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In Part 2 of our series discussing what manufacturers can learn from the metals and mining industry, I’m joined again by Joe Carr from Axora. You can listen to part one here.
In this episode, we discuss where metals and mining are as an industry with regards to digital transformation, why some IT departments are reluctant to embrace this and the role of AI.
Key topics covered (click to jump to the section)
- Digital transformation in metals and mining
- Why IT departments are reluctant to embrace digital transformation
- Misconceptions about AI
- Case study: Alcoa
Niall Sullivan, Senseye: It's really interesting, I guess. Yeah. Think about those savings. It leads onto our next question as well, around sort digital transformation projects. I guess a lot of that those savings can be moved into other areas.
I guess the first question really is to look at where are metals and mining in general, in terms of digital transformation. Some industries are not even thinking about it, very much still dipping their toe in the water, whereas fully engrossed and fully involved in those type of projects. Where would you say on a scale, I guess where metals and mining companies would be?
Joe Carr, Axora: I'd say, it's not a scale. I'd say it's a company by company thing because you have some companies which are incredibly committed and have absolutely incredible digital innovation.
There's a company in Marley, which is a small company, which has an entirely autonomous underground operation, which is very difficult to do, but an incredible feat of engineering. And you'll go five miles down the road and there will be another mine where they don't even have digital shift sheets and everyone will be filling in a piece of paper with a pencil. I don't think it's possible to say the mining industry is here.
I think you can certainly do that with companies and the mining industry as a whole, you would characterize as a bit of a slow moving, technological, laggard as such. The mining industry still very much views equipment as an asset and not a digital type of thing as an asset.
We look at a truck and I say, okay, I can spend 10 million on a truck and I can get this much extra production. I can do that math on the back of an envelope in five minutes and work out the value of my truck, pretty much. You come to someone with an AI system that can reduce the fuel burn or something like that. And that's much more difficult. Because they can't touch it. And the mining industry very much likes to touch the solutions. We're still a physical business.
I think that's where digital systems have historically struggled in mining in that there's been a viewpoint and that viewpoint is changing. People who are in charge at the moment still came into the mining industry at the end of probably when planning was still done on paper.
Niall Sullivan, Senseye: Yeah. It's difficult to shift that mindset. From what I see, I'm a member of Axora's community, I guess that's partly a reason why Axora that really good online community exists. Cause I know there's a lot of talk about digital transformation, AI and some of the technologies that they can leverage.
What sort of feedback are you getting from companies? Are they embracing these new ideas or are they still, and I know it's a company by company basis, I get it, it's not a broad thing, but just in general, I guess?
Joe Carr, Axora: The mining industry, it's certainly changed in the view that the mining industry is exploring, and the metals industry as well, is exploring digital technologies to solve their problems. It's not really a throwing people at it kind of industry anymore, which maybe it was in the past.
Certainly having a digital marketplace, those are the people we see. We engage actively with the people who are really interested in changing the way they work and finding digital solutions.
Cause one of the biggest problems we address as a business is the mining industry has a habit and the metals industry has a habit of reinventing the wheel. Everyone will have made the same solution, different companies have the same problem. And then they will all independently of each other, create a solution to that problem. And that's not particularly the most effective way to work.
If everyone who needed a car, invented their own car and drove it around, whereas you can probably centralize that and have a solution which works for everyone, which is much more efficient and easier to update and more cost effective. And I guess that's where the mining industry is getting to.
That's one of the things we do is helping them do that. But at the moment, a lot of the digital innovation in my mining industry is done in house and the same for metals companies. They create their own solutions to doing things. And actually there's certainly, when you look at it, you can say, there's not really a massive benefit to doing all your stuff in house and it's simply easier to buy it, why don't the miners and the metals producers do what they're good at, which is producing those metals. And what they're not great at necessarily is AI.
And even the ones that are good at it for every company, which is really well versed and has a hundred data scientists working on this kind of thing, the vast majority of your mining industry doesn't. For them, the benefit is there.
Niall Sullivan, Senseye: That does reflect your point from earlier about why you could talk to one company and they'd be fully embracing it and then a few miles down the road or the next country or next town down, they wouldn't be. And it's that sort of isolation dispute.
Is it a worry about sharing intel with competitors and that side of things, that's holding them back from sharing that knowledge?
Joe Carr, Axora: I think there's a certain amount to that because as an industry and that the metals industry is the same, although slightly different in that the metals industry, unless you're producing just a straight raw metal.
For instance, steel producers are a bit different. They closely guard their recipes and how they produce the steel because different steel does different things. And depending if you need high tensile strength or heat resistance or whatever, but for instance, the money industry, if you are running your gold company and I'm running my gold company an ounce of gold, is an ounce of gold. Doesn't matter if you produce it or if I produce it. It's still an ounce of gold.
There is certainly competitive tension within the industry that if I'm a lower cost producer than you I'm inherently make more profit, because I can't control the price I sell at. It's a market price.
You can go type into your computer spot price gold, and it'll tell you how much gold trades for right now on the London Metal Exchange. And as a mining company, you can't control that. As a metals company, you can't control that if you're producing copper or nickel or whatever.
Inherently any cost advantage is a competitive advantage, but we also have to look at fact that most of that's going to normalize. I may gain a competitive advantage for 12 months, but realistically, the mining industry, like many other industries and the metals industry is the same. People move from one company to the next. And the idea that you're going to keep hold of some sort of secret source thing, someone's not going to come move to another company and go, oh, these guys are doing that. And then they go, oh, that's interesting. Maybe we'll do that. And it just percolates around. It may take time. And there's a question of, is there a lot of benefit to that?
The overall industry, wouldn't it be better if we all moved along and developed technology at a pace together, rather then all trying to copy the same technology for five years before we move on to the next technology to copy for five years?
Niall Sullivan, Senseye: Yeah. Does make sense. I think you're right. I think that's how it is. A slow burner at minute about how digital transformation will eventually take off as people move between jobs and take that expertise into new roles. And obviously as a new generation, presumably will emerge. We hasn't just used paper and pen, those kind of activities as well.
The key aspect of digital transformation is clearly IT departments. And I saw from your innovation forecast that at least some departments are reluctant to actually embrace digital transformation. Are you able to put your finger on why that might be the case from that from their point of view?
Joe Carr, Axora: Yeah. I can't speak for every IT department.
Niall Sullivan, Senseye: No, of course.
Joe Carr, Axora: I think as an industry, we look at IT as having a specific role. Generally it's been, oh my computers broken, somebody needs to come and fix it. And I don't view that as being necessarily what it does anymore.
The IT departments really now worry in mining companies. There's a lot of worry about security. Cybersecurity is a big issue. We worry about how what is happening with data and where's it going? And how's it being stored and what is being done with it? And what are the potential impacts?
And I think a lot of the reticence for digital transformation, one comes from the people on site who just say, look, I don't have time for this. I'm busy, I'm running a mine. I don't want to trial some technology that may or may not work, bring me something that works.
From the IT side, anything new is very much viewed with the suspicion of how is this going to interact with our network? Where's the data going to go? What does this mean? Because the mining industry and the metals industry to a certain extent is very much built on its asset. If I know the mine and I know exactly how much of the mine is producing and how much metal is in the ground, that's the entire value of my company right there.
If I own one mine and if I'm smelting or producing the metal further downstream, refining it as a metal's company, the production throughput and how I'm producing my metal and all that kind of thing becomes very important. But a lot of that is digitized. A lot of especially the metals production, the refining, the smelting, the concentrating businesses, it's all done through scarred systems and all that kind of thing.
Very rarely is there, somebody sat in front of a control changing as the system works. It's big control rooms. And in the past that wasn't a problem because a mine or a mill or a refinery was an island. Wasn't connected to anything. Whereas today it is. The idea of ransomware wasn't a problem, but it will in the future. I don't know when it's going to happen, but it will happen.
At some point somebody's going to be running an autonomous mine, and all the trucks are going to stop. They're all going to stop one day. And skull and cross bones will appear on the screen. And it'll say, if you want your mine back, we want, $5 million or something. And until that point, either your trucks are going to not do anything, or we're going to start driving them into each other and smashing them up.
Destroying your assets. And the same in a refinery. The same in a mill, the same in a car plant that someone's going to get some ransomware into, for instance, I don't know the car industry, but Nissan's factory. If someone's going to get some ransomware in and all the machines will stop. Or worse, they'll build cars out specification that break in terms of industrial espionage or state sponsored terrorism or something.
And for the mining industry, it's absolutely terrifying view that everything could stop because if you take people out of an operation, as we are doing, and you are relying on machines, you've changed the weakness and the point of failure. If someone got sick and couldn't drive a truck, I could put another driver in that truck. If my network went down and all of the trucks not moving, I can't just have another network.
I can't just pop another network up. That's why IT departments. And that's just one of the reasons, but it's a great example of a reason why the reticence comes from because you, every time you make a little hole in the cyber security wall for something to come in and out, you are creating a hole that could be exploited because the mining company doesn't have control over the endpoint. That is at the other end with the company, with the technology. If that company is compromised, does that provide an in route into the mine?
Niall Sullivan, Senseye: Actually just on that point as well. Speaking more specifically about cloud systems is cloud based on what you just said, then they were lot to embrace cloud technology as well on that basis.
Joe Carr, Axora: And the mines have their own, they just have their own cloud. They'll get a cloud.
Niall Sullivan, Senseye: Their private cloud. Yeah.
Joe Carr, Axora: Yeah. And you mentioned using scarred the systems as well. I guess the point I picked out of that is essentially if the system's going to come in, I guess it's got to be seen as not is actually enhancing the day to day life either the person in making their job easier, but maybe not a reliance on it in terms of if something went wrong with it, like you said. It wouldn't turn into that disaster. But I was just more thinking actually on the sort of integration side, they are going to embrace different systems. They want them to all integrate and work together rather than working separately and creating those sort of holes that can be exploited as you pointed out.
Joe Carr, Axora: And the industry is very much when, at least in our survey, our innovation forecast, when we looked at it, almost every company said we don't have the skills in house pretty much across the board. We struggle to get skills, anyway.
But the second part is we don't want the skills in house necessarily, we're quite happy to outsource that to a specialist. It's finding the specialists and vetting them and understanding the needs, which is where the struggle, I think, still remains that a lot of people just don't understand the industry and that some of the solutions that exist just aren't appropriate.
And that's one of the problems with companies developing their own stuff, it's all and good. I develop my own AI system in house, but once I've developed it, how am I going to support that?
How am I going to provide updates as we go along? How am I going to provide security? And I don't think that tends to be a thought process that happens when things are developed in house.
And it's one of the reasons why external third party solutions for whatever your problem might be, machine learning, AI maintenance, any thing like that or anything else, third parties can be a better way to do it because generally that third party is a company that exists to deliver that product to an end user.
And it is very committed to making sure that product is the best it can be and is updated and does have security, and does have people at the end of the phone when, Windows updates to its next version, that everything just doesn't stop working. Whereas necessarily if you've done that in house, the person who's developed it may have left the company.
In which case you sort of end up with this classic Excel spreadsheet, which is 50 tabs long, and nobody knows how 48 of them work. But if they delete one, the macro in the background stops working.
Nobody touches it and we just use this one section, and that has an option of happening to in-house solutions where they've existed. And no, the original team has long gone. And no, one's quite sure how it works, but it works so we don't want to touch it and we don't know update it, but at some point it's going to break and then we're in trouble and we don't have a solution if it does break.
Niall Sullivan, Senseye: No. And also as part of that, it makes it more difficult to scale if they might be using it in a smaller way and they want to use it in a bigger way, but like I said, if it's a different team now working on it, didn't originally create it then.
The maintenance involved in the updates and the security side of it, it's a strain on internal resource. But also cause presumably if something's working, they want to use it in other areas, but obviously to do that requires support, more support, more resources. And hence why looking at external parties is a good route to go down.
Joe Carr, Axora: Yeah, exactly. It's the car and analogy again. If I build my own car, I'm probably not going to do as good a job as VW or Ford or a company that builds a car because it's just volumes and the ability to understand how it works and update it and all those kind of things that if I build everything bespoke, one off, it's just going to take far more time and effort. I initially cost me less because I already have the employees necessarily, but in the long run it's going to cost me more.
Niall Sullivan, Senseye: Yeah. I was going to a manufacturer who shifted, we don't predictive maintenance it, but had their own data science team and all that. But when they got to the point where they needed to sort of scale and actually roll it out wider that was the point that was holding them back and made them think, it wasn't actually about replacing humans in the process. It was actually, as I was sort of mentioned before, helping them to do their job better.
That's one of the dangers with AI, or a misconception let's say, or unless you disagree of course, but it's one of those things AI's going to take jobs away. What's your view on that, actually? I guess that's a good question.
Joe Carr, Axora: Yeah. I don't think so. Especially in the mining world, we're pretty automated. Obviously there are different viewpoints. If you go to Canada, your mines are pretty lean anyway, in terms of how they run. And this comes down to a bit, what I talked about earlier, which is the social contract and why things like remote operation centers can have an impact.
Because you go to Canada and let's say the mine has a hundred employees. If you go to a copper mine in Zambia, the same mine reducing the same amount of metal might have a thousand employees. Might have 10 times as many employees. And the reason about that is that there's a different social contract between the workforce. That if you want to build a mine in Zambia, they understand that with that mine comes lots of jobs.
If you want to build a mine in Canada, people will say, there's less jobs, but they're higher paid, for instance. That kind of social construct comes along. And when you're looking at doing something like a remote operation center, those thoughts have to come into your head.
Certain areas of the mining industry say, yeah, sure. Jobs will go. If I've got an autonomous truck, I don't need a truck driver..What do I need a truck driver for? If it's driving itself, I can have one driver for 10 trucks and that's not necessarily an issue because I've got a remote operation center and I can hire the people there and I can have a different workforce and they can go home and it can be more diverse.
And maybe the guy who just wants to drive a truck around and he's been doing it for 20 years, maybe he wants to retire. Maybe you don't want to sit on a plane anymore and do that. I think there'll always be movement in jobs, but then you've got to look at, how many people are employed in a remote operation center or how many people are employed in a data science team that wouldn't be there if those technologies didn't exist.
I think within the mining industry or the metals industry, the jobs will move and by implementing the technology we're implementing, we're actually making people's lives better. They don't have to stand around in a dusty environment and a noisy environment, which it's not necessarily pleasant to work in when they can work in a safer, more pleasant environment. I think any technology and AI is the same.
I think it will just change the way we work, but I don't think it will change the jobs. We'll still need the jobs. We'll still need people to do maintenance. It's just instead of changing the part every 5,000 hours, because that's what it says on the sheet. We might change the part every, this one, 6,000, because it's fine. And we know it's fine. There's no need to change it.
Next time it's 5,800 hours because it's been used differently or the rock's been more abrasive or the refractory bricks in the smelter have worn away at a different rate because of the content of the material running through, whatever it might be. I think it's just a smarter way to do things.
Case Study: Alcoa
Alcoa Corporation is a global leader in bauxite, alumina, and aluminum products, built on a foundation of strong values and operation excellence dating back more than 130 years to the world-changing discovery that made aluminum an affordable and vital part of modern life.
Alcoa operates production plants worldwide and have applied breakthrough innovations and implemented best practices that have led to increased efficiency, safety, sustainability, and stronger communities wherever they operate.
Discover why Alcoa partnered with Senseye to achieve best-in-class technology and operational practices for Predictive Maintenance.