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ContiTech’s solution strategy for 80 plants with central department at its heart

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IoT Use Case Podcast Folge 110 - ICONICS + ContiTech

In the 110th episode of the IoT Use Case Podcast, we dive deep into the world of MDA/PDA solutions and learn how two industry leaders are joining forces to drive innovation.

Episode 110 at a glance (and click):

  • [13:45] Challenges, potentials and status quo – This is what the use case looks like in practice
  • [24:55] Solutions, offerings and services – A look at the technologies used

Podcast episode summary

Sebastian Creischer from ICONICS and Maren Beckmann from ContiTech share exciting insights into their collaboration in this podcast episode. When ContiTech was looking for an advanced MDA/PDA solution, they came across ICONICS, a company known for its global presence and universal software solution – from commercial to critical infrastructure.

A focus of this episode is on data collection and analysis. Local buffering and compression of data minimizes network utilization. Data analysis, supported by statistics and special formulas, makes it possible to calculate important key figures such as OEE or CO2 per manufactured part in real time. Maren emphasizes the crucial role of key users, who not only analyze data, but also recognize complex relationships and identify problems.

Sebastian highlights ICONICS’ capabilities in real-time analytics and universal connectivity, while Maren looks at practical application and implementation from ContiTech’s perspective.

Podcast interview

Hello Sebastian, hello Maren. Welcome to the IoT Use Case Podcast. I am very happy that you are with us today. How are you doing right now? Where are you?

Sebastian

Hey Madeleine, thanks for having me on here. I’m looking forward to sharing and spending the next few minutes with you. I am currently sitting in my home office in Cologne and look forward to the next discussions with you.

Yes, nice to have you with us today and greetings go out to Cologne. Maren, where are you at the moment?

Maren

I live and work in Hannover, but I’m nearby and working from home right now and I’m also very happy to be here today.

Very nice, yes, I know it too well. After all, this also enables us to work flexibly from anywhere. Greetings to Hanover, my hometown. Maybe a quick word about you. You are a Senior Associate IT Consultant for Smart Factory topics. Can you briefly introduce yourself?

Maren

I started my career as a dual student at Continental, going through various practical phases and pursuing a dual degree in Embedded Automation Design. After that, I moved into the position I currently hold. I’ve been in my job for just under three years now and I’m in central IT, in the Smart Factory team, where we’re responsible for solutions within ContiTech and for further developing the plants. We are centrally responsible for providing the plants with solutions. I have also been pursuing a master’s degree alongside my work for the past two years.

Very nice. Yes, I’m also very happy that you are with us. Sebastian, how exactly had the two companies met? Was there a history there or how did that come about?

Sebastian

There is a history there. The whole thing started a few years ago when ContiTech launched a call for tenders on the subject of MDA/PDA, i.e. Machine Data Acquisition, Production Data Acquisition. We were invited because we had already been working with our colleagues at Continental Tires for several years. They have a central production platform with us in order to map topics such as quality management, data acquisition and long-term historization, and also to meet a few regulatory requirements. We were recommended and allowed to take part in the ContiTech beauty contest and all the classic processes, which we ultimately won. Today, we support a wide variety of ContiTech plants with our platform. So I was allowed to get to know Maren.

First of all, let me introduce you as ICONICS: You come from a classic software development background and are part of the Mitsubishi Electric Group, although you also operate independently, especially when it comes to hardware. ICONICS was founded in 1986 and has a correspondingly huge and long history, also in SCADA visualization. You now also have GENESIS64, which used to be your SCADA and is now a kind of software construction kit. You handle everything from data connectivity with the appropriate connectors, extracting data, processing it, and conducting analysis. Your solutions are installed in over 70 percent of the global 500 companies around the world. You’ve installed over 375,000 use cases across multiple industries worldwide. You are a founding member of the OPC Foundation.

Sebastian

That was already very well rendered, I’ll have to write that down. I myself am employed in Business Development for the DACH region. I take care of a certain area, certain topics there. On the one hand, I work in indirect sales. I take care of partners, look after them, develop joint solutions with them, work out marketing concepts, drive technology topics forward. This then ultimately applies to all partners, whether it’s an OEM, a system integrator or a technology partner. On the other hand, I also work in direct sales and look after a wide range of customers, such as a ContiTech. We have been part of the Mitsubishi Electric Group for four years and, although we operate independently, we also work very intensively with our parent company and are more or less its Software Center of Excellence, and it is there that I look after cooperation in the DACH region.

Cool. Very nice. Now I always talk about real-world projects here on the podcast. Today you brought your customer ContiTech. Can you tell us what IoT use cases you’re implementing at ICONICS and what project we might be looking at together with ContiTech today.

Sebastian

Yes, of course, with pleasure. We will now share a wide variety of use cases, one more exciting than the other, with you in your network over the course of the next little while and will present that in more detail. Basically, you can actually say that we take care of the topics of visualization, historization, analysis and mobilization of real-time information and then work on top of that a wide variety of applications for each end device. Ultimately, this means that we collect data from all kinds of devices, pull it into our platform, normalize and contextualize it there, and define a wide variety of applications according to which the data is analyzed and processes are subsequently optimized. Typical use cases there include quality management, energy monitoring, determining CO2 footprint, productivity optimization, integration with the enterprise world for data consistency, which includes IT systems such as ERP, MES, Field Service Tools, and more. We then holistically map different types of systems, SCADA solutions, IoT platforms, HMI’s or mobile HMI’s. Industry 4.0 platforms, smart factories, plant historians, but ultimately also in such topics as building management solutions and today we want to devote ourselves to the topic of Industry 4.0 together with Contitech and I think Maren can explain this best.

Yes, thank you very much for the transition. Maren, you said that you also support the solutions internally. I believe ContiTech is one of the world’s leading industrial specialists, especially in the field as a supplier of technical elastomer products. If you type that into Google, you’ll find very different products that you produce and specialists in plastics technologies who are behind them. Completely different industries, 40,000 employees in more than 40 countries with sales several times in the billions that you make there. You are also globally active. Can you tell us your vision regarding digitalization and do you have some examples of the products? I would be interested to hear more about that.

Maren

Of course. We have a wide range of diverse products, which leads to various business areas. This diversity and these heterogeneous structures are reflected in our operations. Our central department, within ContiTech, has the overarching goal of guiding our plants towards becoming Smart Factories, preparing them for digitalization. The main goal is to create real-time intelligent integration, especially between people, machines and IT systems, in order to simply form a flexible and efficient production system. In principle, we differentiate our solutions a bit in this regard. Sebastian has already talked about the topic of machine and process data acquisition, which we cover with ICONICS, but other solutions also play a role for us, such as the rollout of an MES. For example, we have plants where a manufacturing execution system is not yet in place and a lot is still done with paper. Then someone within our team is also responsible for the IoT platform or for recipe management. We really have a very broad base here, and the various solutions are then to be brought to the plants. It is precisely with ICONICS that we focus on machine and process data acquisition, really on the visualization and historization of data. Due to the large number of plants we have, our main approach is to utilize a kind of template that we can then implement in these plants. The goal is to use a basic data model for each machine, which is, so to speak, fundamentally the same for the time being and is based on OPC UA for Machinery, so that we can create a dashboard or a structure based on it, which is also transferable to the plants. The idea that the plant can independently, depending on the use cases, implement their visualization or use cases themselves. So the basic idea is always that we provide the solution from headquarters and then, especially now in the ICONICS area, enable the plants to work independently and then generate the added value. That is above all the background and also the vision that we are pursuing.

Very nice. Can I ask, just a quick question, how many plants does your team oversee? Are these a few in Germany or globally? What’s the scope of this?

Maren

These are plants that are distributed globally. So we have just under 80 major works. Within a certain program management, it has now been decided to focus on eleven first mover plans for the time being, because it is not possible to manage so many plants at once. We’re just not that big a team for that and we can’t manage it.

[13:45] Challenges, potentials and status quo – This is what the use case looks like in practice

You also offer the service of developing these templates together and then making them available to the plants, that you just build on a certain data structure or on a data model. Could you take us through a typical day in your work? Is that about providing the solution or how does that work for you?

Maren

That’s where it differs depending on state of the plants. Basically, a working day always looks very different. On the one hand, of course, we have rollout projects where we initially bring the solution to the plants and provide the template. But we also have plants that already use them in operations. We usually have a key user in the plants, someone who is empowered to work with the solution. They approach us with new requirements. Are these now requirements that are implemented locally? Are these requirements that we also want to include in our template? This then differs very much. But since it is based on this data model, we do not have such strong contact with the individual processes in the plants in the first step.

Before we get to the data model, I’d like to ask you one more question. You now have a wide variety of equipment, machines, plants or even large-scale plants in the factories. Can you give some examples of what those facilities are in those individual productions?

Maren

Exactly, we have a wide range of different products. Many of them involve rubber, for example, the production of industrial hoses. There we have machines such as extruders, but also a handmade table, a braiding machine, a tape winder, but also vulcanization. So simply machines that process the rubber. Of course, it highly depends on the products. The machines are similar in some places, but then again in some places they are not. These would be such typical machines.

Yes, perfect. Thank you very much for giving a few examples, because I think many people associate Continental with tires, rubber, of course, but you manufacture very different products, including hoses and air springs. Now you just mentioned that there are also new requirements from your so-called key users, what are the classic challenges that you face in your department?

Maren

Basically, of course, it’s a challenge to get the solution into the factory in the first place. This is a crucial step for us, that first of all the knowledge has to be handed over to the factory. In the many plants that I had mentioned, there are many in-house developments in some places that implement the same functionalities in the first step, but where there is no service. One person in a plant has the knowledge, may have left, and then no one can continue to work on these historically grown structures. The first step is also the challenge of explaining to the colleagues what advantage they have with the solution in the first place. We also follow the principle that we bring the solution to the plant and then the plants also have a kind of service. So they can create tickets etc. and just get support there and they just don’t have that with their own developments. First, one must evaluate whether this should be integrated into the standard or if the plant is expected to handle it on its own. These are always questions that we have in everyday life.

Have you already set up a business case for yourselves? At the end of the day, this represents a knowledge drain when individuals depart from your plants, taking their knowledge of or from the system with them. Have you formulated a business case?

Maren

With ICONICS, we first and foremost sell the collection of data and historization as added value. If the plants do not yet have a solution, they thus first manage to take another step in the direction of Industry 4.0, that is, to create a fundamental basis, to have information about the data, that is not the case in many plants.

And by sell you mean sell internally, so to your plants, so to speak?

Maren

Exactly, because our customers are the plants that source the solution from us. In our Tire division, for example, it is already a customer requirement to collect this data; without collecting, a process may not be completed. We are not yet at that point within ContiTech. But it could definitely develop to that point, because it has been shown in the past that now the right customers for the products are also naturally increasing their requirements and you have to collect certain data. Of course, we have to guarantee that at a certain point in time.

Yes, absolutely. Sebastian, now you’re working with very different clients and you’ve been in this project for a while. I would also like to work out this point with the in-house development, because there is a certain scalability or non-scalability behind it from a technical point of view. How do you see the business case? Do you have any additions there?

Sebastian

Yeah, so I think Maren did a pretty good job of portraying that. It is simply a possibility to standardize one’s processes and to offer support from a central department in the form of a team of experts who then support globally distributed machine plants or entire plants in order to meet regulatory requirements or customer requirements. You can archive production data, have proof of good product condition, or just have some kind of customer experience through modern HMI’s.

Okay, very nice. One last question regarding technological requirements. I’ve learned a little bit now, there was a, what did you just call it, beauty contest? So it’s probably a little bit of a lofty term, but the bottom line is you probably have a whole catalog of requirements for how you select suppliers and what’s important there for you.

Maren

Exactly, just a few examples. Basically, we did a proof of concept – we didn’t call it a beauty contest, but a proof of concept – where we evaluated the different solutions. The main requirements were that the solution had to provide a certain interface, i.e. where we wanted to connect OPC data, then of course a connection in the direction of the cloud, Azure, but also in the direction of MQTT. The interfaces had to be provided. In that case, it should be possible for the solution to be deployed both locally, on-site servers, and in the cloud. This is because we have some smaller plants at various locations, and we’ve recognized the advantages of cloud deployment. Then one issue has always been that you can cover your user management with the solutions that already exist. In our case, for example, it’s Active Directory. It should be possible that we can also do the management of the users in the application directly through our user groups. Then one factor was always that a kind of self-service should be possible, i.e. the key user can also do something independently if they have a certain knowledge. Is it user friendly? How can we deal with the visualizations, is it that easy? Because we have plants all over the world, every visualization must also be able to be displayed in the local language. Notifications have been an issue. For example, can we send an email in case of alarm, threshold crossings? Can we send an SMS or send a message in MS Teams?

That’s quite a list of requirements.

Maren

Exactly, so we have a whole list and the most important thing is yes, first of all, storing and historizing data. That was the focus, that of course we want to archive data, that we want to visualize it. Exactly and, of course, in conclusion, you have to be able to secure it somehow through a works council and also regarding data protection. The typical stuff all had to be covered, too. These are just examples.

Very nice. Congratulations Sebastian, first of all to you. After all, you won the project and are working together. You seem to accomplish a lot of the things Maren just listed. I know that you are very flexible in terms of the solution architecture and accordingly hardware independent and bring a certain ease of use. Do you actually have a name for your project? Is there some kind of project name for what you have implemented?

Maren

So on our side there is actually always only MDA/PDA or ICONICS. So it doesn’t have a real name.

[24:55] Solutions, offerings and services – A look at the technologies used

Can you tell me exactly what you’ve implemented now? You could hear a little bit of what you just said shining through. Maren, can you summarize in 1-2 sentences what exactly you did?

Maren

Exactly, so what we’ve done is we’re sourcing this base application from ICONICS. From GENESIS64 we use certain licenses. We provide the data at the plant via OPC UA or MQTT, depending on whether the data is transactional or high-frequency. The data is made available at the plant and then passed on or retrieved by the application. Basically, they are then visualized in the application on the one hand. In the first step, we have basic dashboards for visualizing the machine status, but of course also for the individual machines with the process values, i.e. to see how my temperature is running and then the values are historicized. Basically, it’s a bit different from the plants. We either have the application directly in the plant or in the cloud. If the application is deployed in the cloud, then we use another such component of ICONICS, Remote Collectors. These then buffer, compress and transfer the data collectively to the cloud. That’s sort of the basis, so that’s what we do.

Yes, very nice. Do you have any additions there from your perspective?

Sebastian

In essence, components from our ICONICS Suite are utilized. GENESIS64 serves as our overarching platform with features like user management, and it also doubles as our visualization interface. Additionally, we have the Hyper Historian as a real-time Plant Historian, which offers various calculation functions for KPIs and more. It includes some unique features, such as the Remote Collectors, and there’s also a Development Client to enable Maren to work on it.

Yes. Okay. That is, you bring, when you talk about data ingestion, a wide variety of connectors. You will probably provide them from the GENESIS64 side, that is, from the platform side. Or how does the hardware side work there?

Sebastian

We are pursuing the concept of universal connectivity. That means we want to be hardware-independent and we basically don’t care about the manufacturer, if I may say so. The reality is that a wide variety of brands and manufacturers are located in a plant like this or in a facility and we still have to connect them centrally somehow. For this purpose, we have written and developed various connectors, for example, to connect an OPC UA, a BACnet in the building world, MQTT, Modbus, Ethernet, databases, web services, we still have a residual API and, if all this is still not enough, we still have a software gateway, which we can then bring in as an emergency solution, with a wide variety of drivers. This is a concept that we started very early, which is why we also became founding members of the OPC Foundation.

Yes, nice. Thank you for closing the loop to the beginning. It is also very important that you are hardware-independent. Looking at the time, I still have a few technical questions as well, but maybe those can be clarified in a one-on-one meeting with you two then as a follow up. I would also link your contacts at that point in the show notes, also the LinkedIn contacts, then people can just network with you guys as well if they have specific questions there. I think Sebastian is also talking about Hyper Historian. Maren, can you explain what this is all about? What is it and how do you use it?

Maren

Exactly, there are these connectors, with which you can then tap the data. Then it is actually quite simple that you decide in the application itself whether you want to historize a certain parameter or not. Then it is simply stored directly on the server for the time being, and when it comes to further processing, the whole thing can of course also be transferred to the cloud, for example to a blob storage, and then stored there for a long time. There are different options, but basically the data is simply connected there and then made available. Then you can decide for yourself what to do with it.

Is this what you called a template earlier? Is that already a kind of template, so to speak, that you are developing there? Or what exactly is the template about? How does that work for you now?

Maren

The template actually refers mainly to the visualization. Basically, a tree structure is created within the application for each machine. This tree structure alone is standardized and also already a kind of template because they look the same for each machine, except for the process values, which are of course different per machine.

Yes, for example, for the extruder, which is a type of machine where there are different parameters. This opens a tree diagram that you can use as a template for various works.

Sebastian

I just wanted to add once again that this tree structure that she is referring to, that is our asset tree, with which we can then also reproduce actual plants or plant structures. How is the line prepared? What machines are there? What equipment is in the machine? Then visualize this accordingly on these levels as well. You can prepare intelligently, and that’s precisely what ContiTech is currently doing.

You have an appropriate analysis and evaluation behind it. How do you do this data analysis? How does this work and what exactly do you analyze?

Maren

The basic analysis is done in a first step within the plant. The plant has a comprehensive understanding of the processes, existing problems, and potential areas for further investigation. It allows visualization of data and selection of specific time periods or parameters. Furthermore, the plant has the capability to create custom dashboards using a drag-and-drop interface, facilitating specific use cases and enabling a more in-depth exploration of correlations. These processes can be carried out autonomously by the plant itself. Currently, we are not yet fully utilizing the entire spectrum that ICONICS makes available for analysis. This is because we are still at the beginning of our analysis efforts.

Yes, it’s good that it’s an evolving process. Sebastian, keyword real-time, how relevant is real-time in this context for these analyses with you?

Sebastian

For us, real time is simply the area in which we feel comfortable. This is relevant insofar as it reflects that, because you also want to fix a problem as quickly as possible in real time when it becomes apparent that there is a problem. And then we also provide various analysis options, for example, to identify such a problem as quickly as possible. There are just different levels. First of all, as Maren has already described, it is the human factor, using visualization to identify problems and then derive decisions from them. Then the second level is about, yes, I’ll call it simple mathematics or statistics, just to achieve new insights, to calculate KPIs, for example the OEE or CO2 per manufactured part. You could also lay out these KPIs as a core element of production to control plants in an automated way, if you wanted to. And then in the last level, there is advanced mathematics or AI or machine learning. One could connect third-party services, such as an Azure Machine Learning. There is an AI tool from our parent company for non-data scientists. It’s called AI Lab. But we’re also in the process of just incorporating machine learning algorithms directly into our histories and then making that available in the future, and yes, all in real time.

Really exciting. I think there is also a lot of upside potential for very different use cases that already exist and will of course come. That’s why it’s also nice to know what else you have in your portfolio. And I think, at the end, I would like to address again, you have quite a few partners. If you are listening now and you also find this exciting, feel free to talk to Sebastian and ICONICS, because I think ContiTech, you are, I may have said it wrong earlier, because you are actually not a customer at all, but rather an internal one, and you pass it on as a solution. Sebastian, you’re relying on partnership there, too. You have many partners in your network who work with your solution and also use the ICONICS Suite for their end customers, so to speak. I think that’s always important to work out, isn’t it?

Sebastian

Yes, exactly. We work with a wide variety of partners there. ContiTech is such a classic manufacturing end user. A customer indeed, but with the advantage that they have their own project management in the form of Team Maren. Maren is a bit like our system integrator works. There are many different ways in which we can work together. OEM customers who then develop their own products on the basis of our suite and supplement their products, machine manufacturers who offer HMI solutions or smart products, system integrators who implement their own applications for their customers or even in certain areas or special fields. These are commercial buildings where we map building control systems or smart buildings. These are critical applications, airports, data centers, power generation plants, government buildings like the Pentagon, which will be equipped with it. Ultimately, they all use the same construction kit to visualize and prepare their processes.

This calls for another episode. I think you have a lot of exciting projects and I would be happy if there was another project like that in your area. First of all, thank you very much, Maren. Thank you, Sebastian, for taking the time today as well, and especially to you, Maren, for sharing a bit of ContiTech’s practical experience today. I thought it was easy to understand what you do in the project, what the advantages are for ContiTech in the collaboration, but of course also what ICONICS brings to the table. Therefore, many thanks. All that really remains for me to do is to give you the last word for today. I am really happy that you were here today. I would love to have a follow up with you Sebastian. Maybe from a different industry. Maybe we’ll hear from you again. Thank you very much.

Maren

From my side, I can only say, thank you very much for the opportunity to engage in this format. I hope we were able to present well what we actually do and what we want to achieve. I was glad to take part and that Sebastian approached me.

Sebastian

Yes, wonderful. First of all, thank you very much, Madeleine, for the opportunity to introduce ICONICS here again and also to share different use cases with your community. I hope this was an interesting contribution and of course I look forward to further episodes with you. But also a big thank you to Maren. Thanks for sharing your experience here.

I’m looking forward to the whole lot of topics that we have coming up. And thank you for the great cooperation. It was really fun with you. If anything else is unclear, just write to me on LinkedIn.

The contacts are in the show notes. Thank you very much and have a nice rest of the week. Until next time. Take care. Ciao.

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

Questions? - Ing. Madeleine Mickeleit

Ing. Madeleine Mickeleit

Host & General Manager
IoT Use Case Podcast