Speed continues to be a major focal point for all in the resources sector. It could be time to first ore, accelerating the approvals process with regulators, or ramping up the plant to nameplate capacity.
OreNova Engineering out of Perth, Western Australia, is looking to speed up the engineering process associated with building mineral processing plants, leveraging what it says are proprietary artificial intelligence (AI)-based tools to help automate study-phase mechanical design deliverables for said plants. This covers material and equipment selection, through to datasheet development and mechanical equipment lists, delivering, it says, high-quality results in a fraction of the time – and with a fraction of the cost – than it conventionally takes.
Brad Skajko, Founder and Director of the company, provides an example: “A lot of what is written when it comes to automation is tied to the automation of mobile equipment or the running of processing plants, but the massive roadblocks in many of these projects is the time taken from test work to construction. It can be 10 years in many instances, and a lot of that time is associated with repetitive rework. Through our software, we are showing a way to automate a lot of that work for engineering consultancies and EPCM (engineering, procurement and construction management) firms, and save significant time in completing those milestones.
“The more complex the project, the more time we are able to save.”
Skajko is approaching this challenge from a ‘known position’, having previously worked on the EPCM side on a rare earths plant.
“During my time, we were engaged in a project where the flowsheet underwent multiple iterations. Speaking to other individuals within the industry, this could be up to 10, maybe 12 iterations over a sustained period of time,” he told IM. “The amount of hours we spent as engineers recalculating and reproducing data sheets, going out to market and going out to vendors just blew my mind.
“With the increasing onset of AI and the ongoing digitisation of the mining sector, I could see a massive opportunity for speeding up this everyday work and creating the same results in a significantly shorter timeframe, all while saving costs for clients.”
The outputs that Skajko and his team (AI experts, software engineers, etc) are now able to generate come with around 95% accuracy compared with that labour-intensive baseline. “We’re helping engineering firms complete these deliverables in hours instead of weeks, automating up to 2,000 engineering hours in a couple of days,” he claims, adding that the company has eyes on bringing the accuracy level up to 99% next year with the addition of new software modules.
“Not only that; we’re helping them deliver on projects that they wouldn’t be able to meet deadlines on before. This helps solidify their place in the market – mining firms know they can rely on them for timely outputs, at the same time as the engineering firms can bid for work based on these reduced time to complete work.”
It is the engineering side of the business that is OreNova’s initial target market – Skajko highlighted that the company is engaged in a number of engineering firms involving, engineering teams in Australia and Southeast Asia – but the improved turnaround time for accurate plant-based data could see its software feature in plenty of other parts of the market.
In M&A, for example, it’s easy to see the due diligence team picking up an old plant design from, say, a decade ago and re-working it based on today’s inputs with OreNova’s AI-based software.
And, with bigger mining groups, it could help them run the ruler across their portfolio of assets based on today’s pricing environment and industry inputs. It can also help them carry out trade-off studies to inform decision making on individual assets at a plant-based level.
“We’re very much a software-focused firm, with clients paying fees based on billable contracting hours, but we see a subscription-based model future that reflects this wider market reality,” Skajko says. “The possibilities for accelerating this manual and labour intensive process are vast, and we feel it is only a matter of time before companies are exposed to this reality.”
Another reality he was keen to confront from the off was the actual impact on engineering jobs from the use of such tools.
“Some engineers get concerned that these tools might take their jobs; engineers thought the same thing when AutoCAD came out,” he said. “They soon realised that AutoCAD was another tool to make them more effective at their actual job, which is to design and engineer plants.
“We see our software as helping them engineer solutions, as opposed to getting bogged down in producing mundane documentation time and again ahead of deadlines.
“Our software is an engineering enabler; it is not acting as a replacement engineer.”
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