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Industrie 4.0: Coming of the cyber-physical age
Are we on the cusp of the 4th Industrial Revolution, the cyber-physical age? Where machines and products co-operate to drive productivity.
So yeah. I’m Alan Norbury from Siemens. I started with Siemens in 1978 as an apprentice and stayed with the company ever since. So I spent some time in Germany looking after global accounts, one of which was Philip Morris, who do cigarette making machines and cigarettes as well, although I don’t smoke myself. But the machines are very, very interesting, about 12,000 cigarettes a minute. And they sample every cigarette 50 times looking at density. And then they eject the right one off of the end further down the line. So quite challenging, as you can imagine. I came back to the UK. I became product specialist for hot standby PLCs, fail safe PLCs, high speed counting positioning.
And then eventually I set up my own team of application specialists, which is a team of technical consultants based all around the UK. I did that for 17 years. And then in the last three or four years I also started working with catapult centres, universities, and last year became Siemens industrial CTO, which meant it became a full time job. So industrie 4.0… Actually, the first industrial revolution started here in Britain in the 18th Century. And this was based around our expertise in mass production of cloth. So with the Arkwright’s spinning frame and Samuel Crompton’s spinning mule meant that Britain was the centre of mass production of cloth globally. It was all built around steam-driven machinery, motor-driven energy.
And the second industrial revolution was when we started to see electricity-driven conveyor system, so mass production. And apparently the first evidence of that was in the Cincinnati slaughterhouses in 1870. The third industrial revolution - I kind of remember some of this - was when we saw IT being used in manufacturing. So the first PLCs, for example, were been used. And Siemens very first PLC was called Somatic G. And it was announced in the Parish Machine Tool Fair back in 1959. So Siemens have had decades of experience working with automation. The fourth industrial revolution is… well it’s actually started already. And it’s based on something called cyber-physical systems. This is where the virtual world meets the real world.
It’s all to do with the internet of things, to do with big data flexible manufacturing, robotics. All these things put together are the underlying principles behind industrie 4.0. So we live in a connected world, which is changing the way that we do business. And this is putting great pressure on manufacturing. How do we address those challenges? If you look at some of these business models, for example, today you don’t necessarily have to go to a library to read a book. You can download it onto your Kindle, for example. I don’t know if any of you ever still use the Yellow Pages. I certainly don’t. In fact, the last time I did I used it to prop a door open.
So we just don’t use it anymore. We go on the internet and we find phone numbers through the internet. Same with records as well. You can stream records and music. So the point I’m trying to get to here is those businesses that are becoming the masters of data are becoming very successful. It’s the way you handle that data and reuse that data, develops business models that have been successful. So what are the drivers behind industrie 4.0? Well, it’s actually consumers, you and I. And our expectation for innovation is putting great pressures on manufacturing. And there’s an expectation for shorter innovation cycles. And what I mean by that? For example, the mobile phone. This phone’s about two months old now.
And it’s out of date already. So how do the manufacturers address that challenge of accelerated innovation, the expectation by consumers? Increased flexibility. So what I mean by that is can a manufacturing process produce more than one product? Is it flexible enough to be able to produce more than one product? And efficiency. And I don’t just mean energy efficiency. Obviously, that’s very important. But also the efficiency of assets of machinery, making better use of machinery and optimising the machinery. So industrie 4.0, as John said, it did start in Germany back in 2011. There was a gentleman called Henning Kagermann from a research establishment called Acatech. And he came up with this vision. And he announced it at Hannover Fair in 2011.
And then in 2012, he got together with a guy called Dr Siegfried Dais from Bosch. And they took it to the German government and said, look, this is the way we’re going to increase productivity in Germany. This is the future of manufacturing. And then the German government put 200 million euros into further research into industrie 4.0. And today it isn’t just a German thing anymore. It’s a global, let’s say initiative. There is a bit of a race on. And as you said before, Jan, the Germans are ahead of the game followed very closely by the Japanese, the American, and the Chinese. And as you can see, there’s no Union Jack on there yet.
It’s one of my passions to try to get the Union Jack at least part of the peloton anyway. So we need the right level of government investment. We need to invest in the right ways. And one of my passions is trying to help manufacturing, understand what the principles are underneath industrie 4.0, whatever name you call it, and why we need to adopt it and where we need to invest. So cyber-physical systems, this is probably the best slide in terms of explaining what I mean by that. And if you can imagine there production line, let’s say a bottling line. And that will be broken down into production units.
So you’ll have a filling machine, you’ll have a labelling machine, you’ll have a capping machine. And if you can imagine one of those machines, in an ideal world, what you would do is you’d develop that machine in the virtual world. So you’d include the automation, the safety, the mechanics, everything in the virtual world. You can’t do all of that today. But that is the direction manufacturing is going in. So some of the things you can do, you can do the 3D modelling of the mechanics, for example. And then once you’ve gone through the prototype iterations in the virtual world (so you’ve ironed out all the problems in the virtual world) you then start to produce your physical model.
And in theory, if we get this right, that will be the final model as well. It won’t be just a prototype. Today what happens is some work is done here and some development work is done here. But in the long term, everything will be done in the virtual world. So you minimise the number of physical mistakes that you make. So once you have your machine, you start… let’s say a capping machine. You start capping your bottles. And then as you go through the lifecycle of the machine, your digital footprint would get bigger, and bigger, and bigger to such a point where you can make use of that data.
And what I mean by that, I’ll give you some examples, is condition monitoring. Condition monitoring analyses the vibration of the machine, or the motor, or the gearbox, or whatever. And it can, through the harmonics of the vibration, it can determine when something is going to fail before it fails because you’re looking for trends. So in theory, based on that information, the machine could be self-healing. If you’ve got the right technology built into the machine, it could also self-optimise. It can become self-aware. So it can adjust its parameters internally. And then the next challenge is, well, we talk about mass customisation. So if we got production line making product A, can we change that to make product B?
And I don’t mean from a mobile phone to a car, but fairly similar products. So what you would do is you’d then go back to your virtual model. And you’d try it in the virtual to see if you can make product B. And if we can, then we migrate those parameters across to the actual machine, which could include robotics, give you more flexibility. And you start making product B. Potentially, you could make product A or product B. They’re in the same production line, very much like we do in automotive today. Same production line makes all the different types of customised cars. So this is what we call cyber-physical systems.
And eventually, you’ll get to the point where everything is zero prototyping, zero physical prototyping.
So Siemens have decades of experience, market leading experience in electrification and automation, last year we changed our organisation on a global scale. We have 32 divisions. We rationalised it down to nine. And one of those divisions was called the digital factory division, which is the division I work for. And the reason we did this is we already knew a little bit about industrie 4.0 and what the demands were. And we also have the technologies as well, these technologies over here on the right. So things like sensors, sensors are becoming more intelligent. They have web servers built into them. It’s part of the internet of things. Storage capacities are becoming greater. Data analytics is becoming cleverer.
And networking very important as well, the infrastructure that we have available, whether that’s wireless copper or fibre optic. So if you was to start a brand new facility and I know this isn’t always the case, where would you start to invest? Or, even if you had an existing facility, where should you consider starting to invest? And there’s four cornerstones to what they call the digital enterprise platform. First of all transparent factories and flexibility in manufacturing. So I mean things like robotics. So are your machines capable of making more than one thing? Are they flexible enough to do that? If you can’t make a certain product in one factory, if your factories are connected, can you make it in another factory?
And that could be a global factory, anywhere in the world. So that’s the first step. The second step is supply chain. How do you connect your supply chain into this flexible manufacturing environment so that you can provide products just in time, very much like the automotive industry today, but in other industries like food and beverage or water. So the same philosophy will apply across all industries. The modelling and simulation, as I’ve already explained, really, that the fact you can model something in 3D card. You can virtualise it. You can test it in the virtual world. And last but not least is the infrastructure.
So one of the things I challenge the customers that I deal with is go down your manufacturing process and look at all your machines. And ask the question, how many of the machines are capable of becoming part of the internet of things? In other words, has it got ethernet port on it? Can the machines talk to each other? Can the factory floor talk to the office environment? And then last but not least is can then your factory talk into your supply chain? So they’re aware in real terms, or real time should I say, the demands of the manufacturing process. So you need that connectivity. But you’ve also got to do it security as well.
Because if you can imagine, if you was a managing director of a factory, and then somebody’s come along say, right. Well, you see that machine there? Anybody in the world can access that machine. They’ll say, right, disconnected it now, you know, but it can be done in a secure way, which comes on to this area. So Siemens has developed some new ways of developing our business. It’s all based on big data. And what we’re doing is we’re converting it into smart data, then delivering business data to the customer. So a good example is Heathrow Airport. They have 4,000 conveyors. Each conveyor will have two motors. But in the motor, you may have one or two bearings.
It just takes one of those bearings to fail. And that could be havoc. And there’d be backlogs of traffic all the way around the M25. So what Heathrow Airport want to know is, where’s that conveyor going to fail before it fails so they can make a business decision? And the business decision might be I want to slow the conveyor down so it lasts a lot longer, a longer period of time until the maintenance period. Or, I might want to stop it and divert production. So they can make a business decision based on this business data. They’re not interested in the big data.
Could you imagine the amount of data around analysing all the harmonics of all the vibrations of all the conveyors in Heathrow Airport? It would be horrendous. So all they want to know is the Business Data. So plant analytics is one way of doing this, asset analytics, energy analytics, condition monitoring, and then also security. So one of the services that we offer now is we’ll go to a plant. And we’ll look for vulnerabilities around a plant and then remove those vulnerabilities. So coming back to the future of manufacturing and the way that we’re changing our business models is if you can imagine your factory floor would consist of automation, CNC machines (hopefully Siemans) communications, third party products.
And what will happen in the future is organisations (and I don’t just mean Siemans) I mean machine builders. There might be system integrators. It could be WMG, will be developing these cloud-based industrial apps. And this will give you the visibility, that business data at your hand on your mobile phone, or your iPad, or your PC. So the challenge then is, how do you access the data from the factory floor? So Siemans have got an activity that we’re going through with SAP HANA. And this gives you that security between the factory floor and your cloud-based industrial apps. Now, SAP HANA is actually used in 90% of industry already for transactional information, for order processing, etc.
So when you talk to the IT managers and say, right. Well, how you going to do it securely? If you’re going to use SAP HANA. You’re already using it. So that’s quite often the biggest challenge talking to the IT manager about secure communication. Well, if they’re already using it, why not use it in this way? Now, if you think about it, Siemans could do ourselves out of business because we sell HMIs and scala systems. That gives you that business data. So the way we’re changing our business model is based on the data. So we will be the custodians of the data. So we’ll make money on the data.
The people who develop the apps will make money on the download of the apps. As far as the manufacturer is concerned, they get their business information when they need it. And coming back to the supply chain, quite often some of these large software packages are very expensive, like MES software, for example. And the supply chain can’t afford it. Whereas if you use this model on a pay per use model, they only use a small amount of data. So they don’t pay as much. The large manufactures, like Siemans, will pay a lot more because we’re using more data. So therefore the model works all the way through the supply chain.
At the moment, we’ve got five global pilot users of this technology. And so far, it’s been very successful. So now we’re going to start looking wider than those five pilot users because I think this would be the way forward in terms of gathering data and turn it into business data. And I was asked by our managing director about three years ago to try and get my head around industrie 4.0 and bring it back to the UK. So I went over to Germany. And I found out that Siemans have got two of these smart automation cells. There’s one in Nuremberg, which is based on discrete great manufacturing.
And there’s one in Karlsruhe, which is based on process of liquids, for example, things in pipes. So I visited this one here. And it’s all based around mass customisation. So every product has an identification on it, like a barcode, or an RFID code. And it tells the machine what to do to it. Whereas traditionally, the machine would decide what to do to a component. Now the component tells the machine what to do to it. Hence you get mass customisation because every product is different. There we go. So this is what they did was they 3D modelled the whole machine first, so each one of those elements as an individual file.
And they developed what they call JT model of the machine. And I said to the guy, how do I bring it to the UK, because I want that machine in the UK? And he said, very easy. I’ll email it to you. I said, what? The whole machine? He says, yeah. And he sent me these 3D CAD files. And I emailed them through to the MTC where they have a virtual reality cave. And within half a day, they had the whole machine running in the virtual reality cave.
And what amazed me, when I went to see it the week after, is that I could actually explain the machine far better in the virtual world than I could in the physical world because you can go inside it. You can go through it. You can point at things very easily, which you can’t necessarily do in the real world. And we used this model all over the UK now. I’ve emailed it to lots of different organisations. They’ve all got VR caves. And we can use it for government investment. So I’ve shown this to quite a few government administers to say, well, this is the future of manufacturing. We need to invest in this technology.
So just to summarise, three key things to take away is infrastructure. So do you have the capability of becoming part of the internet of things? Where do you start investing? Secondly, virtualisation, can you 3D model your facility or your machinery? And thirdly, the skills, which I haven’t really touched on. And I think the skills we’ll need for the future will be hybrid skills. We’ll need mechanical skills, we’ll need electrical skills. But we’ll also need the skills for the virtual world, these 3D modelling type skills. Because the engineers of the future will probably spend more time in the virtual world than they will in the physical world. That’s where all the engineering will be done in the future.
Why should we do this? Well, potentially batch sizes of one, because consumers like you and I expect customised products, like customised garments, customised food. Our taste is changing. We expect customisation. So we’ll have to be able to manufacture mass customised products. Show us a time to market so we can innovate a lot quicker, potentially zero prototyping. Then highly flexible manufacturing as well so we can make more than one product on the same production line.
So the Centre of Economics and Business Research said that if we adopt automation and robotics to the same level as the best in the world, which is Germany and Japan, we would increase our productivity by 22% and employment would increase by up to 7% in the long term. So it would decrease initially. Then we’d reskill, upskill. It would increase employment by 7%. That’s with technology that’s available today and been used in other parts of the world. And then AccuSet said that industrie 4.0 would increase productivity by up to 30% within the next 10 years in Germany.
So you think of our great engineering pedigree and the right level of government investment, there’s no reason why Britain can’t be back in the driving seat of the fourth industrial revolution. Thank you.
Are we on the cusp of the 4th Industrial Revolution, the cyber-physical age? Where machines and products co-operate to drive productivity. Or is it just propaganda?
In the video above Alan Norbury, the Industrial Central Technology Officer (CTO) for Siemens, puts the 4th Industrial Revolution into context. The term Industrie 4.0 originates from the high-tech strategy of the German government, which sought to re-define the role of manufacturing post global economic downturn. It suggests that we are on the cusp of the 4th Industrial Revolution, a cyber physical age, which will be realised over the next 20 years. It is an age in which materials and machines are inter-connected within the internet of things (IoT), where everyday objects have network connectivity, allowing them to send and receive data. Enabling highly flexible, individualised and resource friendly mass production.
This will drive new business models, that are ‘the masters of data’. It is driven by a requirement for shorter time to market, increased flexibility and greater asset efficiency. At its core is the cyber-physical-system (CPS) of which there are 4 cornerstones:
- Transparent factories – internally and externally networked
- Integrated value chain with seamless engineering
- Use of intelligent models
- Modular and networked secure automation
There are some cynics who believe that Industrie 4.0 is just German propaganda. A way to invigorate German manufacturing following the global economic crisis. Others argue that we are on the cusp of the cyber-physical age and it is an important consideration of both industrial and corporate strategy.
Talking point
- Do you think that the cyber-physical age is the next stage in our industrial evolution or hype?
- Is it appropriate for all types of products?
- Will there still be a role for more traditional forms of manufacturing?
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Supply Chains in Practice: How Things Get to You
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Supply Chains in Practice: How Things Get to You
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