In the 105. episode of the IoT Use Case Podcast, the first after the summer break, Ing. Madeleine Mickeleitwelcomesthree exciting guests from the industry: Richard Stegmann, Manager Digital Solutions at ruhlamat, a company in the special machine construction sector; Stefan Huber, Managing Director of machine builder RAMPF Production Systems, and Thomas Dreyer, Director Research & Development at Kontron AIS, a software company.
Podcast episode summary
The episode offers a deep dive into how these three companies are uniquely collaborating in the field of IoT. Our guests share their collective visions of how they use IoT to create value for their customers and discuss the impact of the EU Data Act on their businesses.
Some highlights of the episode:
- An in-depth discussion on business models, organization and how IoT impacts the value chain
- Insights into specific use cases and how they add value for customers
- Considerations for customer centricity and IT solutions that fit the described use cases
- Insights into EquipmentCloud®, a cloud-based service platform with integrated knowledge database
- A discussion about their vision and meaning of their collaboration
- An analysis of the EU Data Act and its implications
Finally, the guests share their thoughts on the future of IoT, monetization and business models for OEMs and what developments they expect to see in the coming years.
This episode offers valuable insights for anyone working at or interested in the IoT, mechanical engineering and software development.
Welcome back after the summer break. I am very happy to be back and to discuss with you exciting use cases and projects on the market from practice.
Today I start with a very special episode, because I never had this constellation before. I’m discussing with Richard Stegmann, Manager Digital Solutions at ruhlamat, the industry is special machinery. With Stefan Huber, Managing Director at Rampf Production Systems, also from mechanical engineering, and Thomas Dreyer, Director Research & Development at Kontron AIS, the industry is IT services and IT consulting,
Find out about their truly unique collaboration in IoT, what exactly makes them so unique, and what use cases they serve in today’s episode.
I’m particularly excited about their monetization approaches and how they plan to leverage shared value for their customers.
Hello Richard, hello Stefan and hello Thomas.
I am very happy that you joined us today. Welcome to the IoT Use Case Podcast. How are you guys doing? What’s new with you? Thomas, how are you doing? Where are you at the moment?
I’m sitting in the office here in Dresden right now. The weather today is not quite as nice as one could wish for. It’s raining a bit, but we’re still in a good mood and we programmers like it when the sun doesn’t shine on the screen.
Yes, greetings to Dresden. You have such a wonderful user conference with your customers once a year. I was there and so were my guests from today. Beautiful city and you are based there. So, what more reasons can there be to stop by.
Richard, how are you? Where are you at the moment? Where are you right now?
I’m actually sitting in our headquarters near Gerstungen, in the heart of Thuringia, right now. We also have bad weather, like Thomas, whereas I think that is quite good for nature. Basically, you reach out to me as we drive digital transformation at ruhlamat for us and our customers. We are always and constantly working on this and thinking about what we can offer and how, so that our customers can benefit from it.
Very nice. Stefan, are you working from home or are you in your office?
I am actually in the office on the beautiful edge of the Black Forest. I think it’s the same weather nationwide, summer has just taken a break here too.
I am also very pleased that you are with us in the round today, because today we have a special constellation. Richard, you just started to tell a little bit about you and you guys. Can you just kind of introduce how you guys are actually connected?
Yes with pleasure. I’m glad that it came about this way and that we’re also talking in the round today because it is indeed something special. We, as ruhlamat, are basically special machine builders first. That means, of course, we have customers who have special requirements. We build many assembly lines. Typically, a very big business of ours is also personalization equipment for chip and passport. On the one hand, of course, we always have the customer’s requirements and specifications, which are very different and in some cases also very special, as I think is known and common in special machine construction everywhere.
On the other hand, we have partners and suppliers, such as Rampf. You have already mentioned it, we came together at the User Conference and learned there, at least I did, for the first time that we actually also use dosing systems from Rampf. That’s kind of the other end of the spectrum, this partnership-based collaboration with suppliers. At the end of the day, this raises the question: how can we work together, both with our customers and with our suppliers? How can we exchange data in a meaningful way?
That’s how we ended up with EquipmentCloud® on our machines at the end of the day, which we ran through the PoC with Kontron. We have thought about very specific things that are very important to us and that we attach great importance to. I believe Thomas also has something to say about that. That’s actually how we found Kontron, and that’s how this triumvirate came about.
Very nice. I would also ask a bit about the EquipmentCloud® in a moment. You were just talking about passports?
Right. Passport personalization or smart cards for official identification documents with appropriate security features.
Not the normal chip card that everyone carries as an employee ID, but actual official identification documents.
Stefan, do you know what kind of machine that is at ruhlamat?
That was a relatively simple casting system that we supplied there. I think even right into this passport area.
This means, so to speak, that we now have the constellation here, ruhlamat as, you could say, a customer who has, purchased a Rampf machine, in this case the casting system, and Kontron AIS as the flagship above it as a partner who then also helps with the implementation and realization in the area of IoT, could you put it that way?
Exactly, that’s how you can sum it up.
Let’s talk about your vision, Thomas. You’ve been guests on the podcast before with Kontron AIS, but for those who don’t know you yet. What is your vision here, of Kontron AIS, moving towards IoT digitization and how does this collaboration fit into your vision? Can you tell us more about that?
Yeah, sure, I can do that. Kontron AIS has been on the market for many years. We have been active since 1990. Especially in the field of mechanical engineering we have good cooperation with many of our customers, have realized machine control systems and also the
connection to the corresponding factory systems. We believe that we know and understand the mechanical engineers quite well, but we have also noticed that there are things that can be done better. Particularly when it comes to knowing what the machine actually does for the end customer and what they are confronted with, so to speak, and what problems may also occur, that is still relatively little known by the machine manufacturer. I have also noticed that the cooperation between the machine builder and the end customer is still more of a supplier-customer relationship and not always a partnership. That was the initial situation where we said that we could actually do something, and that we could also provide support on the tool side. We had a vision of enabling machine builders, giving them a tool with which they can also work in partnership with their end customers, so to speak, and obtain the data they need to optimize machines, but also to generate additional services that ultimately help the end customer. That was the beginning of EquipmentCloud®, where we started. And today we have a system that allows us to do all that. There are two customers here on the podcast who also use the system and they can certainly talk about their experiences.
Yes, very nice. You had now also said, mechanical engineering is very much also going in the direction of additional services, to some extent
to work in partnership with customers. Stefan, can you tell us a little bit from the Rampf side what’s happening on the market here right now? So how do customer requirements change. Can you address the customer needs that are coming up?
Of course, customer requirements are changing completely at the moment.
So you move away from customers servicing and maintaining their own equipment. A customer operates the plant, but doesn’t really want to have anything more to do with the whole shebang.
That’s where the demands on us come from. Now it’s simply a case of wanting an all-round carefree package. You know it from the car, maintenance and wear package. This is exactly what customers expect from us. They want a plant that simply works, on which they can produce. At the end of the day, this requires us as equipment manufacturers to have more information about the equipment.
We also have to be able to say that the plant needs maintenance, but the plant now also needs spare parts and the plant now also has to be down at some point so that we can carry out this maintenance.
But that is what the customer or the market itself expects from us afterwards, that we ultimately offer them this service,
so that they can display the full productivity on their plant.
Richard, you are virtually a customer of Rampf. You have your own facilities where you now have a new service model. Now you also have your production, where the Rampf plant is located. How do you guys see it? What is your specialty in special mechanical engineering and
that you have in the field and how do you deal with it?
Basically, we use solutions from partners, of course, in special cases such as the dosing unit from Stefan. We use those in our plants where the most suitable component arrives at the end of the day. We specialize in production mechanisms, in the actual assembly of products, for example. This means that we think a lot about what a plant like this has to look like, how big it is, what cycle times can be realized, how can it be improved, how can it be optimized. But what we are not, of course, because we tend to focus more on this overall product assembly process, is an expert for a single dosing system in that sense or for a single component. And there, of course, is our interest again.
Our interest is to provide our customer who receives an entire plant from us with just such maintenance information. To say: hey, let’s schedule some maintenance, because on the equipment, based on wear behavior, from data analysis, this and that behavior is showing up. In the end, our goal is actually to integrate this expert knowledge from our components, partners, suppliers into the plant. That’s where this collaborative building block comes from and this idea of combining this knowledge and making it available to the customer in turn. That ends up creating this lever of collaborative working and allows everyone to benefit in the end.
At the end of the day, our customer should benefit from the fact that, as Stefan has already said, they have higher productivity, less unplanned downtime. That’s what we want to enable them to do. And that’s why it’s incredibly important for us, if we can get that kind of information, that we just integrate it into our system. The point is that this is all based on a bilateral exchange of data, and data is essential to that. That is one of the points where I still see difficulties. Customers who use our equipment on our side – justifiably and understandably, of course, and I would like to emphasize this quite clearly – naturally use the equipment to manufacture products. Ergo, of course, they are not interested in having their trade secrets, their recipes, their workloads, etc. completely transparent. And of course we understand that. But the question is simply how can we achieve a collaborative exchange of data, where we can benefit on the one hand and say: okay, based on the analyses, we can simply intercept certain issues beforehand and support them so that failures or increased wear and tear or things like that do not occur.
On the other hand, we are not interested in extrapolating how the customer’s production is going. I think this misunderstanding needs to be cleared up a bit. And I think you just really have to go in there with full transparency. We don’t want to pull any data and give the customer the feeling that we are the big data octopus and we are doing the wildest analyses. Rather, we want to optimize our plant and, at the end of the day, offer them added value. This chain must be shown quite transparently at the end of the day.
Right. Yes, important point. I would also go into this issue of bilateral data exchange a little bit more, how that works exactly, in a moment. Maybe a question to kind of put that out there again. My understanding is that we now have two cases. So you have your own production facility, where this Rampf plant is located, and you have your general plant from ruhlamat, which you now also provide digitally. Is it possible to separate these two cases?
Or is it that you form an assembly line together,
which you in turn sell to your customer?
Yes, we are actually integrating Stefan’s solution into our system. We do not now have our own plant on which this runs on the production side, but we integrate the solution, the technical solution that Rampf offers, into our plant, which we in turn sell to the customer.
Okay, that’s a special machine, I think, or a certain line that you set up there for the customers.
Yes, that’s right.
Well, with such a passport probably does not make itself in a process step. It’s not that easy to produce, is it?
Not really, nope. There’s a bit more to it than that.
So let’s take a closer look at the individual use cases and the added value for customers. Richard, you just said it now. In the end, it’s all about operating this plant even better and adding value for the customer. Can you tell us more about this plant and about your customer cases? Can you talk a little bit about those challenges that come up with a client there?
This service perspective is simply incredibly important. After the successful commissioning of the plant at the customer’s site, productivity should simply be ensured. At this point, you have enormous leverage via the service, which decides whether the whole thing will be very successful or whether this is more of a difficult issue for the customer. At the end of the day, that’s just how we got started, where we said we’d like to use this machine as a communication channel. Simply because we then have the opportunity to use these classic cases, which everyone knows: the customer sends a photo of the system, it arrives in the service department by e-mail, and then the research begins. What is this plant, where is it located? All these classic questions come up, and of course they cause effort on our side, but they also cause effort or downtime on the customer side in the worst case. Of course, this is something that we can accelerate very decisively simply via the EquipmentCloud®, i.e. via the machine hub with us. The topics can be tackled a much more focused way, the feedback is much faster, be it information or a spare part, it can be presented faster and more transparently. That is also a bit of the use case that we have here in the first step from the service perspective. That is perhaps the first step.
The aim is to reduce the amount of documentation required. And you can break that down quite clearly to an hourly rate and also times that you otherwise need for research. There’s also a very clear business aspect behind it. Stefan, can you tell us a little bit more about this? Do you know of any cases like this from your clients as well, or would you expand on this with other cases you see with clients? What’s it like for you?
Yes, well, at the end of the day, it started out the same way for us. So we have also been looking for a customer portal where we can provide exactly this topic of documentation, installations, maintenance plans, etc. to the customer. And there we have always had the challenge from our customer. They need to know more about his plant. They want to know more. As Richard also said, that’s just the requirement that comes from the market.
Very good. Is there anything special about the collaboration with ruhlamat that you see? Where you say: actually, together we can leverage many more cases at the customer. What advantages do you see here to do this together?
Well, at the end of the day, we can only both learn from this. So bottom line, if we make our plant transparent and ruhlamat see their plant or our plant in their portal as well, then of course we learn with us from it. We recently had a case where you could actually recognize pump wear in advance. Unfortunately, we did not react to it at that moment because we were not yet so familiar with it and then we could have avoided significantly more downtime. This is what ruhlamat can also take from us as information at this point. If we are there earlier with the early warning system, ruhlamat can of course also approach the customer much earlier and tell them that something needs to be done.
Yes, this is really a beautiful example. Richard, you said at the beginning that you actively rely on solutions from partners. Do you also see pump manufacturers or component manufacturers that you could integrate into this ecosystem in order to collect even more data in the future?
Yes, in principle, that is of course our concern to some extent. Now, in our mind, it’s not about collecting more data at all. So now I don’t want us to put tons of data from a dosing system or a pump or whatever as a component in our database just so we have the data, but I’m really more concerned with coming up with a clever format. We are currently in contact with Stefan and also with our colleagues from Kontron in order to think about the project further together. That’s where we’re concerned with how can we share the data in such a way that, for example, Rampf gets the information they need to train their algorithm in turn. Or I just want to get the feedback back from the algorithm. The load spectrum of the equipment looked like this and this, determine the remaining life of the component, whatever.
That’s the information I’m interested in providing to our customer in turn. I don’t want to become the expert of the component, but I want to draw on the expert knowledge. And that’s why this data exchange and the form is also correspondingly important, how we can trade this with our customers and how we can reason. Once we have this data, we can run such algorithms on it. That is always the bottom line: the data alone is of no use to me, but at the end of the day I have to extract information that is of value to the customer and that can add value. That’s exactly the point here. We are trying to work with our partners on this, because our systems are typically assembly lines, and some of them fill entire halls. So these are just huge plants. We won’t manage to be experts in everything, from the drive and dosing unit to any robot or whatever else, to determine when a component fails. Instead, we simply need to be able to rely on this network. Instead, we simply need to be able to draw on this network.
Yes, very nice. For me, the key word in this context would be “business model” once again. Have you already developed initial approaches as to how you can set the whole thing up as a business model? You just brought this up, how can we share the data? For example, you are then simply interested in the evaluation, how is a load collective for a plant? Have you already thought about what such a business model could potentially look like?
Well, of course we worry about that. However, I think it is still a bit too early. Today we are discussing how we can implement it technically and what offers we can make. And as long as we can’t judge that one-to-one, it’s just incredibly difficult to monetize the whole thing. At least that is my personal opinion. And I believe that this whole issue, as we are now experiencing with the Equipment Hub, for example, that will simply be a basic requirement for a plant, because the customer simply expects to get this additional service. Nevertheless, there are certainly components in there that mean a lot of effort on our side as well, and at the end of the day they can’t all go for free.
Having a direct monetization option now always depends very much on the customer’s actual use case. As of today, if you look at this whole digital product range, that’s something that’s an incremental improvement component of the plant. That’s where we are today. And that means that, as of today, it is always linked to a plant. We’ll see to some extent in the first step, but what that will look like in the future is something I really don’t have the imagination for, and I have to be honest and say that we’re also lacking a bit of feedback from customers in the market to say, is that an option for you or can you not even imagine it? And that’s exactly this customer-centricity, where we want to go at the end of the day.
Yes, exactly. Stefan, how do you see it? So in the end, that’s almost an entire value chain that’s changing here. You have an established service, which also works very well, where you look after the customer closely. How does the whole thing change now with such an integration of, IoT function or additionally a digital service?
What impact does that have on the value chain for you?
I can only underline Richard’s statement at this point. Yes, we are also currently still brainstorming how to monetize the whole thing. At the moment monetization is a topic, we offer it to our customer, that they get this system actively into their machine. Of course, we already earn a little money with it. That also gives us a bit of backing, because at the end of the day it costs us money to keep the project going. But it’s not yet, and as I said, that can only be confirmed in such a way that we can already generate an absolute new business case from it right now. Looking forward, we ourselves naturally hope to be able to expand our service area significantly. By simply having data earlier, we can plan better. We can also generate a lot of potential savings internally by simply saying we can plan our service routes better. Because we can just say that we can do this plant, that plant, and that plant, one after the other. Because there are actually some service activities to do now in the next two to four weeks. I think that all in all there is a good use case afterwards, where you can also get a decent monetization out of it. But so it’s like we said before, it’s just too early to have a really, really great use case out of it there now that we can monetize.
Yes, I think at this point, if someone is now listening, manufacturing company and is open to an exchange, I would find it totally exciting to do a follow-up to discuss exactly that. After all, there are already some manufacturing companies on the market that are also developing solutions themselves. Of course, the big companies go some way and build their own data hubs, where you integrate a wide variety of data and, of course, data from OEMs and manufacturers is used there somewhere. But there is also the other case where medium-sized companies do not yet have a solution, so to speak, but are perhaps thinking about it for the first time, where you can approach this partnership and develop these use cases together, not only with the large companies, but also perhaps with medium-sized customers.
But of course it’s also interesting to see how that flows together with you at the end, where there’s also a monetization strategy behind it. How do you see the issue? Did you already have contact with customers? Have you already received the feedback?
I can calmly say there are quite a few large companies that have their own platforms there. Here, too, we as machine manufacturers always come to the point, they would like to have the data from us and want to have the data provided, but they want it on their platform. Then we have nothing of it again for the time being and then the cycle is actually already cut off again. In some places, there is still a lack of standardization in the entire market so that we can fall back on a common basis. I mean, you titled it so nicely as a data hub. Yes, it was going to be at some point. But, as I said, I don’t think the standards are quite there yet.
Richard, Thomas, what’s your take on this?
I agree with what Stefan said, perhaps with one additional point. We have customers or large customers who have their own solution. It is not a problem in principle. Thomas also mentioned, they originally come from the whole automation industry as well. We also provide plant data for an MES system, for example. We’ll continue to do that, of course, but can we enrich the data? And at the end of the day, of course, a large customer wants to have their plant data available in the ERP. The problem is exactly what Stefan alluded to. We can’t get at the data, and that makes it extremely difficult for us.
Machine learning, for example, if we want to train algorithms, simply has the crux that you need a relatively large amount of data from a wide variety of plants, preferably distributed worldwide. And if we’re cut off and we don’t have access to the data, then we don’t have a chance to develop that service or develop that optimization. And this means that monetization is also a bit invalid, because I can only monetize if I can really prove that it has an effect. Nobody gives me money for having a good idea and we don’t know for sure if it will work. That’s completely understandable, and it’s not meant to sound like an accusation, but you can see that this mindset of collaborative work is expanding and seeping in, but it’s just going to take a little while before we actually get there.
Yes, perfectly. From the discussions we have had in our network, I have the feeling that some manufacturing companies are taking the path of being open and providing data in order to promote pilot projects, because I believe, Richard, as you said at the beginning, that as a manufacturing company, you cannot be the expert for every pump, for every dosing system, for every assembly line. So of course I know them all, but now really in detail these insights, that’s the asset that you bring as a mechanical engineer, so to speak, and really in a collaborative approach to develop that together. I think that’s the path that’s opening up right now, and of course digital solutions like this give us the opportunity to work well together on this basis. Do you see it the same way?
Yes, I can actually only underline that as well. We are also active in the area of machine integration and connect the machines to MES systems, so to speak. We have already seen that there is a knowledge gap between the manufacturers and the machine builders. Machine builders don’t like to reveal all the data they have on the plant, so to speak. The machine builder, on the other hand, does not receive all the data that they deliver to the factory. So there’s a perceived gap in between. We just wanted to try to give the machine builder at least a solution so that they can get hold of their data themselves. And to be able to use this to drive forward topics such as AI or predictive maintenance or similar topics. And that can only be done if the operator of the plant knows what the data is, what it looks like. For this, they themselves also need a view into this system. And this is also made possible with the system. So they can observe a little bit themselves, what’s going out there in terms of data and is that critical in any way or is that okay?
Yes, I would also like to delve into the operation of such a solution because with the EquipmentCloud®, you enable roles and permissions to open up these data repositories exactly as needed. The market is new, the infrastructure is being built. What comes first: connectivity or use case? Manufacturing companies are currently doing a lot of setup work to collect these internal solutions or projects that they have set up in the first place and to create structures there. I could also imagine that first this setup work is done to then open up in partnership. I would imagine it will take a few more years before such collaborative approaches really work at the monetization and business model level. Or how do you see it?
Yes, I see that to some extent similarly. I believe that this dynamic way of working, which these digital topics bring with them, must be internalized to a certain extent. And that has to be on the machine builder side as well as on the component supplier or partner side as well as on the manufacturing commercial factory side. At the end of the day, it will be our job to then create added value and actually implement it. That’s also where we clearly see the focus for digital solutions. After all, we don’t do this as an end in itself; we do it because we want to offer added value. At the end of the day, we always revolve around the topic of data. There are data space concepts and the EU Data Act, and so on and so forth, all of which are aimed precisely at saying how we can ensure a fair, secure exchange of data and create added value for all partners, because only then will it work. But this collaborative mindset is slowly starting to grow. You can just tell that companies are opening up. That is simply the basic prerequisite for this entire digital transformation to succeed. That’s why, in the end, it’s also so important to talk about it and even if you might not have your own infrastructure ready yet, to reach out and talk to people who might already be a step or two ahead, just to pick up some best practices. Because what we can’t afford, in my view, is for everyone to make the mistakes again themselves. That’s just a bit of the point. You simply have to open yourself up a bit, perhaps even going into the exchange at a stage where you are not yet ready. That’s what I mean by this cooperative partnership. It’s simply a development process, and I think that applies just as much to technology as it does to the business model. So you’re not going to throw that on the market and say, there it is, <<take it or leave it>>. It is simply a development process that will be driven forward together with customers and partners.
Yes, definitely. This cultural change is one of the most important things. How do I get this organized and set up? Perhaps there again a hint. I’m doing a special episode soon, so after this episode, on culture change, also organizations, change management. So feel free to subscribe to my podcast at this point, if you’d like, and then give it a listen. However, I would now like to come back to the subject of the EU Data Act.
Yes, so the topic of law and data always plays a role for us, of course. In addition to the purely technical presentation and introduction of the product, we also have a whole series of discussions with almost all of our customers that are more concerned with legal issues. Of course, we also got a bit of reinforcement in the network for this, because we are not necessarily lawyers now, but rather software developers, who can advise us or also advise the customer there. Interesting topics also emerged, such as the General Data Protection Regulation, which we are all familiar with, and which regulates data that has a personal reference, so to speak. Everything else is just completely unregulated. This has advantages and disadvantages. The advantage is that it can be solved by contract. The disadvantage is that you also have to solve it contractually. And that’s perhaps easier if there is a regularium for it, where you can move along certain lines, so to speak, and don’t have to draw up extra contracts for it. And in that respect, we’ll have to see exactly what that looks like when it arrives. I think it will help us in many places and it will also, as Stefan says, give us work again in other places or trouble to have to fulfill that. But basically I see it rather positively.
Very good. I will definitely create a special episode on the topic as well, and at this point, a warm invitation as well. On September 14, we will have our IoT Use Case User Festival and there will also be a booth on the EU Data Act. We’re doing the whole thing online and there will be attorneys there to answer questions. Kontron is of course also represented. But we can go into that in detail, because it’s a topic that moves many people. Richard, you made a suggestion earlier on the subject of bilateral data exchange, which must be possible in order to make this solution possible for partners. Thomas, once again the question to you. You have various solutions, above all the EquipmentCloud®, which represents the portal for mechanical engineering, so to speak, in order to cover just such use cases and also to be able to implement them. How do you ensure that this data security is really guaranteed and how can you enable these different roles and rights in your tool so that something like partnership-based collaboration is also possible in the future? How do you deal with it?
With the EquipmentCloud®, we’ve initially implemented a rights system for the mechanical engineer themselves, with groups and permissions, just as you would expect. Even the first customers want to share this with their end customers, so that they also have insight, but not into everything, but into certain data. For this purpose, we have devised a concept that allows mechanical engineers to integrate their end customers into the system, providing them with their own space, so to speak, where they can manage users, distribute roles, and more. This is now provided with minimal effort for the mechanical engineer, where they can practically delegate administrative tasks directly to their end customers. The framework of what is possible there is defined by the system owner himself. This then extends down to the individual data records, if you will. Individual process values, individual data documents, or entries in open point lists can also be marked with visibility flags so that they are only visible internally to the machine manufacturer or only visible to the machine operator. So you can practically exchange data that you want to exchange. But you can also mark data that you don’t necessarily want to share, that are rather confidential.
That is, do you guys use something like this to do this email documentation, which now includes sharing images with the customer, or do you use it for other use cases?
So we’re actually much further along in that respect. We actually use it with every customer now. This means that at the start of each project, the customer receives a letter from us inviting them to join us in our, we call it the Rampf Project Cockpit, which is ultimately the EquipmentCloud® behind it, and to work on the entire project there with us. That is, we are doing exactly what the Richard just said. Open points lists, we no longer share them with the customer via excel and send back and forth that everyone has a different state. No, we work here directly completely on one system. We have also rolled out the system completely across the company, including our sites in the USA and Korea. There, too, the exchange with colleagues takes place directly via the portal. It makes life itself much easier and, above all, much more transparent. This is much more acceptable to customers in large places than sending their own Excel forms back and forth.
Yes, and could you now also imagine merging such approaches? So if you now have a common customer, for example, you could also consider using the Rampf Project Cockpit, I think, so that you give quasi access and then perhaps also integrate data from the entire line, although ruhlamat would probably then have to go into the lead. But can you imagine merging such data in the portal?
Yes, I think these are the ideas that we have discussed, also with our colleagues from Kontron. That is precisely the journey we are embarking on. I don’t think any of us has the solution right off the bat right now. But as Stefan said so well earlier, we will learn together how this can work, what is actually good, what is perhaps not so good. In principle, there is nothing at all to be said against it. Why shouldn’t our partners also have access to the data if it is relevant to them at the end of the day? So in terms of just an OPL for example in a project. Yes, so why not?
Yes, really nice. So I think you are also one of the first movers on the market, if I may say so, who are going down this path at all and are now also thinking in this direction as partners. These are all such knowledge curves that will give you a tremendous advantage, over the next few years, just in these digital solutions that are coming now. I think if we talk again in a year, I’ll be curious. Maybe I can get you to do another episode. Then it would be really exciting to report on our collaborative work, without exerting any pressure here.
On the one hand, we have now talked about specific cases. You have said how you apply it. You’ve said how you’re going to build the added value for customers. We have now also gone into the EquipmentCloud® to a certain extent to ensure that precisely these roles and rights, as well as data security, are guaranteed so that something like this can be rolled out and expanded in the future. Maybe once again to everyone, the question is, where do you see the future now? So what kind of issues do you say are definitely coming now, that are going to affect us a lot over the next few years. Thomas, what do you see coming in the direction of the future with IoT, also in the direction of monetization of business models, especially for mechanical engineering?
Yes, so I personally feel that the whole subject of data processing is becoming more interesting. At the moment, we are now in a state that we collect a lot of data and evaluate it rather manually through some graphics that we also offer and various possibilities. But I think that’s also going to move more and more toward automated processing. Whether that necessarily has to be AI or statistical models is another matter, but I think that will be the next thing our customers need there to be able to react quickly. So that no human has to look at it, but the system itself practically recognizes whether everything is still in the green zone or if the plant is already in a state that requires a bit of attention. I think those will be the next steps. The basis is to have data first, so that you can build something like this at all.
Stefan, how do you see it? Would you agree or do you have any additions?
I agree with him, but it will probably go a step further. So I actually see the next steps already rather in the self-learning machines. In other words, in some places they really can optimize themselves to a certain extent on the basis of the algorithms or perhaps also depending on what you actually have in use. There are the first approaches and I think they are already very, very promising. And for me, that’s actually one of the next steps that’s going to come.
Okay. Richard, what’s your take on this? So where do you see the future? Would you agree or do you have any additions?
I would agree. They are both valid points that will keep us busy. In the end, analysis is just the next step in generating information from the data. Then what Stefan says is already the next step to say, what do I do with the info then? Then I can also throw them right back into the loop. I would actually aim more in the direction of cultural topics, because my two colleagues have already talked a lot about the technical stuff now. I would formulate this more as a wish. What really gets us moving forward is simply this open visor in the exchange and simply saying quite clearly, yes, that’s a cool idea, but here and there we see really critical points or also simply saying quite openly, hey, it’s not a good idea at all to do it that way. At the end of the day, we benefit from this feedback to develop the solution to where it helps our customers, helps Rampf’s customers, maybe helps Kontron’s customers. And we definitely need this mindset, this culture, which, I think, And we definitely need this in order to implement the technical things that our colleagues have touched on in the end.
Yes, that is a very important statement here also again at the end. Thank you very much for this. And yes, I think you are also open for the exchange. So if someone now also finds the topic exciting. I would just link your LinkedIn profiles in the show notes as well. You could also go one-on-one. Maybe even a customer will listen. And you are already exchanging information with your customers, but you need to expand this even further and drive it forward in the future in a way that is valuable for everyone. Yes, I think that’s the goal here.
Thank you for being open about your collaboration. This is exactly the path that I think many are now taking or want to take. Therefore, thank you very much for your statements. Thank you for joining us today and for your time. Maybe we’ll hear from you again in a year. Otherwise, we remain in exchange through our network. With that, I would turn the final word over to you. Maybe Thomas to you again. From my side, first of all, thank you very much for being with us today.
Thank you also that we had the chance to present ourselves here and to talk together. I’m excited to see what the future brings in terms of all the legalities that are in the works. And I also firmly believe, as Richard says, that this collaboration component will become stronger and stronger and that this will actually be the success that we will achieve in the end, working together, customer and supplier, on the problem.
I can only agree with Thomas on this. I also extend my heartfelt thanks for being able to participate in the session. And yes, for me, as I said, the whole topic around digitalization, is going to be a huge topic for all of us. That will also be a very, very big challenge. Especially for us mechanical engineers, we are more on the ancient side there. And from that, I think it’s really going to be a big challenge for the whole market. But I think that we can also do that in the collaborations, as Thomas and Richard also said, together we’ll get this thing done and it can become something really great.
Yes, I definitely agree with the previous speakers. It was a lot of fun to be there. I’ll be happy to do another round with Stefan and Thomas in a year’s time. Thank you very much for this. In principle, Stefan has already touched on this a bit: We must not forget that this is a change process. And this change process simply requires that we take people with us and that we manage it together and drive it in the right direction. It takes a lot of people to come up with clever solutions, but also, let’s say, open ears and eyes, so that in the end we can implement it and get added value for everyone.
That was a nice closing statement and thank you very much for being there and have a nice rest of the week. Take care, ciao!