securing the resources needed to transform society. It is therefore critical that the mining industry itself is equipped with the tools to decarbonise as rapidly as possible, allowing it to lead the way in enabling a more sustainable future for everyone.
To that end, PT Pamapersada Nusantara (PAMA), one of Indonesia’s largest mining contractors, has partnered with British technology and engineering company, McLaren Applied, to immediately expedite the process of decarbonising its operations.
With fuel representing between 25 and 30% of a mine’s operating expenses, any gain in efficiency can have a large impact on pollution, productivity, and costs. Such gains are hard won, with PAMA haul trucks capable of carrying around 100 t of mined material over steep, uneven ground operating in a dynamic environment which requires constant analysis. Ever-changing variables – such as payload, weather, terrain, and route – all affect the driving technique required to ensure maximum efficiency.
While the widespread introduction of electrified or hydrogen-powered mining trucks remains some way off, the application of accurate, real-time fuel analytics can represent a cost-effective way to make an instant impact on both consumption and emissions, increasing efficiency and accelerating decarbonisation.
McLaren Applied’s Formula 1-derived technology collects detailed live data from multiple sensors onboard PAMA’s fleet of mining trucks, transmitting it to cloud-based servers and using it to inform a powerful machine learning-based algorithm.
The Fuel Analytics Service references the data received against a full digital model of the mine, using specially developed AI tools to instantaneously calculate what changes the driver should make to optimise fuel efficiency.
Learning from the behaviours of the most efficient drivers over the last three-days’ worth of data, the model instructs vehicle operators in real time, offering live feedback to ensure optimal driving, maximising efficiency and minimising fuel consumption in any conditions. With different drivers’ styles better suited to various aspects of the dynamically changing environment, the most efficient among them may not always be the same, providing all employees with an opportunity to learn and improve.
Read the full story at Global Mining Review HERE
Return to Decarbonisation New Index HERE
