EXPLOSIVES & BLASTING
applied in the blast holes to get the same result .
“ If you can control your fragmentation to hit a target specification with much more accuracy , then the energy used in the mill is going to be less , creating efficiencies and reducing greenhouse gas emissions ,” Rounsley added .
The loading of blast holes with DIFFERENTIAL ENERGY emulsion and the ΔE jumbo truck was carried out manually via a control system that loads up a pre-planned blasting profile , but Dyno Nobel has released a second-generation system of semi-autonomous loading , and Rounsley sees a future where there is fullyautonomous loading that also connects back to the aforementioned Nobel Fire digital platform .
“ With the generation one ΔE trucks , the loading of that tailor-made energy profile was carried out manually via the control system ,” Rounsley said . “ Yet , there is a step after that saying : ‘ why do I want that particular blasting profile and what design is actually suitable here ?’
“ What you need to answer those questions is data from the ground . That could be measurewhile-drilling data , the block model in a digital form , the geologists ’ input , etc .”
ΔE generation two allows customers to use such data to calculate what the most advantageous energy profile will be for the ground to be blasted and the outcome required . This information is then directed to the truck ’ s on-board control system to load the hole with that specific profile .
“ This isn ’ t automated driving of the trucks , it is automated pumping to a specific design ,” Rounsley stated . “ It ’ s doing a number of things – ingesting data , using that data to create a blast design and then directing the truck to load the hole to that design . Instead of only relying on the site ’ s drill and blast experience to come up with the design , you are getting the benefit of all the skilled DynoConsult people that have put all of their intellectual knowledge into that ΔE algorithm to create the outcome you are looking for .”
This solution is already available commercially , according to Rounsley .
The third generation ΔE platform is something to look forward to .
This is where the truck delivering the ΔE emulsion will come with automation capabilities , picking the required profile , lining up with the correct hole destination and loading the consumable in a “ local remote method , a tele-op remote method , semi-autonomous or a fullyautonomous fashion ”, Rounsley said . He clarified on the latter : “ That doesn ’ t mean it will drive around the mine by itself with no-one there . Instead , it may be positioned to drive up and down the rows to load those holes by itself .” This generation of ΔE trucks , which will be able to “ sense and identify humans , boosters and other products ”, is currently in the prototype phase , with two models developed and a third moving into an open-pit mining environment later this year .
This is where it comes back to the ‘ Connected Bench ’ concept and the Nobel Fire platform that started the discussion , where ingesting the correct data on the bench , carrying out the blast – through wireless or wired means – and reconciling that data , post-blast , can improve overall blasting outcomes .
“ If you have that pathway from the truck with the data back to the cloud-based digital system , you also have the ability to send data the other way – with instructions going back to the truck ,” Rounsley said . “ This brings you into the realm of ΔE Gen 3 . The design information directed by modelling software like FDM ( Fracture Density Model , Dyno Nobel ’ s fragmentation simulation software ) or GEM ( Geologic Element Motion , Dyno ’ s movement analysis software ) will be sent to the truck which will run away and deliver it to plan , without direct human control .
“ Then , of course , once the blast has concluded , you can measure the outcomes using whatever third-party system you like , we create the required APIs to bring it back into Nobel Fire and this information is then used to drive better decisions in the next blast design .
“ It all comes back to the ‘ Connected Bench ’ concept .”
Open to integration
Integrating and embedding its products and solutions into the wider mining process is also a key aim for Orica .
Through organic and acquisitive growth , the Australia-based company has become way more than a supplier of explosives and blasting equipment . Its solutions cover everything from bulk systems , packaged explosives , initiating systems and fragmentation tracking , to slope stability monitoring ( with GroundProbe ), ground support ( through Minova ) and gold leaching ( through LeachIT™ ).
This wide-ranging expertise – underpinned by digital solutions that ensure companies can track all-important productivity , profitability and sustainability metrics – allows the company to look beyond blasting .
Even with such an expansive offering , Raj Mathiravedu , Vice President of Digital Solutions , acknowledges that the company cannot – and should not – take on the burden of improving mine site performance alone .
Instead , the company should facilitate such improvements through connecting its broad and connected offering with other systems present at mine sites .
“ Our digital strategy is maturing beyond the
range of technologies we offer as we continue to explore continuous integration of our individual digital blasting technologies and the systems at our customers ’ operating sites ,” Mathiravedu told IM . “ The multiple integration points for our suite of digital solutions ensures flexibility for our customers in leveraging the best combination of solutions that suit their operational needs .”
Improved connectivity is proving key to enabling automation at multiple points and scales of a company ’ s process , all aimed at supporting both upstream and downstream efficiency and productivity gains in mining , he said .
Orica ’ s FRAGTrack™ is an example of this at the “ micro level ”, Mathiravedu explained , with the fragmentation measurement tool using advanced machine vision technologies that interface with a site ’ s crusher control to enable automated post-blast measurement and analysis .
Usually delivered as part of Orica ’ s BlastIQ™ Digital Blast Optimisation Platform suite , FRAGTrack has previously allowed Boliden ’ s Kevitsa mine to quantify the effect geology had on its blast performance , with the data used to make targeted design modifications to its drill and blast process .
Further upstream of this , the recent addition of Orica ’ s Orebody Intelligence division and the Rhino™ measurement technology has allowed mine sites to infer more about their resources . Rhino comes as a set of drill string-mounted geophysical sensors that measure rock elastic moduli while drilling , streaming said data in real time to the cloud .
This platform , Mathiravedu says , creates a high-fidelity data stream that increases the level of insight and automation that can be delivered across Orica ’ s platform .
Orica ’ s OrePro™ 3D blast movement modelling solution goes even further , tracking rock mass , post-blast , for effective ore and waste distinction ahead of processing .
Some of these elements come together on a macro level within Orica ’ s Design for Outcome software , which has helped improve performance at the Roy Hill iron ore mine in the Pilbara of Western Australia .
Design for Outcome applies machine learning to data integrated upstream and downstream of the blasting process , providing an automated workflow using algorithms to define the geological hardness and generate blast designs that accurately allocate the optimal energy to consistently achieve targeted mining outcomes , according to Orica .
These machine-learning algorithms domain the geology in each drill hole and match explosives energy to the said domain ,
96 International Mining | AUGUST 2021