This month we caught up with Peter Horsburgh from SORBA.ai to learn about a technology designed to unlock the full potential of a mining operation’s assets.
Peter is a reliability engineer, for more than two decades he has been using his technical expertise to assess the risks and reliability associated with assets in business operations. He’s also the author of ‘5 Habits of an Extraordinary Reliability Engineer’, a book that teaches you a few simple habits to help you find problems before they find you.
“The holy grail of reliability engineering is warning time. Being able to do something to solve the problem before it occurs. That’s what this technology can do,” said Peter.
Peter was at an international maintenance conference doing a presentation on the future of reliability when he first met the team behind SORBA.ai.
“After I spoke I had so many businesses calling me over to show me their products and to be honest I was feeling fatigued and all I wanted to do was leave. Then a couple of guys from SORBA.ai stand beckoned me over. Compared to the other exhibitors they didn’t stand out. Just a couple guys with a laptop and a small demo rig, nothing impressive.
“But then they showed me what they could do, and I was impressed.
“It was that chance meeting that led to me becoming the APAC Managing Director of SORBA.ai and I’m still pinching myself today.”
SORBA.ai is an automation software platform that allows businesses to improve asset availability and optimise processes. While it is used across a range of industries with many different applications, it’s the SORBA.ai SMART Asset Health Monitoring for Mining that Peter believes is a game changer for our industry.
“Take a haul truck for instance. There are many things that can cause a failure. Constant demands, difficult environments, as well as the failure of individual components to name a few.
“SMART Asset Health Monitoring is a closed-loop AI-Driven platform. It takes the data coming from real-time monitoring and historical data and by using machine learning algorithms it can predict problems before they occur.
“It’s able to process 1000 pieces of data per second on a machine. Temperatures, pressures, vibration, and fuel usage and more. It can handle operational variations. It can even compare data with other assets in the fleet and on other sites.
“Then it uses the data to predict when the truck is going to fail and why, so you can remedy it before it occurs.”
While some original equipment manufacturers (OEMs) have competitive products, unlike SORBA.ai, they are designed to talk only to their own machines and may even have restricted end user access.
“We’re very proud to be independent. It doesn’t matter who the OEM is or what the equipment is. Wash plants, haul trucks, fixed and remote plants, dozers, excavators, SORBA.ai can be employed on all of them.
“Plus, unlike anyone else in the market, we only need a small amount like days or hours of historical data in comparison to the 6 or 12 months requested by most other solutions to achieve the same results.”
Peter also explains that what sets SORBA.ai apart is the simplicity of the platform.
“One of things about SORBA.ai which in my experience I’ve found to be very rare, is that it is easy to use. You don’t need to know how to code, you don’t need data analysts to interpret the results for you. It’s made to be used by the engineers and maintainers working on site. You know – the people who know the equipment better than anyone else.”
Peter is also proud of the price tag. The cost to run SMART Asset Health Monitoring on a piece of equipment is around $500 per month. To put that in perspective, that’s less than the cost of the fuel that a haul truck will use in 30 minutes.
Speaking of fuel consumption, minimising fuel usage is another of the benefits it provides by enabling the user to optimise equipment to its full capability.
“It will save you fuel by showing you if your truck is in tune with correct engine settings and show you where you are using the most fuel using GPS locations so you can optimise your mine design and/or travel speeds. And that’s only the start.
“For example there’s no more need for battery tests as it is constantly monitoring the battery. All of the data is going to the maintenance team at their workshop in real time. They don’t have to go to the pit so it minimises risk to people by negating the need to do live work.
“The safety and training department can see what the operator is doing in real time. Where the steering wheel is, how fast they’re going, the brake position, the accelerator position, whether that body is up or down, everything. Having that data is the best way to make improvement.
“This is what gets me excited. Having one integrated platform that gives people the right tools to do their jobs effectively. If anyone is skeptical, all they have to do is trial the technology. Once the data is flowing it takes about 15 minutes to create a Sorbot to monitor an engine – the results will speak for themselves.”
