Emerald Challenge Winner - Blasting Down CO2

Description

The integration of cutting-edge technologies has paved the way for groundbreaking advancements in enhancing the Mine-to-Mill efficiency while minimising environmental impact. One such pioneering endeavour is the Blasting Down CO2 project initiated by a collaborative effort between Tarmac Mountsorrel Quarry, GEARS, and New Gradient. This transformative project, which won the Institute of Quarrying’s prestigious Emerald Challenge marks a significant milestone in the application of Artificial Intelligence in quarrying practices in the UK. The genesis of the project stemmed from a collective realisation that traditional blasting methodologies, primarily focused on cost reduction, often fell short in terms of optimising blast quality and curbing overall costs and CO2 emissions. This critical insight served as the impetus to embark on a mission to harness the power of AI to revolutionise the blast design process at Mountsorrel Quarry. By leveraging sophisticated AI solutions, the project unveiled a potential game-changing approach that not only streamlines operational processes but also yields tangible environmental benefits. Through precise fragmentation measurements of both the blast pile and crushing processes, Tarmac’s Mountsorrel Quarry has been empowered to accurately gauge the ramifications of subpar outcomes at each stage. Armed with comprehensive data encompassing both cost, environmental and quality metrics, Tarmac have been able to make informed decisions that have driven superior optimisation strategies. Stage 1 of the project has now been completed which has focused on implementation and data collection. It will shortly begin stage 2 where it will start to assess the impact of optimising the blast design. The first stage has already identified some significant outcomes which include. 1. Significant cost and revenue losses from oversize within the blast pile as identified by FragMAP; 2. This equates to a potential reduction in CO2 emissions of up to 15% where poor blasting fragmentation has caused excessive secondary breakage. 3. AggCAM identified inefficiencies within the primary crusher feed, from which the fleet was then optimised. This fleet optimisation increased the primary crusher throughput by around 13%. The outcomes from Stage 1 have demonstrated that AI has the transformative capabilities to reshape traditional practices whilst offering a new cost effective method of undertaking a Mine-to-Mill optimisation process that can be applied at any scale. It is projects like this that underscores the immense potential for technology-driven solutions to steer the sector towards a more efficient, eco-conscious, and economically viable future. Please confirm your attendance by Monday, 9th September 2024 to help with refreshments on the night.

Venue

Buxton Rugby Club, Sunnyfields, Harpur Hill, Buxton, SK17 9PX