Greg Kinsey, Global Head, Digital Manufacturing Solutions, Hitachi
Greg Kinsey describes how digitisation, together with technologies such as IOT and 3D printing, is transforming manufacturing and how this will ultimately make manufacturing more sustainable.
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Read the transcript of Greg Kinsey’s interview on digitisation, and how technologies such as IOT and 3D printing are transforming manufacturing and will ultimately make it more sustainable.Show transcript
How will digital technology transform manufacturing?
Digital transformation is a journey. And the initial stages of that journey are about improving the productivity, improving the quality of your manufacturing by using digital analytics and digital tools. As you advance on that journey, you can introduce new ways of working. Manufacturing becomes more modular, more flexible. And ultimately, it’s moving towards new types of manufacturing.
There is a trend towards mass customization, and that’s having the ability to basically create products per order. Products very specific to customers wants. Customers can design their own products, if you will. So mass customization is one of the big trends in that transformation of manufacturing. But it is a, journey and it starts with I think, some of the basic things – being able to increase efficiency improve productivity.
Another angle is the environmental aspects. We at Hitachi see that digital tools and digital transformation can contribute to running cleaner manufacturing. Manufacturing that has a lower carbon footprint has fewer waste generated, uses less electricity, et cetera.
How would you define Industry 4.0?
Industry 4.0, that’s shorthand for the fourth Industrial Revolution. And it’s basically taking a helicopter view of the last 250 years. We’ve gone through the first Industrial Revolution which was brought on by steam and the early industrialization, I would say. The second Industrial Revolution was all about mass production, consumerism. And the third Industrial Revolution was brought on by IT, and automation, and robots.
What we see happening in the fourth Industrial Revolution is the digitization of processes, digitization of products, and the digitization of work. And so being able to virtualize things, being able to move work around, create a data driven type of environment, and a data driven process. The promise of Industry 4.0 is a radical shift in productivity, an ability to improve quality, to improve workplace safety. And I think very importantly, change the flexibility and bring new capabilities to manufacturing.
How does IoT drive digital manufacturing?
The fundamental change starts not with the technology, but it starts really, with the people in the processes. So typically, what we look at is building upon the continuum of lean manufacturing. Building upon the continuum of best practise manufacturing processes. And taking that to the next level with digital tools.
In the early phases, what that brings you is being able to apply analytics and big data to continuous improvement of manufacturing processes. At the next level, you start to bring in new manufacturing technologies, such as next generation robots, robots which are more flexible to work side by side with humans, robots that can physically move within the factory. These are new technologies. And as well, there’s 3D printing and 4d printing which are emerging as new technologies to enable new types of manufacturing.
So as I said earlier, it’s a journey. It starts with the processes and the people. And then builds upon that by using data. And then builds upon that with newer manufacturing technologies such as advanced robotics and 3- or 4D printing.
How will 3-D printing affect manufacturing?
3D printing will have massive implications for manufacturing. The early use cases are fairly limited right now, but what companies are finding that 3D printing unlocks the ability to create new products, new geometries, which have up till now, have not been possible. It allows you to virtualize some of the production, because you can basically take a digital file, and you can create things directly from that digital file.
It enables you to move production. So say you need a spare part at a very distant location. Rather than centrally manufacturing that part and then shipping it, you can actually produce that part locally where it’s needed.
On top of 3D printing, you have 4D printing now emerging. So with 4D printing, not only do you 3D print a product, but then you have the ability to make that product change based upon a stimulus– whether that’s temperature, or an electrical impulse, or whatever. That product will be able to collapse itself to fold itself, to expand itself. And so even moving on to 4D printing, that’s probably one of the ultimate use cases of what we call IoT.
Many companies feel constrained by the IT architecture and infrastructure of industry 3.0. And that was a very traditional structure of applications such as manufacturing execution systems and ERP each having its own database, each being really optimised as a monolithic monolithically type of physical software application.
Industry 4.0 is all about digital. So digital starts with the concept of a data lake. You have lots of big data, and it’s using that data universally. So the data is aggregated. The data can be shared, and apps can be developed, which use that data for different purposes.
And so what many companies are doing is they’re starting their digital effort in parallel to the existing legacy IT effort. I think the dream for many companies is to be able to switch off today’s IT systems, and be able to run their complete company on tomorrow’s digital platforms.
What is the difference between IT and digital?
IT and digital are really two different animals. I think it starts first of all, with the architecture, which I mentioned earlier, as well as the overall approach. But more importantly, IT is about known solutions for known problems. Digital is more about unknown solutions for known problems. Or actually, unknown solutions for unknown problems. So by definition, digital is innovation.
And when you do innovation, you’re not sure exactly where you’re going. You’re sure of the problems you want to solve, you’re sure of the performance that you want to end up with. But in fact, many digital projects go in different directions. You so call pivot, you change directions. As you develop digital applications, as you develop digital projects, often, you fail. And through that failure, you actually learn. And that brings new learning and new understanding, which can then continue to build the innovation. But it’s very much an innovation process.
Contrast that with IT. IT is very much about reliability. It’s about cost. It’s about knowing what you have, knowing what you’re building. When you start an IT project, you know exactly how many weeks it’s going to take. You know exactly the resources that you need. And you know functionally, what you’re going to end up with. With A Digital project, you don’t know any of that. You don’t know how long it’s going to take, you don’t know what skills you need, and you don’t know what the final solution is going to look like. It’s innovation.
Can you draw a roadmap to digital transformation?
At Hitachi, we’ve developed a roadmap for the digital transformation of manufacturing. So there are six phases in that roadmap. And behind each phase, we have identified the types of capabilities that are needed to be developed and put into place to achieve that phase. It’s a journey. Might be a five year journey, might be a 10 year journey. The key is to be able to unlock value at each stage of that journey.
So there should be a very clear ROI within the first 12 or 18 months of that journey, and you should continually build upon those initial successes.
The early projects are quite simple. It’s about visualising the end to end process. It’s about digitising analogue data. So typically, you go into a factory, and there are whiteboards with lots of numbers written on them. And what we do is we find that we can digitise those whiteboards. And it brings two or three real benefits. The first benefit is that the data never disappears. You can do historical analysis, you can do trending. That’s a big deal.
Secondly, you have the ability to share that data up and down the value stream. In today’s manufacturing environment, if something’s written physically on a whiteboard, you cannot move that data. You need to go to see it physically to understand that information.
And thirdly, of course, is that allows you to then start to build higher level analytics. As you move up and progress with your digital transformation, you get into what’s called predictive analytics. Predictive analytics is where we’re doing most of our projects today. And that’s really being able to predict problems before they happen. So predict quality defects before they start to happen. Predict a bottleneck in your production line. Predict downtime before it actually happens. So there’s a lot of value in that. We have many projects that we’ve done already and all three of those cases that I just mentioned.
Moving beyond predictive analytics, you get into prescriptive. So not only then can you predict a problem before it happens, but the system will suggest things that you can do to prevent it. So let’s say for example, you’re predicting a bottleneck in a production flow. It will also recommend that if you resequence the work orders, you can minimise that bottleneck. Or if you turn on another machine, and then move an activity from machine A to machine B, that might be a way to reduce that bottleneck. So that carries a lot of value because not only can you see the problems before they happen, but you can prevent them from happening, or at least alleviate some of the negative impact.
Can digital make manufacturing more sustainable?
Sustainability is a big part of digital manufacturing. Not only is there productivity benefits, but efficiency benefits which come across with using less electricity, less materials, less waste. Also, the movement of materials is a big contribution to carbon footprint. And if we can reconceptualize an industrial footprint or reconceptualize the value chain, we have the ability to reduce the carbon impact of those industrial operations.
How can digital promote life long learning among employees?
Digital transformation has a very big impact on the employees of a factory in several different dimensions. First of all, it’s a chance for employees to bring their ideas to the table. It builds upon the principles of kaizen, the principles of the people in the process know best how to improve it.
But it takes that to a new level, because in the innovation process for example, they may say, well, if we were able to monitor the noise that a machine makes, that would give us really good insight to the process. Because when the machine goes tick, tick, tick, tick, tick, tick, I know it’s running well. When it starts to go tack, tack, tack, tack, I know, for example, that it needs to be lubricated, or something needs to be changed, or a problem is about to happen.
So that knowledge of the employee is actually contributing and shaping to that use case. And they will bring in that knowledge of having worked many years on the production line to say the noise is an important factor. Or maybe noise is not an important factor. Maybe a visual inspection is a very important part of it. So the employee will bring their ideas forward on how to best shape and how to build those digital apps, if you will.
The second thing is that digital apps are all about making life easier. The development of predictive analytics will make not only the manager’s life easier, but the line worker, the production operator’s lives easier by eliminating the amount of problems that they have on the day to day work. So the vision for the factory ofthe future is a factory that moves from firefighting and problem solving to something that’s more predictable and something that’s more reliable. And everybody wants to work in a predictable and reliable workplace where you’re not constantly having to fix, and fiddle, and really solve problems on an ongoing basis.
There’s a cultural change involved. I think it moves from a firefighting culture to one of innovation, to one of thinking forward, to one that’s more proactive. I think the factory of the future will be much more showcase and a playground for innovation. And today, when you talk to manufacturing people, typically, they don’t talk a lot about innovation. They talk a lot about making what we have work or work as it’s designed to, rather than dreaming about new ways of doing things, and ways of doing things better.
So I think the two things are very interrelated. Digital and innovation can come together, and can engage the entire workforce in that journey.
Is this the end of “dirty, dull and dangerous” jobs?
Well, I think world class factories today are generally not very dangerous or dirty. There is a perception for people who have not been in factories, but many world class factories are already at quite a high level. I think safety is a key issue for many industrial operations. And digital is a way to prevent things from happening, where people do experience injury or health issues related to the daily work.
I think the future factory will be more modular. And I think it will be more flexible. And that whole flexibility of the workplace is also a major change to the environment, the working environment.
That’s one of the big differences between digital and IT. In these digital projects, we always start by exploring the problem or the job to be done. What is it that we’re actually trying to achieve. How do things work today. It’s really understanding the process, understanding a hypothesis about what causes quality problems. Or a hypothesis about how you could improve productivity.
That requires design thinking. That requires stepping back and understanding the customer requirements, understanding the worker requirements, understanding that whole environment. So we use a lot of tools. We use ethnography, for example. We do what’s called an FMEA, failure mode effects analysis. We have an approach of mapping out the processes, of sketching out and visually representing what’s happening.
So that whole first phase is really about design thinking. So understanding what’s happening on the shop floor, understanding the processes.
Then you move into the agile phase, which is another phase. And that’s about building a minimum viable solution. It’s building a minimum viable data set. It’s a very innovative process, where you go through cycles, maybe a one week or two week Scrum cycles using the Agile method.
And along the way, you experiment. You try things. You say, what if we add some more data, what would that do to the model. Or what if we build some functionality, let’s try it. It might work, it might not work. So you fail along the way. And from each failure, you learn. And you continue through that agile cycle.
That’s hard for people to learn how to do if they’ve not done it before. And so again, in the projects that we do, our clients say, the cultural change from traditional engineering mindset to this Agile mindset is a leap. It’s a big leap forward. The design thinking is an important front end to that, and it really drives the first part of that whole analysis, and the development of the hypothesis of what the solution could look like.
One of the key lessons we’ve learned is don’t start with the technology. Start with the processes, start with people, and start with the problems to be solved. Most innovations fail because people jump to a solution too quickly.
The IT industry loves selling solutions. It’s not about buying a solution, it’s about solving a problem. The way you solve the problem is you have to first dig into the process, dig into the operational constraints, and most importantly, engage the people who work in that process.
So we have an approach we call co-creation. It’s built upon mixed teams. We bring in people of different skill sets, we bring people from Hitachi in, we may bring people from suppliers in, we may bring customers into that process. Each person brings a different perspective or different skill set in the co-creation process.
There’s no right or wrong answers. That’s an important part of it. We don’t go in with any preconceived notion of what the solution should look like. But rather, we innovate. And by innovating, we create new approaches, which are oftentimes novel, unproven, and sometimes, even things that people don’t believe could possibly work. And the teams figure out how to make that stuff work.
So it’s very empowering, and it’s a very different way of working. For the employees, everyone who’s involved in this co-creation process will say, this has been a career changing experience for me. It’s allowed me to learn by doing, but allowed me to learn from the other people in the co-creation team.
So you might have a mechanical engineer who’s an expert on some of the mechanics of what’s happening. You might have a Six Sigma black belt who’s an expert on the statistics behind the process, and can build a process model, and can perform and design experiments to understand the different factors that contribute to the process performance. You might bring in a designer, who’s very good at designing the overall user experience, or designing the overall process flow. You’ll bring in programmers who know how to build software to do different things.
So it’s a mix of skills. And for many people working in such a multidisciplinary environment, it’s a great experience. That multidisciplinary environment is necessary in order to really have those breakthrough innovations.
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