Don’t digitise the waste: How signal towers became IoT devices

Armin: Thank you very much for the invitation, Ruth. I'm also very happy to be here today.

Ruth: Tell us a little bit about yourself. Who are you and what is it that you do at WERMA?

Armin: Yeah. Yes. Um, actually my name is Armin and I've been working for WERMA since quite a long time. I studied industrial engineering two decades ago, I think now, so it's already quite a long time, and been working as a product manager here for WERMA over the last years.

Since roughly one and a half year now, we created a business unit for our product WeAssist. And WeAssist is a simple tool for companies to monitor their production, to monitor their logistics processes as a simple retrofit solution. The company WERMA is coming from the field of industrial signalling, meaning visual management is very important for us. So beacon, sounders, horns, so always to alarm the people, to bring the right people to the right place. And with WeAssist, we are actually bringing that to the next level and connecting these signal devices as an IoT device, uh, bringing the information of the signal light into the, uh, cloud and then also into the software of course, and visualisation for the customers.

Ruth: Interesting. When, I assume when manufacturers think about Industry 4.0, they always imagine greenfield smart factories with connected equipment everywhere, but most factories aren't like that. And what does the average production floor actually look like?

Armin: Yeah. And that is, I think, the biggest problem that companies usually have. They start from zero, usually. Yeah. Or they start from very simple processes. So if you look at, um, a normal production floor, I can also look at our own company here, medium-sized company, 400 employees working here. And we have different areas in the production.

You will see manual workplaces, a lot of manual assembly still going on in all those companies. You will see very modern areas where we have, uh, electronics manufacturing, or you will see modern CNC machines, tools, and injection moulding machines. And the first idea that people usually have is to go a hundred per cent for the digitalisation modern machines IoT interfaces, like OPC UA, MQTT.

You connect your hardware right away and basically you can go down into the machine on the sensor level, you see temperatures, you see velocities, pressures and so on. But the reality really is a different one. You will find old machinery, sometimes machinery from the sixties, old punching machines and things like this, and they don't really have an interface.

And also if you look at different machines from different manufacturers, they also come with different standards, and even if it is advertised to be very easy to connect them all in one big system, it is, or it can be really a little bit of a pain. And the manual workplaces, the manual processes, that's something that people usually don't think about, even though they are crucial for a successful, uh, process improvement and digitalisation in the factories.

Ruth: Okay. And you and your team are working on a solution called WeAssist and it's supposed to transform existing signal towers into IIoT devices. How does that work?

Armin: It's a very simple process. We have a camera here, so I show you just the signal tower. It's a, it's a traffic light, basically with the traffic light colours, you can switch it on. You can switch it off, so very simple. This traffic light usually indicates already the most important states of a machine or a workplace.

Is everything operational? Is there uptime? Is everything running or maybe a red light indicating for downtime, uh, and problems? It is a, a very important info. If I'm the production manager, I look at my shop floor and I see red and green, and I have an understanding of what's going on. But it's of course a view that changes every second, basically.

And with WeAssist, we add a very simple radio transceiver to that signal tower. It's a small radio device that, uh, monitors the states of the machine by monitoring the lights that are on top. And this information then is with that, uh, simple radio system is transferred to a central receiver and that receiver is connected to the internet, pushing the information of up to 300 machines and workplaces into the cloud, cloud-based system.

And then of course, um, making it available for visualisation and analytics on our web app, and this is the, the very simple retrofit way, the radio device that you connect to the signal towers. It's basically industrial radio 868 megahertz. So we are not connecting each and every device to the customer's WiFi, which is also sometimes a little bit difficult nowadays with cybersecurity and IT security.

Armin: That the people are taking care of a lot. So we are building up our own infrastructure with the signal tower being our edge device, basically the device that is connecting the workplace and the machine to the internet.

Ruth: I'm thinking about the advantages of this approach. Obviously budget comes to mind versus ripping out old equipment and installing smart machines. I suppose it's you. You mentioned something like, um, a low barrier entry into the world of IIoT. What other advantages are there to this approach?

Armin: Yeah, the low entry, of course, is the most important one. The retrofit. So you see that signal devices everywhere on the shop floors.

Ruth: Okay.

Armin: You just put in that small radio device and basically you are, you're ready to go.

Ruth: Mm-hmm.

Armin: The important part here, or the big advantage that, uh, that we see in the discussion with our customer is that the manual processes, so the people are also included. So basically you can imagine a manual workplace. The employee there is having a problem can just push a button, the red light goes up.

Some other person, the supervisor or some, uh, maintenance crew directly receives a push notification on a mobile phone or sees on the screen that there is actually a problem happening and you can directly react to that. All of our clients, maybe that is the starting point. Usually they are taking care of their production processes.

They want to be more efficient, they want to be leaner, as we say.

Ruth: Mm-hmm.

Armin: And being lean of course requires, first of all, a lot of transparency. Being lean is also always linked to the production philosophy of Toyota. So what we usually try to avoid are the so-called wastes of lean.

Ruth: Mm-hmm.

Armin: And, um, to remember them basically, I always use this, uh, acronym Tim Woods. Okay. And Tim Woods actually stands for the team basically stands for, uh, transport, inventory and motion. Mm-hmm. Which is, um, a lot of waste can come from there. Too much, uh, material on the wrong place. Too much motion of material, too much motion of people. And then we have woods, which basically stands for waiting.

So people are waiting for the right people to arrive, are waiting for the right material or production resources. And then we have the O, the two O's, one is over-engineering.

Ruth: Mm-hmm.

Armin: It's, uh, also a little bit of a German topic, to be honest.

Ruth: That's why I'm laughing.

Armin: Yeah, exactly. I mean, that's, that's also a thing. Uh, as a product manager, I also had to consider, uh, to keep that a little bit lower sometimes. And overproduction, yeah. To, to produce too much for the stock, for instance.

Ruth: Mm-hmm.

Armin: Um, and D of course in the end, um, is the defects. And the S stands for skills unused, which also puts the people basically in focus. Okay. And yeah, we try to bring transparency into the processes and then in the next step for the customer to reduce these wastes. And not only to reduce costs by doing so, which is of course also a topic, but to have a very stable and a high quality production process in that Toyota management, um, idea.

Basically there is always the customer in focus. So if we reduce something, we're not doing it to bring down costs at the firsthand, we are doing it to, uh, improve our product quality and uh, to deliver the right product to the right people.

Ruth: Maybe we can dive into a use case. We have a lot of things to unpack now, like, um, you mentioned lean production, you mentioned wastes that are identified in our customers. Mm-hmm. I think you have a very nice example of a logistics company where you, where we can maybe walk us through how this process then worked.

Armin: Yeah. We have a nice use case, our customer is, uh, a logistics centre that is shipping, uh, for instance, uh, washing machines, this kind of, um, machinery for household.

And of course, uh, specifically if there is Black Week or if there is close before Christmas, there's a lot of action going on in this logistics centre. So you can imagine

Ruth: Guilty.

Armin: Yeah, me too, to be honest. Yeah. And we have different loading docks there in this logistics centre and, um, to basically fill those trucks that are at the loading docks, people are, uh, storing the material, uh, right before the docks. Mm-hmm. If the truck arrives, the material is delivered into the truck, but no one, nobody really knows when the truck is full or when the truck is full. Actually, the worker there has to call for the supervisor to give the green light actually that, that the truck is ready to leave. Mm-hmm. And what we are now doing with WeAssist, we install these traffic light, the signal towers on each of those loading docks together with a simple push button box and our radio device, our IIoT device.

And as soon as the truck is ready for departure, the employee at the dock can push the button for the supervisor to arrive. The supervisor directly sees on his mobile phone dock number five, for instance, is ready for departure, can come over, sign the documents. And directly the truck is off and ready to go.

Mm-hmm. And the people, of course, they are available now for new duties and before that, basically everybody was shouting, was looking for the right people, running around. And now we are steering basically the traffic of people in this area. And also with the signal tower, not indicating only digitally, but also visually.

Mm-hmm. So there's always the light that also indicates that the truck is ready to leave, for instance.

Ruth: Okay. The communication is really clear because everybody knows the signals of a traffic light. Right. It's just unmistakenly, you just know what to do. Right?

Armin: Absolutely. And it's completely universal. That is also a topic. We try to keep it simple that way because, uh, sometimes spoken language is also, uh, difficult. You can imagine in these logistics centres, people from many different countries are working there. Maybe the German is not so, so easy to understand for them. Not everybody can speak English.

So basically we are communicating with simple signals that everybody can, can understand basically.

Ruth: And what results did they see? If you stop people from running around a logistics hall, the results should be seen really quickly, right?

Armin: Absolutely. The results will be seen. It's, it's all more in order.

Ruth: Mm-hmm.

Armin: So basically, people don't have to go too many miles, let's say, that way they can directly focus also on preparing the next shipment, for instance. So basically, if one truck now is ready for departure, the button is pushed and then the person can directly go to the next loading dock, start again with the filling and loading the next truck.

So basically everything comes to a very nice structured approach now. Not too much shouting, not too much running around. Also, the storage areas are more tidy now because actually the flow of material is more, uh, clear and more stable. Okay. Which is also, again, one of the wastes of lean to reduce that inventory at these areas.

Ruth: And it also makes it more secure for the workers as well.

Armin: For sure. For sure. You can imagine the forklift traffic and people running around. Personally, I have to be honest, if I go to these areas, I'm always a little bit afraid because there is still, I mean, luckily there's not too much happening, but the forklift traffic can really be, be crazy. And this of course, uh, helps a lot.

What we also are doing, not at this particular customer, but at other logistics centres, is to have, uh, also vocal alarms that we can trigger. It's like a, like an MP3 player, uh, you can say. So basically, for instance, if the button is pushed, the push notification is sent to the right person, and if this person does not react in time or it might not be available in this case, potentially after two minutes or so, a melody will be played.

Or, um, some, uh, voice message will be, uh, activated to also address to other people that might be in the area that might be ready for helping. It's always the approach on one side to be digital, to see everything also on the mobile for the supervisors. It's um, not only the push notification to understand where they have to go, but they can also see for how long that light has already been switched. They can see in the end if they want to run analytics on that, how often, for instance, specific, uh, calls have been done. Or you can also identify then your bottlenecks. If there are, uh, loading docks that usually cause problems or if there is some kind of, uh, let's say misproportion in the use of the loading docks, you can balance everything now with the data that you have available.

Ruth: We will take a short break, stay with us and we will be hearing from our guest very shortly. This podcast is brought to you by Avnet Silica, the engineers of evolution. Subscribe to our Avnet Silica newsletter or connect with us on LinkedIn. If you want to learn more about us, we have put information and links in this episode's show notes.

You also mentioned user acceptance in the beginning as critical. How did the logistics company convince its workers to use the system? Or was it a no-brainer?

Armin: In this case of, of course, at the beginning it's always discussions. I mean, it, it's a, it's a normal change process. Hmm. To be honest. And change comes sometimes difficult for the people if they have the feeling, if, if it would be the same for me. Uh, if you and me, we have the feeling that somebody wants to monitor us, wants to see what we are doing, wants to see if we are efficient or not, that always comes at a, with a little bit of a, a grain of salt, let's say that way. I think transparency is the key here to, um, to let the people know what you intend to do, what, what your intentions really are, and also to show them that in this specific case, for instance, the use of this tool makes their life a lot easier. So basically the, the shouting, the running, that is, uh, of course that was never convenient for the people there. And now with this simple additional approach, this new process involved, it became pretty clear for them that this is also an advantage for, for themselves.

Clear communication. Also clear communication about the intention. Why are we doing some things? Why do we want to implement, uh, a system that gives us transparency here? Um, is something that everybody, uh, can or should make use of. That's the key to it. And then mm-hmm. If the people see the benefit for themselves, of course, then it's going in the right direction.

Sometimes it even leads to a certain, let's say, gamification, that's more for production monitoring, where you can use the system as well. Um, sometimes we see that workplaces have some, uh, kind of internal battle who's the more efficient, the faster, uh, and so on. Um, but you have to give the people the, the feeling that it's not about, uh, reducing, uh, or maybe cutting the workplace in the end or something.

Ruth: Yeah. That's the first fear that always comes to mind.

Armin: Absolutely. Yeah.

Ruth: Um, going back to the, to the concept of lean production, you manage the eight types of waste, Tim Woods. Is there a waste that manufacturers typically find most surprising when they start monitoring with WeAssist?

Armin: Yeah. What they, what they find very surprising is, for instance, the waiting time. So you can imagine your machine has, uh, malfunctioning. There is downtime happening and usually the people don't really know since what time that machine is on error. Um, and now with WeAssist, okay, they can easily see the red light is now active. The machine stands still for maybe half an hour in the past, usually specifically if there is a night shift or, um, shifts on the weekend where not so many people are around, it can take sometimes hours until it's identified that there is a problem on one machine and later that is the the first impression that we usually get, that people are totally surprised how much more productivity they can gain by reacting quickly. Nobody knew how long the machine stood still beforehand, and now it's transparent and that is the the most simple approach and it's the most surprising for most of these people.

Ruth: And you also mentioned going from zero to a hundred usually doesn't work, but I suppose many clients still approach it that way. Where in your opinion would you start? What, what should they do instead?

Armin: In our opinion, they should first of all have, um, let's say an overall view on their production site. Sometimes the requests for digitalisation come from a specific area, let's say the newest, uh, production area, new investment in machinery. They want to start right away with digitalisation, but they don't keep in mind that the company consists of so many other areas that also need to be digitalised and monitored.

So therefore, I suggest, usually have a look at your complete production site, have a look at your manual processes also, and then start ideally with a system that gives you very low entry hurdles. Yeah. So that you can really start. Maybe also why not in a limited area to get a feel for if it's working or not, and then start and roll it out all across your facility.

Mm-hmm. The problem with going too deep is usually that it is on the one side, it's, it's super expensive if you, uh, want to have an IoT project or IIoT project for monitoring all of your machines in the company. This can easily take you years. Uh, it will cost you a fortune and also the project management will consume a lot of time of your internal and of course of external employees.

So that's, uh, also a problem there because everybody has already a hundred per cent job and, uh, now this project comes on top. So we try to bring that, um, hurdle quite low so that you can start with it usually by doing so. You will get the original Pareto, uh, 80-20. You have 20 per cent of the effort and you will get, uh, 80 per cent of the results.

Um, okay. You will see productivity, you will see uptime, downtime. And then if you want to go deeper, you're free to do so. Let's do that. If you have modern machines, invest in those, let's say IoT systems that can, that can give you all the insights on that. But be aware that in my opinion, at least, IoT systems are always a mix of different components. There will never be like that one IoT platform that will cover everything. And I think that's a big learning that I had myself. I remember that companies like Siemens and other big players, they wanted to bring their IoT solution to the market, a big platform that is the only one to be used.

Uh, but that's not happening actually. And we need to have small systems that interact together. So basically interfaces, APIs, that's the key.

Ruth: Okay, terrific. Beyond manufacturing mm-hmm. And logistics, are there any other industries that would benefit from WeAssist?

Armin: Yeah, basically, of course the manufacturing and the logistics is the most important part, uh, where we are going into what you can also imagine because it's, it's simple, uh, traffic lights, you can use it, uh, also for facility management, you can monitor, for instance, doors that are open or not open, you can see entrance, uh, gates, uh, and doors that you're monitoring. So all those, uh, topics are easily to be covered.

But frankly speaking, manufacturing, edit with machines or manual and the logistics processes, those are basically the most important fields that, that we are working in.

Ruth: Mm-hmm. Before we wrap up this episode, is there anything I haven't asked you that you wish I had asked you?

Armin: I think, uh, you asked a lot of very interesting questions, Ruth, maybe not a question, but I was just, I would just like to emphasise that involving the people and keeping in mind that mm-hmm there is so much manual work going on and so many people working in companies. If you talk about digitalisation, don't forget the people. Don't forget to involve them. And if you want to eliminate your wastes in terms of lean, be aware that basically the best IoT solution is not digitalising the waste because you can, you can collect so much information, so much data. Mm-hmm. But in the end, you need to get something out of it and you should be, uh, the one that is able, uh, with the results to act and then to, uh, improve.

Ruth: Fantastic. And my final question as always, if you had to put together a soundtrack for this episode, what song would you put on it?

Armin: I like that question actually. I thought about that. Um, and I think, um, I will go for the Queens of the Stone Age.

Ruth: Okay.

Armin: No One Knows.

Ruth: Oh,

Armin: and this is a nice song. I like it. Uh, I'm more for the, for, for a little bit the, the harder sounds. Oh, good. Um, and, uh, the Queens of the Stone Age band that I, that I, uh, visited, uh, a few times at concerts and No One Knows, basically, that's usually the answer to, to the question, uh, do you know what's happening in your, uh, production site at the moment? Um, and this of course, we want to change with our IoT solutions.

Ruth: Fantastic. Thank you very much. Thank you so much, Armin, for being on the show and sharing all your practical insights. It was really refreshing to hear about IoT implementation that actually works and keeps the humans in the centre of things. Thank you so much for being here.

Armin: Thank you very much, Ruth, for the invitation. It was a pleasure talking to you.

Ruth: Thank you for listening to We Talk IoT, stay curious and keep innovating. This was Avnet Silica's We Talk IoT. If you enjoyed this episode, please subscribe and leave a rating. Talk to you soon.