Industry 4.0 is the hot topic among manufacturing companies right now. With the movement seemingly wrapped up in taking automation to extremes, attendant concerns about employment in manufacturing have come to the fore. Calum MacRae of just-auto talked to the CEO of leading2lean, Keith Barr, about their differentiated approach to 4.0 which seeks to put the human in the driving seat.
just-auto: Tell me about your company and its genesis.
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Keith Barr: The company started in 2010, and really was born from one of my business partners working with Toyota for four years and living with the Toyota production system in his plant. What he tried to do was exactly what Toyota does in its factories in Japan and it didn’t work as well. So what he discovered was we’re more an individualistic society and there has to be some form of personal connection and personal accountability in order to drive the right behaviour.
We took inspiration from gaming technology around a technology platform to influence people on a personal basis in tasks
He took on the principles from the Toyota production system as far as recognising the value of people and the ability of people to solve problems and innovate. But we took inspiration from gaming technology around a technology platform to influence people on a personal basis in tasks. It’s a little bit unusual and we’re working with a lot of different companies and getting a lot of success with it. But it’s really driving the engagement of the workforce on the plant floor.
Our objective is to really help drive continuous improvement and create a continuous improvement culture in companies, and we’re doing that through a real time collaboration and problem solving methodology that we provide as a cloud solution.
We have a wide cross section of customers: a lot in automotive, but a lot in food, and pharma, and oil and gas. In every case, our customer’s sites have realised significant improvements.
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By GlobalDataIt starts with the personal accountabilities through transparency to what they do. So we’re capturing things that normally management doesn’t see. There’s sort of a hidden plant that exists, and most management knows it exists, they just don’t know what the workforce is having to do to ensure production continues and to handle problems. So, our system provides visibility to that. We’re capturing their movement and the activities that they’re using to solve those issues immediately. They come back around and do focused problem solving and present the ability to solve problems in their immediate work area, which becomes a very personal thing to them.
j-a: Are you putting sensors on each individual on the shopfloor?
KB: We don’t actually. They do typically have an individual user ID. With our application being cloud based, a smart phone or anything with a browser can access it. So, they’ll log in and get a notification specifically to them or escalation specifically to managers based on the way the protocols are set up in the dispatch sense. In the process of doing that, they’re having to acknowledge that and now everyone can see that they’ve acknowledged it and that they’re the ones working on that particular issue and problem. It’s very interactive. So it tracks movements and activities on a very granular scale without anything more than a smartphone.
j-a: You talked a bit about the gamification that you’ve introduced. How does that work? Are there rewards for the individual?
KB: So there are two elements to the gamification, what gamers call white hat incentives and black hat incentives. Black hat incentives are those things that are the lower level of Maslow’s hierarchy: the need to belong, the fear of confrontation or appraisal. So initially we use the elements around individual accountability; making their activity transparent to others and recorded in a way that someone could come back to them later and say, “Hey, you didn’t do the right thing, or you should have documented this differently, or I need to understand more about what you did.”
The white hat incentives come in the form of being able to solve problems in their own work area. Events that they are responding to, they’re able to be captured and those events are quantified in terms of production impact. With this at the end of the week, or end of the month, you can step back and say, “Where was the greatest production impact for those things that are in my area?” If the individual has all those events that data can be drilled into and problems can be solved and then time is gained back.
Of course the business benefits from that as well. But, it gets people very engaged because they can also analyse the trends in the data. They can Pareto the data first, to see where problem solving should be focused, and after the problems are fixed they can revisit the data and see if less time is spent on the initial problem area.
j-a: You said earlier that your company is carrying this out for many companies, not just automotive. Can you expand a little more?
KB: The way we look at manufacturing it is everything we eat, touch, consume, use. It’s all manufactured someplace and the workforce that exists there is a critical element to that. That’s kind of where the Industry 4.0 or Manufacturing 4.0 fit is.
We see Industry 4.0 as a level of maturity that recognises the cyber physical elements that capture and leverage human capital and the human brain in a way to effect how they think and how they see the pattern of problem solving
We see Industry 4.0 as a level of maturity that recognises the cyber physical elements that capture and leverage human capital and the human brain in a way to effect how they think and how they see the pattern of problem solving. So we have a significant number of customers that are quite sophisticated in the way that they gather information and data, but automotive, especially the automotive supplier community, is not as mature as the OEMs. They have a lot of cases of very manual operation, so the equipment is much older. There are some environments that aren’t prone to automation or automated equipment. Sensory technology has been a great boon to visibility to things that are beyond some of the current human controlled equipment even. Using that data has been the challenge and leveraging or determining the value of that data is a bit of a challenge. So, it’s difficult to justify an ROI for a big sensor investment. What we’re finding though is that we can provide value in two ways. Understanding where people are moving gives us the ability to know where an investment in sensor technology automation makes sense. Once the information is there, it can be used at the point of task by the people who are responding or maintaining the equipment or upgrading the equipment so that they can make the next decisions. We are boiling the data down as opposed to people having to do deep dive analysis.
There is a bit of an AI component there. Some of it based on narrowing the scope: you work in this area, you work on this equipment, you are producing this particular product. So the things that come to bear on those things, that’s a very fast filter that we can put in. But there’s other elements that we’ll put in that are more predictive.
j-a: What in your mind marks 4.0 against naturally increasing automation? Do you think there’s a natural staging post for 4.0?
KB: It has to be the evolution of automation. I think we are a long way from manufacturers being able to not depend on and leverage human capital. So the more we can enable that today, the more we’ll understand how best to leverage that to drive a different level of intelligence in automation, and we are quite a way from that. Artificial Intelligence has matured very slowly because we’re still not quite focused on truly capturing the way people behave and move and think. We are doing things on a fairly low level compared to what sophistication exists in the human mind. We are mimicking speech and we are mimicking movement in machine operation with robots and things like that, but getting it down to making the right decisions and being able to think and compare we’re quite a distance from that.
That’s why we think realising 4.0 is really about having that human capital engaged and enabled in a way that leverages their unique value as human minds, and that’s going to be around for quite a while.
j-a: Do you see 4.0 as a natural progression of lean theory?
KB: I think there’s elements that can certainly be modelled into it, but not always. Manufacturers in the investment of automation, I think marginalised the workforce, and probably put us in a position we weren’t innovating as much, because we looked at human capitalism as a variance problem, thinking, “We have to move them out of the production environment. We have this machine that consistently do the same thing without mistakes.” That has marginalised the value of human capital, and we are seeing that come back now. Certainly through our approach, and the way that we are enabling that, to drive innovative problem solving.
j-a: You talked about problem solving there, do you think Six Sigma still has a role in the Industry 4.0 world?
KB: I think it does. I think we are going to be looking at information and how to use information patterns to be more predictive. AI as a place for all the data that is in the plant certainly can point to statistical problem solving like Six Sigma.
But I think the value of doing problem solving in the task, in real time, exists and is occurring right now. Part of it is in the models we’re doing with human capital, and I think that’s the part that’s going to get replaced with more automation and more predictive thinking. It’s not looking at data for the last year and trying to predict some pattern it’s, “I’m in the moment and I’m responding to I’ve got an issue that’s impacting production right now.”
4.0 is almost going to accelerate or turbocharge Six Sigma so we’re problem solving instantly
So 4.0 is almost going to accelerate or turbocharge Six Sigma so we’re problem solving instantly. But it’ll be at a lower resolution or narrower scope than most Six Sigma projects. It’s not going to be project based. It’s going to be task based.
j-a: What do you see as the main challenges in implementing 4.0? I would imagine there’s a lot of change management that has to be brought to the organisation when they introduce your systems…
KB: Actually not. Manufacturers need evolution, not revolution. Manufacturers are essentially printing money – production lines have to run because that’s money. So they are very sensitive to change and I think evolution that doesn’t feel like change is a much more digestible approach than saying we are going to come in and retool everything or change the operation. So what we do is we come in and overlay the existing operation initially, just to provide visibility to that hidden plant that exists. Once that occurs, management has that visibility to what’s happening and they can start turning the dials or adjusting the process a little at a time. They can add a poka-yoke step or use that to feed back into the way the operator runs the machine and so the next time the machine operator logs in they see that standard work change. It’s making a more real time loop around those things, but it’s really capturing what they’re doing today, in a more standard process. In the first month our customers are typically just adding protocols for the things that they respond to on the floor.
It starts providing that process to eliminate problems and focused problem solving as well as improve the process in the way they respond and correct issues. That methodology now starts getting expanded to other areas of the plant. We have a lot of customers that do kanban-based delivery to the line in a spider schedule. Our system gives them the ability to see where the spider schedule is not keeping up. So, they’ll do what they call a material hotshot or immediate replenishment of material at the line. Well they’ll use that emergency replenishment signal, they’ll capture that and see how often it occurs, and if they don’t have any in place they realise they can probably lower inventory. By iteratively lowering stock, looking at where emergency replenishments start occurring, solving those problems and so on businesses can operate on much reduced inventory levels. Once workers get into the pattern of solving problems we find they continue to want to solve problems be it reducing the takt time or reducing inventory levels.
j-a: Do you have any real and tangible examples of the benefits of your approach?
Once they start on this path, the workforce embraces this continual improvement and every metric they measure tends to see a 7-10% annual improvement
KB: Operational availability of equipment is probably the biggest thing that we impact immediately because we increase the response time as well as eliminate recurring problems. We are seeing, within the first six months, a 5% increase in operational availability of equipment; in one plant this occurred in the first five months. Plants can successively reduce the cost of a product as a result of the increase in availability. We’ve also seen improvements in quality of 7-10% every year. Once they start on this path, the workforce embraces this continual improvement and every metric they measure tends to see a 7-10% annual improvement.
In the early years, it’s quite large because there’s a lot of improvement! For a company like Autoliv, they reduced the cost of product over 95% over the last twelve to fourteen years and that’s dramatic! It’s like putting money in a savings account. We have a defence contractor customer, the largest bullet producer in the world, who has reduced the cost of product over 40% in the last four years. Customers will say it’s the most dramatic thing they’ve ever done.
j-a: Industry 4.0 has been cited as a means for established economies to begin onshoring manufacture again, but there’s been a lot of reports in the media that onshoring won’t necessarily mean more jobs coming. What’s your view on that?
KB: I think it’s different jobs. There is a job shortage, in that we’ve retired a workforce on a large scale. So we have to replace a workforce, but it’s going to be a different kind of worker. I think there are going to be jobs that probably fit the next generation workforce better than the current generation. They understand automation and how information is used to do problem solving and to innovate. And they collaborate on a much greater scale than we’ve done historically.
I look at Industry 4.0 as the opportunity to provide an abstraction layer, much like development in software has evolved. We don’t do machine programming at the higher level languages; now we do much more abstracted development to the point where we can leverage all that to do much more creative and innovative things. There’s more information, more data, more opportunity to influence. They are going impact things more directly. It’s going to be more through the fact that they’re creating these things that are going to get realised in a production environment through automation than it is having them as production line operatives. We’re still going to have some of that, certainly, but I think that’s the evolution that’s occurring.
