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Traceability in practice – using the example of conveyor belt components


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IoT Use Case Podcast#127 - Optalio + GURTEC

Traceability as a use case is a buzzword at first – but what does it mean in practice? In podcast episode 127, Benedikt Sturm from Optalio, the German expert for SaaS/PLM solutions, and Thomas Dreyer from GURTEC, the manufacturer of conveyor components “Made in Germany”, are our guests for this topic. Together, they have developed a system that reduces complexity and keeps an eye on everything – with an AI that will amaze even the most experienced foremen.

Episode 127 at a glance (and click):

  • [14:59] Challenges, potentials and status quo – This is what the use case looks like in practice
  • [25:57] Solutions, offerings and services – A look at the technologies used

Podcast episode summary

In this episode of the IoT Use Case Podcast, Benedikt from Optalio and Thomas from GURTEC discuss their collaboration on optimizing production processes through advanced data analysis and artificial intelligence. Optalio, a German SaaS provider, specializes in PLM and AI-based production optimization and supports companies in the manufacturing industry. GURTEC, a 55-year-old German company, is part of the NEPEAN Group and manufactures conveyor belt rollers.

The episode sheds light on how GURTEC is mastering the challenges of digital transformation. This involves undergoing a transformation in which analog processes are replaced by digital solutions. This covers various areas of the company, from production to personnel management. Optalio’s Production.Suite is used for this, which uses data analytics and machine learning to improve the production process and make manufacturing processes more efficient.

Complex production challenges: Production at GURTEC is characterized by a high level of complexity due to different product types, colour changes and customer requirements. Production.Suite helps to manage this complexity and create more efficient production plans.

In this podcast episode, we learn how the family business with 50 years of tradition has experienced strong growth and how it is mastering its digitalization strategy and the worldwide deliveries of over 50 million rolls.

Podcast interview

Hello Benedikt and hello Thomas. Welcome to the IoT Use Case Podcast. I’m really happy that you’re here today. Benedikt, where are you right now?


I am in the office in Eschborn.

In Eschborn, that’s near Frankfurt, right?


Precisely exact. The Frankfurters would like to include Eschborn, but the Eschborners are glad that they don’t belong to the Frankfurters. I live in Frankfurt myself, but our office is in Eschborn.

I also lived in Frankfurt for two years, it’s really nice there by the Main and generally a beautiful area.


Yes, it’s not bad.

Thomas, where are you? I have already heard in the preliminary talks that you are in the same building?


Exactly, we are in the same building, 10 meters apart as the crow flies. Die Technologie und die verschiedenen Vorgespräche, die wir heute geführt haben, waren naheliegend.

That sounds very nice. And how are you doing at the moment? Are you going full throttle into the year already? Do you have the feeling that the year has fully started?


Yes, full throttle into the year, absolutely. We don’t close the year in December, but always at the end of June. That means we still have about 5 months ahead of us, and we really go on the offensive again. So, yes, we’re already back in full swing, absolutely. I think that applies to everyone.

I’ll have to check again, you’re now in the Optalio office on site, but otherwise you’re based in Schöppenstedt, aren’t you? That’s somewhere in Lower Saxony.


Right, so the town of Schöppenstedt and our plant there is close to Wolfenbüttel, in the town of Schöppenstedt, Wolfenbüttel, close to Braunschweig.

Cool, I just looked at it on Google Maps, that’s where i come from. I originally come from the region between Braunschweig and Hanover. I would like to make a very brief introduction to you and then talk a bit about your two companies, who you are, what you do and also a bit about what your core business is. Benedikt, can you say one or two things about yourself? You are Managing Partner and Co-Founder at Optalio. What exactly is your role?


Exactly, so my role at Optalio as co-founder is to be responsible for everything technical. I have a mathematical background, studied mathematics, then came into contact with computer science relatively early on and my role in our founding team is ultimately to be responsible for everything that concerns technology and software development, customer onboarding, data analysis, etc., to develop it further and that is exactly what I do every day.

Thomas, how are things with you? You are Managing Director of GURTEC. What are your typical tasks at your company?


Yes, a little bit about myself: I’ve been with GURTEC for four years since February 1, where I work as Managing Director. I studied electrical engineering, worked in sales for many, many years, then got the opportunity to go into operations in 2011 and since then I have been very closely involved, also as a managing director and also in management when it comes to production facilities. GURTEC GmbH employs 130 people and is a production facility for conveyor belt rollers with a good 100 production employees, i.e. 130 employees in total.

Yes, and you are a family business, aren’t you? I believe you have been around for more than 50 years and everything you produce is truly made in Germany. Perhaps that can be emphasized again.


So now, in 2024, we have actually been around for 55 years. It is a family-run company. We are part of the Australian NEPEAN Group with around 1500 employees worldwide, i.e. various production plants. And once again, we are primarily concerned with the conveyor components, production and worldwide distribution.

The NEPEAN Group itself comes from mining, construction, infrastructure, products, but also a lot of transportation, equipment with corresponding services. You fit perfectly into the portfolio and that has also brought you strong growth because you have a very strong focus on the rolls or on the conveyor components. Of course, this also fits perfectly into the portfolio in terms of growth.


Yes, absolutely. We were acquired by the NEPEAN Group at the end of 2017. This was also a milestone for the NEPEAN Group, not only to be active in the Asia-Pacific region and also in Australia, but also to actually expand further into the European regions. This also includes other acquisitions, as well as North and South America, so that the company, which originally comes from Australia, now operates like a network across the entire planet, both in sales and in production.

To make a direct connection to Optalio, how did you two get to know each other and the companies? How did you get together?


Yes, well, the first contact was ultimately via e-mail, and then we had our first meeting relatively quickly. There is actually a nice story to tell. Thomas is from the area, I think I can reveal that you live here too, that you’re a Eintracht Frankfurt fan, just like most of us here at Optalio. Thomas was on the video call with his Eintracht mug and, amusingly enough, we were just at Eintracht Tech, which is a tech department of Eintracht that is setting itself up in the area of digital stadiums etc. and wants to develop further in a future-oriented way. We sat in front of the large Eintrachtstein. I don’t know what the reason was, maybe the Euroleague title or something, or the new performance center that was built. Then we said, oh well, that’s a coincidence. That’s how we got to know each other for the first time.

Then you have found common starting points, so to speak, and started a joint project.


Exactly, absolutely. We will certainly have a word or two to say about this in a moment and tell you a little about what exactly it’s all about. But in the end it worked out very well. The challenges we face at GURTEC, especially in production, the complexity that prevails there, is actually a great case for our use case, where you feel very comfortable as a mathematician.

Now you’ve given me the perfect transition. It’s also about the use case. I think we’ll talk about that in a moment. Perhaps one small thing first, just so that people can briefly categorize you as a company. With Optalio, you are a German software-as-a-service provider, you have a very strong background in software and you also focus on PLM, i.e. product lifecycle management. You do complex data analysis, especially with a focus on process monitoring and AI-based production optimization, also in the manufacturing industry, especially in the DACH region. What kind of customers do you have and which industries do you work with?


We now have everything from low, single-digit million annual sales to large listed companies. We mainly have customers where something goes in and something else comes out. In other words, something is manufactured, something is assembled, sweat and tears are shed and then finally the end product is delivered to the customer. We have a completely broad base. For example with GURTEC manufacturer of rollers for conveyor belts, manufacturer of seals for engines. But also manufacturers of high-precision drill heads. So we are positioned very differently, but what is always really nice to see is how everything is connected again when you are at one customer who manufactures the milling heads and says we supply x, y, z, among others, and then we say oh, well, we actually spoke to them the other day.

Exciting. Perhaps for the audience: You know some of our projects on the iotusecase.com platform. A project with the company Bergi-Plast is online there. Take a look if you don’t know it yet. Today it’s all about your project. Let’s dive into what you have done. Benedikt, can you explain the use case in more detail? You mentioned complexity. It’s all about production. What use cases are we talking about here?


It’s all about optimized production planning. The challenges are capacities, material availability and the required sequence of work steps. Current and future orders are to be arranged in such a way that, for example, throughput is maximized and, above all, set-up times are minimized at GURTEC. We will come back to this later, especially with color changes. Production has to pay attention to various parameters at many stations. Our aim is to deliver a more effective sequence of production proposals. We are looking forward to the developments over the coming weeks and months.

Thomas, you produce various products. Today it’s not about labeling your rolls for sale as a service, but about your production practice, about your conveyor components.


We are a manufacturing plant with a very deep vertical range of manufacture, focusing on conveyor technology components, especially conveyor belt rollers. These are used in numerous branches of industry – from the food industry, known from airports for baggage transportation, to checkout belts in supermarkets. They are also used in mining, both above and below ground, and in tunnel construction. Conveyor belt rollers are required in various dimensions – in different colors, with different dimensions such as outer diameter, inner diameter, length and width. Our broad portfolio includes a variety of production lines, ranging from fully automated to semi-automated. There are also manual processes for customer-specific orders. All these processes reflect the diversity of our customer requirements and present us with the challenge of fulfilling all these orders on time. It is easy to imagine that there are many, many disruptive fires that pose particular challenges in production planning.

What is your vision or objective in terms of IoT and digitalization? Where do you want to go with the work or with the lines?


As I said, I have been with the company for four years and we have been in the middle of a transformation for these four years and will continue to be for the next few years. This transformation clearly means the transition in the individual departments from the analog to the digital world. What does that mean? In sales, we had a lot of paper processes that we have already digitized and automated. We have made improvements in personnel management, no longer everything on paper and in suspension files. We know this from the old world. In quality management, we also think of accounting, electronic invoicing. We have driven all of these things forward over the past four years. I’m not saying they’re all finished, but it’s an ongoing process. And yes, you may smirk, but I well remember the production manager coming to me and asking when it would be his turn to automate and digitalize. So we dedicated ourselves to this topic. At the same time, we have grown by almost 50 percent in the last four years, which poses particular challenges for my team. The solution is not always to simply hire new employees, but to optimize, find capacities, etc. That was also the motivation for us to get help from a professional who would take us by the hand.

[15:30] Challenges, potentials and status quo – This is what the use case looks like in practice

Benedikt, can you briefly explain what exactly your joint project is about? What exactly did you do there?


As already mentioned, our project concerns the planning of the production sequence. Around 300 to 400 orders have to be processed every week, comprising a variety of quantities and different types of rolls: very large rolls, very small rolls, rolls that are dyed or rolls that have a different diameter. Different work steps are carried out at different workstations. Small series are sometimes produced manually, while larger series are produced on certain machines, which is faster. The products may then have to be coated and treated externally. There are numerous interlocking work steps and requirements as well as a large volume of orders. Our project is to plan all of these, taking into account the weekly restrictions and capacities, without causing delays or losses.

Thomas, you have already mentioned the so-called disruptive fires. Could you explain what that means in your context? Perhaps give some examples and describe in more detail what specific challenges there were?


Yes, I would like to explain a little bit about that. On the one hand, we talked about the very broad portfolio, also very supra-regional. We’re not just talking about metric rolls, we’re also talking about imperial dimensions, i.e. in inches. I would like to briefly explain that we not only have a broad portfolio, but also operate beyond regional boundaries. We do not only deal with metric rollers, but also with imperial dimensions in inches. It is important to understand the variety of order sizes and types as well as the customer spectrum, which ranges from the smallest orders to medium-sized projects that are well over 50,000, 60,000 or 100,000 euros. We also serve many OEMs who have precise delivery schedules and where you have to be very reliable, with delivery windows of a few hours a day. This reliability is just as important for a small order, where perhaps three rolls are needed to prevent a system standstill. Due to our exorbitant growth, for which we are very grateful, it is no longer fair to our employees to continue to manage everything in analog form. Everyone does their best, but you reach a point where you have to think about using AI to assist. The disruptive fires – by this I mean, for example, an employee absence due to illness or a machine breakdown where a replacement machine has to be used. Or material is not available or proves to be of insufficient quality, which leads to delays. These disruptions are handled with great effort, which is particularly challenging when there is a large volume of orders. If it is possible to enter this data and faults into a system that uses algorithms to enable the best possible optimization and display, everyone gets their role in good time. In this way, problems are identified at an early stage and the customer or sales department can be informed quickly about the effects of prioritizing certain orders. This dialog helps to remove emotions from the process. Because dissatisfied customers, which we all want to avoid, lead to troubleshooting around the table, and we know that troubleshooting is not an efficient way of working.

Yes, it’s about working in a data-driven way and taking advantage of the opportunities that arise for various use cases. Data is the key to working more efficiently, not only in sales, but also in other areas such as employee sickness.

Benedikt, as a data expert from the software side, could you first explain which data is relevant? And Thomas, could you add which data is particularly important in practice?


Gladly. First of all, it is important to understand that it is mainly about data that is available in the ERP system. We are not talking about alternative data sources here. Relevant data includes order data, article items, work processes and the associated processing times, which can be scaled or generalized depending on the number of items. A setup matrix is also of interest for planning setup times, for example when changing colors in the paint shop. To be specific, if I change from red to blue in the paint shop, I may need less time because blue covers the red color more quickly than if I change from blue to red. This is relevant if you want to observe the set-up times. Capacities are of course just as important as shift systems and the availability of machines. Then there are robots that take over certain tasks so that no employee is needed. Material and stock levels are also crucial, as is the consideration of future material deliveries for order planning.

Thomas, what were your requirements for Optalio in terms of the collaboration? What were the requirements for the collaboration that you said really had to be there for the whole thing to be successful?


In view of our growing business volume, it was important to me to relieve the burden on our employees on the one hand and to have the opportunity to identify free capacity and exploit optimization potential on the other, as purely analogue management is no longer possible. Data from our ERP system is extracted and passed through appropriate filters. We have to deal with different diameters of rollers and tubes, as well as an extensive range of colors. In a fully automated process, I can’t simply change the setting; if a system is set to red, it stays red. It therefore makes sense to minimize set-up times and combine all jobs that have to be painted red or powder-coated. The challenge is to find and optimize free capacity while ensuring high availability and quality in terms of deadlines. I find this particularly exciting because we have a wide range of orders, from small to large projects with different priorities. Ultimately, you have to have everything under control. Delivery reliability is known to be a critical point, especially when the order book is very large. From my point of view, it is essential to use algorithms and possibly AI to ensure that everything reaches the customer on time, based on predefined targets and priorities.

It is also a very strong trust that you have shown towards Optalio, where you have said, okay, Optalio, let’s go for it.


Yes, that is correct. We did our research and found the concept and the references presented to us very interesting. One challenge is communicating with employees. We don’t want to offend anyone or give them the feeling that their work is being devalued because AI is now being used. The technology should support, not replace. We have great confidence in Optalio in this respect. However, it is important to understand that we are ultimately in control. We receive suggestions and then decide for ourselves whether we want to implement them or not. It is not the case that Optalio completely takes over the control of our production. Benedikt, support me here if I’m right. There are indeed many fears, especially when it comes to AI, and we are confronting these – be it among employees or the works council. We are not experts in this field, so we have to inform ourselves and get to grips with it. Optalio gave us excellent support, explained and persuaded us to overcome such unfounded fears.

[26:28] Solutions, offerings and services – A look at the technologies used

Benedikt, could you explain in more detail what you have set up and which products are used? I know you have different solutions. You have your Production.Suite, I think that’s the name of the product. You have a Monitoring.Suite. You do a lot in the field of analytics, with a focus on AI. Which products were used here?


That’s right, the Production.Suite is used here. It records all the data we talked about earlier and some more. Their quality lies in taking over the task of a manual planner. Imagine you have 100 orders to plan, and each order can have between one and 50 operations. These operations have specific parts lists and can be carried out at specific workstations. If you start planning the first mission and then continue with the second and third until you have gone through all 100, the question arises at the end as to what would have happened if you had chosen the second or third mission instead of the first. With so many possibilities, an algorithm surpasses human capacity. Even it can’t test all combinations because 100 factorial is an unimaginably large number. This is where a clever heuristic comes into play, comparable to a descent method: You are standing on a mountain and want to get down into the valley. The deeper you go, the better the solution. And sometimes you have to go back a bit to find a better way down. Our heuristics have a similar structure and skillfully test various possibilities, occasionally allowing for deterioration, in order to ultimately end up in an optimal state.

So you also carry out data onboarding, correct? Your software has connectors that can connect various data sources, such as ERP data, set-up times, matrices and various work processes, even quality and machine data. You record this via your connector, right? Your software can do that too?


Exactly, absolutely, we have ready-made interfaces, and if these can be used, onboarding works relatively quickly. In addition, the data must be prepared in the appropriate format. Otherwise, we have to go back to adapting the system so that it works. There is an ongoing exchange, as we don’t know today what orders we will have in six months’ time. New orders are added regularly, so there is a regular exchange. Here at GURTEC, this takes place twice a day. In this way, we always have a synchronized status. It is important to have a certain amount of security for the coming hours and days and at the same time to retain the flexibility to be able to react to unforeseen events, for example if a machine breaks down.

Thomas, you spoke earlier about various disruptive fires that are currently occurring in real time, for example. The other thing you mentioned is the need for a solid database in order to make informed decisions, whether in sales or with the production manager. What requirements have you entered into the AI in this regard so that the whole thing can be analyzed? Can you tell us more about this? Have you developed these use cases together and determined what information you need for sales? And what data does the production manager need? How were these requirements defined?


So the challenges are very complex. Firstly, there is the issue of delivery time and availability. But I’m also looking five or ten years ahead. We now know that we will lose between 15 and 20 percent of our long-standing employees who have grown up in the analog world. New employees who have already dealt with AI will no longer feel comfortable in this analog world. Integrating these new employees is a challenge in order to ensure a smooth transition and avoid falling into a black hole. With growth also comes investment in machinery and employees. Data maintenance is also an important point. It turns out that we should possibly have data that we don’t currently have, and that some data needs to be better maintained to provide more meaningful information. It is a very complex situation with many objectives. However, my primary focus is on the future and the transformation from analog to digital working methods. It is also about finding capacities. Where are we really not efficient enough? Where are we not as productive as we could be? Where is the money lying on the street that we really only have to bend over for? We just have our black glasses on and can’t see where these advantages, efficiencies or the best productivity can be found. Last but not least, it is also a little bit about investing in machines. If you go through the cost calculation and look at the machinery, then I can also see this reflected in Benedikt’s result. This also helps to identify which work processes are particularly complex, time-consuming and error-prone. Machines with a poor service life also require measures. That is why we are also investing in new machines. It is helpful if you also receive arguments for decisions from other areas. Decisions on multi-million euro investments are not made alone; authorities have to be brought on board. It’s fantastic to be able to deal with this.

Yes, Benedikt, when you hear that from our project, it’s all about efficiency and using different data potentials. How exactly do you go about it? Your focus is primarily on analysis. I think you even have huge databases that you use to map this complex knowledge. Can you explain how you do that? How does this analysis work?


Yes, a lot of things at the beginning, especially this exchange and getting to know the company GURTEC at this point and also understanding the challenges, especially now here the set-up time issues, which are based on different parameters at the different stations. As I said, we have the heuristics, which work well in principle, but we also always have the option of tweaking them and saying, okay, in this case GURTEC, please pay more attention to this and that point. This exchange is immensely important and that we also understand how this production process works. In the end, you always have the lowest common denominator: something goes in, something comes out, but what happens in between and what special features the production then has is always different, the better we understand it. That comes from the initial onboarding phase, first setting up the pipeline and then talking about the production processes. If we also get this information, then we can calibrate the algorithm even better, adjust it even better, which then leads to better results. Here at GURTEC it is totally exciting, you have a sequence of work steps. At each work step, there is another parameter that determines the set-up time. One time it’s the roll length, at the next workstation it’s the diameter, because I have to change the diameter on my machine afterwards, and then it’s the color. Looking at all this across several hundred orders is a challenge and totally exciting. But understanding that first and understanding this sequence also takes time, because Thomas and his employees talk about it and they clearly know what’s going on, and then technical terms are used and we say, okay, stop, please explain it again for the stupid. We were once at your plant, but we don’t know where we are in your thoughts at the moment, and we don’t know what you mean by the terms. Then it is also this exchange that is very important in order to achieve better results. Then we will be able to do our job much better, i.e. optimize and make the whole thing data-based. This is the synergy effect, so to speak. Users on the production side and our algorithms, our data model. Then we can analyze and use all the data we have accordingly.

It really is a complex topic, but broken down into the various application scenarios you have just described, it is very concrete. What I have understood is that your Production.Suite helps to first understand the disruptions, to understand different scenarios, to analyze them with your heuristics, where the analysis really runs in your software, so to speak, in order to really keep an eye on everything in the end. Regardless of whether these are somehow work orders, a product status or various capacities that are then freed up, where you simply have the opportunity to look at something like this and make data-driven decisions. I still have a lot of questions, but we’re almost at the end. If you realize now, ey, that’s exactly my topic or we have similar topics, I’ll just link the LinkedIn profiles in the show notes. So maybe have a chat about it afterwards. Benedikt, you can be asked about anything relating to data. You are represented as a partner in our network. Without going into any more detail, I would like to talk briefly about the future. Thomas, you mentioned that too. Above all, you always look ahead. So what does the future hold? What is the next step? So where do you stand today? Where are you going?


We have actually made progress with the production module as part of the transformation. We have basically completed the first fully automated hall and finished some of the preliminary work processes. However, there are still a few production halls to go. Here I have a specific topic and also a wish: we would like to have more measurable KPIs and key figures to better represent the old world with the new world. On the one hand, for conviction and, as I said, once you start optimizing, it’s a long road. We won’t be finished by August. I believe that the circle is getting bigger and bigger, especially now that we are dealing with this topic, and therefore the attack surface is also getting bigger given the size of the circle. I just see it as very exciting. We need to uncover further bottlenecks, including within the machinery. Some may say that thats not hard. We have machines, we have been around for 55 years. They are worth revising, and we need to research the extent to which there is still potential. We want to continue to grow and we want to do it smart. We are all aware of the shortage of skilled workers here and there. We have to take countermeasures. We are a training company and I am very proud of that. But despite everything, we must also pay attention to automation in order to remain absolutely competitive, within Europe and worldwide, and we must do everything we can to achieve this. I am convinced that digitalization will continue here. Robotics is also at the top of my list. We are talking about the automation of roll production. There are still areas that are semi-automatic and also some jobs where employees have to lift heavy loads. These are all things that we need to tackle and automate over the next few years.

It’s fantastic that you also have this view and will continue to drive it forward in the future. Benedikt, finally, what else is on your agenda? What will there be in the new years or the next few years? What is still to come? Maybe we can even see something at the trade fair, the question is what we can look at there.


The nice thing about Software-as-a-Service is that we have to keep courting the customer, but if the customer is satisfied, he will stay with us. If we weren’t constantly evolving, our customers might at some point ask what’s going on. That is why we are constantly developing new features, always in consultation with our customers. For example, we recently introduced employee planning to schedule employee capacities and take vacations into account. We developed this in collaboration with one or two customers. We need a few more months on the roadmap for the Production.Suite to implement some of the ideas we have received, but also to further develop our own ideas. The Monitoring.Suite is at an earlier stage than the Production.Suite and draws on machine data that is continuously recorded. You’ve already mentioned Bergi-Plast, they produce shampoo lids and some of them don’t have fully filled lids and detecting this automatically is a big challenge, first of all to collect the data, but then also to have sufficient training material to ultimately train the algorithms. We still have a lot to do. The merging of these two tools is also possible, because let’s imagine that predictive maintenance forecasts give the Production.Suite the input that there is a 90% probability that machine XYZ will be down for five hours in the next week. This allows us to take this into account as early as the production planning stage. Another important topic concerns the EU taxonomy, CO2 emissions and verification.

Yes, the new requirements from the legislator are really interesting. You could almost make a separate episode about it. There are many regulations that need to be taken into account and can be answered in a data-driven way. That is a topic in its own right. I would like to thank you for being here today. I have learned a lot from your project and also got to know your concrete vision and strategy for the coming years. It is important to understand how you and GURTEC want to move forward in the future and how this works. Perhaps we can do an update in a year’s time to see how the roles are developing and what new business models are emerging. Thank you for being here today and openly sharing your insights. I’m happy to give you the last word. Thank you so much for joining us today.


Thank you very much, also from my side. It is a pleasure to work with you and the entire Optalio team. It’s really fun to work with such a young and dynamic team. As a boomer, I don’t like looking at my passport, but this is a great experience. I would be delighted if we could get together again in a year or whenever and look at the progress. The podcast is also a great opportunity, thank you for that.


Yes, from my side too, thank you very much for giving us the opportunity to speak so openly and honestly here today and to record this great podcast. At this point, thanks to your team Madeleine and of course Thomas. An even bigger thank you at this point, almost or definitely to the trust, but also that you say, I’ll come up here with us, with Optalio, and just have a chat. We can use this as an opportunity next year to present the next results or perhaps to see if we have one or two more ideas together with GURTEC that we can then take forward. It’s really fun, especially the collaboration. Thomas, we don’t work together that much. I mainly work with your colleagues. But you have a great team, especially a capable team that faces the challenges of digitalization with open visors and says, we’re doing it. It’s fun.

Very nice. Thank you very much and have a great week. Take care. Bye.


All right, thank you, bye bye.


Thank you, bye!

Please do not hesitate to contact me if you have any questions.

Questions? Contact Madeleine Mickeleit

Ing. Madeleine Mickeleit

Host & General Manager
IoT Use Case Podcast