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PIA Maintenance App – How Proactive Service and Demand-Based Maintenance Is Done


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IoT Use Case - Digital Enabler + PIA Automation

In this podcast episode, automation specialist PIA Automation – represented by Tobias Weber – and independent implementation and consulting company Digital Enabler – represented by Dr. Stephan Verclas – talk about practical use cases in customer service, a new maintenance app and the need for partnerships.

Podcast episode summary

“Every company needs to focus more and more on its core competence – that’s why the future will depend on more collaborations and partnerships. We are already living this credo today – on the customer and supplier side,” says Tobias Weber of PIA Automation in episode 102 of the IoT Use Case Podcast. Digital Enabler helped PIA Automation develop a software package that supports and simplifies its customers’ maintenance and repair activities.

PIA Automation has been working with IoT for several years now. Many will be familiar with the so-called “PIA Industrial App Suite”. This podcast episode discusses how their vision with IoT has evolved since then and what use cases they see in practice in the area of service for their customers. Digital Enabler helped PIA Automation develop a software package that supports and simplifies its customers’ maintenance and repair activities.


➡️ What does a day-to-day production of an assembly line of a customer of PIA actually look like? ➡️ What challenges do customers face here?

➡️ Which use cases really take customer service to a qualitatively higher level?

Keyword IoT and strong partners – Digital Enabler! 🌐🤝🏼

👉🏻 Event note: If you would like to see the whole thing LIVE and have it explained, you can do so from June 27-30, 2023 at the automatica trade fair in Munich at booth A6.302!

Episode 102 at a glance (and click):

  • [09:35] Challenges, potentials and status quo – This is what the use case looks like in practice
  • [19:46] Solutions, offerings and services – A look at the technologies used
  • [31:48] Results, Business Models and Best Practices – How Success is Measured

Podcast interview

Hello Stephan and hello Tobias. Nice to have you with me today. Welcome to the IoT Use Case Podcast. I am very glad that you are here. Stephan, how are you doing today? Where are you at the moment?


Thank you very much first of all for the invitation. I am working from home today. I’ve been working from home for many years, even before Covid, and I’m doing great. I’m about to go on vacation, it starts on Monday and I’m looking forward to it.

Very nice. Very nice. Tobias, how are you doing? Where are you at the moment? Are you also working from home?


Yes, thanks for the invitation also from my side. I am also doing well. I’m excited to be a part of the podcast for the first time. It’s my premiere and I’m also working from home today. I don’t have a vacation coming up, but at least I have the weekend. From that point of view, I’m doing quite well, too. Thank you for asking.

Very good. Perhaps one thing up front. This podcast episode goes live before the automatica trade fair. Tobias, you are also exhibitors, aren’t you? What are you exhibiting there?


Exactly, automatica is our leading trade fair, the most important trade fair of the year. We show the range of plants, of assembly systems and testing systems that we build. In general, the products exhibited at these trade fairs are always those that are built on our systems.

That means if you’re listening to this podcast now and you’re at automatica next week, you should definitely stop by their booth. I’ll link that in the shownotes. And if you’re not there, you can just listen to this podcast. We’ll also talk a bit about what you’re doing in this area.


Exactly, we have a digital section where we present our software products and where, among other things, the maintenance app is released, which we also discuss here.

Stephan, are you also on site?


Yes, definitely, because it’s such an exciting trade fair and not only our customer PIA is there, but also other exciting customers of ours, so it’s a must-attend event.

It’s worth a visit. A warm invitation goes out to you. Drop by for coffee with Stephan and Tobias, if you are on site.

Very briefly, to introduce Digital Enabler in case people don’t know you yet. In general, you are first of all a provider of IT services and IT consulting related to software, data management or the networking of systems and machines, but also connection to the back end, to the cloud or also the integration of processes. For example, ERP, CRM, customer portals and so on. You do this end-to-end, and of course bring with you the corresponding solution and methodological expertise that you not only develop prototypes, but also holistic products and digital platforms for a wide range of customers. I think we’ll be hearing more about that today. Tobias, you two will talk about that later. Let’s start with the keyword “customers”. Stephan, what kind of customers do you have? What companies do you generally work with at Digital Enabler?


As you just said, the entire industrial sector is our target sector, i.e. all industrial customers with a focus on plant and mechanical engineering. This is the industry in which we are active and where we work for customers such as Liebherr, Wirtgen or Kärcher. For a few months now, also for PIA Automation.

Can you tell us what your joint project is about? Tobias, can you explain what exactly you did there?


Yes, very much so. Digital Enabler has helped us to develop a software package that will support and simplify our customers’ maintenance and repair activities. The Maintenance App, as we have named the package, is installed locally at the system as one of several modules of our Industrial Apps. These local applications are then the basis for our system digitalization. In the future, we will also expand this architecture to include a customer service platform. But that will probably happen next year.


Yes, so what we have done for PIA is part of our fundamental belief that digitalization is simply becoming more and more important for the complete plant and mechanical engineering industry. That’s why intelligent software, the topic of networking, the topic of data utilization of the plants/machines is simply becoming more and more important. Then, for example, also things like: What can I simply set up for the service there? And that’s where PIA comes in with its Customer Service Platform. And I think that’s a beautiful example of how digitalization and industry just works brilliantly. And part of that customer service platform is the issue: how can PIA take customer service to a higher or next level in terms of quality? And the maintenance app we developed for PIA for the assembly and testing systems is the first, but big and important step to raise the service to a different level.

As for what that means exactly in practice, I will ask you exactly how you did that in a moment. Tobias, let’s also introduce you. You’ve just talked about your systems. You are a machine manufacturer, you have 20 interconnected sites in Europe, North America, Asia, you are really the world’s leading automation specialist. You are a partner for assembly and testing systems for very different industries. Your customers produce a wide variety of things on the systems. These can be toothbrushes, plug connectors, camera systems, even a wide variety of things. Also drive trains for vehicles and so on. You can take a look at all this online. And now it’s particularly exciting to find out what your vision is here in terms of digitalization?

As you said, we work in a wide variety of industries. There are customers who produce drive trains in the automotive sector, but on the other hand also consumer goods that produce toothbrushes for the end consumer on our systems. Although this is so widely spread, all producers have one thing in common: that they want to make their products better and better, cheaper and smarter. That’s where we come to our vision on digitalization. After all, we don’t just want to be a system supplier for our customers, we want to help them get the most out of these systems. And for this we offer various software packages and services.

When operating such a system, our customers are not only faced with the challenge that the processes in the system itself are becoming increasingly complex, but are also struggling above all with the shortage of skilled workers and the constantly growing cost pressure. In addition, in at least some industries, the innovation cycle is getting shorter and shorter, and then time-to-market is becoming more and more important as a result.

So, for example, if one of our two customers here has to deliver a component to their customer for the first time on day X so that the customer can then integrate it into their new product and then launch it on the market, this means extreme time pressure for the relationship between us and our customers, which is imposed externally. All of this then leads to a situation that is much easier to manage with digital tools. Most of our customers are working on digitalizing their production. But many just don’t have the right tools to deal with that. For the higher levels of the automation pyramid, mature software packages, such as MES systems, have been available for years. But the shift supervisors, the maintenance staff, all the production-related employees often still work in analog or, at best, somehow with data they have entered themselves, with Excel spreadsheets they have made themselves, which often wouldn’t be looked at again. With our digitalization strategy, we want to help our customers move away from that and give them tools to do it in a professional way.

[09:25] Challenges, potentials and status quo – This is what the use case looks like in practice

I would then like to ask you about the details. Above all, I’m interested in the business case, Tobias, from you, and also so a bit why that’s important, what you’re doing there today and also the vision that you just mentioned, what that means in practice. You have just spoken about maintenance and servicing, various software modules. I think listeners come from very different backgrounds. Can you give us a sense of what a typical day in the service department is like? What kind of tasks do you have to do here?


Yes, very much so. So our day-to-day customer service is currently still very reactive. Our service staff supports our customers with small system modifications, coordinates spare parts requests and orders or, of course, provides remote or even on-site support for troubleshooting acute problems at the production system. In some cases, our customers also have a service contract that includes 24/7 telephone support, for example, or regular on-site visits by our service technicians to carry out defined maintenance work on a regular basis. Apart from these regular activities that can be planned, however, everyday life is very reactive, as mentioned above. Figuratively speaking, my colleagues sit in front of the PC and the telephone and wait for mails or calls from our customers in order to then provide support for acute problems.

What are your customers’ challenges in everyday operations? Can you tell us more about that?


Yes, of course, the main challenge is that everyday life is very dynamic. Although one thinks that everything should be very strict and regulated. Ultimately, everyone has the goal of producing maximum quantities in the most standardized, automated way possible. But there are so many factors that influence the process, and this means that there are shifts in the plans on a virtually daily basis, and new situations and challenges arise all the time.

Regular maintenance activities are a simple example of this. In principle, every producer would like to perform this activity during the times when the system is at standstill anyway. But even these periods shift regularly and without software it is difficult to keep track of which maintenance work is due now or which is already overdue. Then, when they are performed, the maintenance person often has neither good guidance nor a means of documenting what they are doing or have done. And so there are often whole DIN-A4 folders full of paper and documentation near the systems. Some of these are then also gathering dust in these folders.


I would like to make a brief comparison with the automobile: in many cars, an indicator now lights up when the next service is due. Meanwhile, even authorized workshops are proactively calling customers to make an appointment for this. Ideally, they do this in good time so that this workshop appointment is much easier to schedule for both the customer and the workshop. In the industry, this type of scheduling has been rarely implemented thus far, and the topic has not gained significant traction yet.

As mentioned earlier, take service to a new level. The reality is often still that maintenance schedules are paper-based. If there is any planning management at all, which is then additionally further supported by the shortage of skilled workers, that it is just poorly implemented or is often just a point of conflict. Things like achieving OEE targets or even routine maintenance, which are very important factors, are difficult to implement. To maintain in a planned manner means to maintain with foresight. And thus, if necessary, to prevent costly machine downtimes or to be able to plan service much better so that as little downtime as possible occurs. The maintenance app we have now created for PIA follows exactly this approach and offers customers a reliable digital solution for service planning.

We all know this from our private lives, many of us also have our own car. You know that from the contract workshops that the service takes place proactively. And it is also nice and interesting to see how this is now finding its way into the industry. You both talked about paper, documentation, but also spare parts that have to be reordered, just as an example. What kind of data is relevant for this kind of projects and also for this software? Which data are used in this solution?


So in the first stage of the evolution, which we have now realized, we are only talking about metadata that is relevant to the components used. That is, how often an axis must be oiled and a measuring instrument calibrated, for example.


Exactly, we see the whole thing, as Stephan has already indicated, as an evolutionary process, a three-stage process. Namely, in the next stage of development we will include the parameters such as the production time or even the number of measurements performed. Then, unlike today, we can no longer just work with fixed intervals, but also take the actual use of the system or components as a basis for detecting when a component needs to be serviced. This saves the customer a lot of unproductive time and, of course, becomes much more efficient.

In the third and final development step, we will integrate condition monitoring systems into the system so that the components only have to be maintained when actually needed. The whole thing is then our progression from time-based, usage-based to condition-based maintenance. Unlike the other modules of the PIA Industrial App Suite, we only ever need the machine status data for the Maintenance App and no process data, even in the following expansion stages.

Right. At this point also a remark for those who do not know it yet. So you have already had such applications on the part of PIA before and this is now, so to speak, the expansion of a new solution, I would say.


Exactly, so our previous software portfolio is just a process analysis tool for the process data. Now it is about the condition data of the machine.

Exactly and about the demand-based maintenance and number of measurements performed. This can now all be done via this solution. In order to implement such a project, there are a wide variety of technological requirements. You have made the decision to choose Digital Enabler here. What are the general technological requirements for the solution? Requirements that were then also perhaps requested by PIA or that you also know from other projects. Could you give me an overview?


Yes, I mentioned earlier that we have a structured, efficient procedure from the idea through a well thought-out concept to the finished product or solution. Our customers’ challenges are often very similar. However, the starting conditions or framework conditions are almost always very different, so that in the end we do not develop or implement standard products for our customers, but rather highly professional individual solutions, because the framework conditions are just as extremely different and because our customers are also at a very different level of digitalization.

Nevertheless, in the end, a stable, safe and long-term and also cost-effective solution in operation should be created. Our in-depth industry or domain expertise, starting from the manufacturers, to the users, to processes and technologies, allows us to have a strong understanding of the actual customer problem via a concrete actionable solution proposal for the implementation. This means that in the end we hand over or transfer the developed solution to our customers and can therefore offer this complete added value. No matter the challenges. And that’s exactly what happened with the PIA project.

Yes. Very good. Tobias, can you report from your practical experience, what challenges you faced, what technological requirements you had for this solution, which you perhaps also demanded of Stephan and the team? What are your requirements?


The biggest challenge on our part is to develop a concept that can form the basis for a partnership between us and our customers. This concept must nevertheless take into account the fact that a manufacturing company is reluctant to share its production data with the supplier. From a software and IT architecture point of view, the basic requirement is to create an architecture that takes into account the data security and sovereignty of our customers.

At the same time, of course, we want to work together to proactively optimize system performance. In concrete terms, this means that data pre-processing must happen at the customer’s systems. At the same time, there must be a communication channel that can provide indications of certain conditions or developments via this intelligent system.

Yes, perfectly. Companies or your customers also share production data if they get value from it. I think you’ve presented it very nicely as well, that there’s now the possibility to do maintenance as needed and also really add value to the customer here. This provides a reason to share this data. We know it here from the maintenance shops with our vehicles. We know exactly why we are sharing the data or what data is available there. It is probably the same with your customers that you are now creating added value there.

[19:40] Solutions, offerings and services – A look at the technologies used

Let’s talk about the solution and introduce it briefly. Stephan, can you very briefly explain this solution in a few sentences? What did you do there in detail?


The jointly developed maintenance app makes it easier for PIA’s customers to plan, perform and document the regular maintenance work that is due. In particular, it is an aid for customers’ maintenance managers and maintainers. In addition, customers can then use the app, which is also like a knowledge database for the machines and systems. There, for example, the maintenance technician could have inserted a comment function for the activities, insert additional information via free text, via comments, but also photos or video files and thus document, for example, abnormalities of the machine, so that this information is not lost. This information can then be taken into account during the next maintenance.

Can we delve a little bit deeper into that as well? I would be interested to know how this works from data recording to processing to analysis. How does that work? Tobias, earlier you mentioned various types of data that are relevant. How does the data recording work? From the control, from your systems?


The data is recorded in our software via the control. The PLC acts as a data pump for our software packages and sends data to our software via MQTT in a defined data model. With the Maintenance App, however, we do not need any of this data in the first development step. There we have no data connection to the PLC. There we work only with the metadata of the components. Each component manufacturer specifies how many operating hours or fixed intervals their component can operate without maintenance. We pass on this information from our suppliers. This is the information that is available in the maintenance app.

Now there are different ways to send these data packets coming from the PLC. Can you tell us more about that? How do you handle this? Via mobile communications? Via your customers’ infrastructure? How does that work?


This is done via an IPC built into the system. That is, this is all our system network, our system infrastructure. As mentioned before, it is extremely critical for our customers as to where the data is located. In order to have a concept with which we do not come up against any limitations in the first step, we install an IPC that hangs in the control cabinet, so to speak, like the PLC. The two are then connected to each other at most via a switch, with an Ethernet cable, and so the data then ends up from the PLC in our software modules.

Okay, do you then also already do the processing of the data locally, i.e. on the controller itself? Do you do any pre-processing of the data? How does that work exactly, how does that processing then work into the cloud in the next step?


Our system is cloud-ready. The customers who want to do that are welcome to do so. But as I said, we are more based on IPC at the moment. That’s where the intelligence actually resides. We are aware of the data we need in order to draw the relevant information and conclusions from it. That’s why we send only the needed information, only the needed data to the software. In most cases, the intelligence and data preprocessing are located within the software, typically in the IPC.

Then you also talked about spare parts at the beginning, where the customer should already be informed proactively by your service. How does it work? Does your sales department then receive a ticket? How does this data evaluation work or how should it work? You guys are working on it right now. Can you explain a little bit how this works?


Yes, very much so. In principle, I would like to say at the outset that a distinction can be made between two scenarios in the spare parts business. In the first case, it is one of the described regular maintenance activities. For such a one, the required spare part can already be stored in this overall maintenance activity and the customer can then request the spare part via a shopping cart function at PIA. Quotations and orders, however, continue to follow the classic path between purchasing and sales.

But in the second case, which is actually much more critical, the producer, the plant operator, has an unplanned need for a spare part. The machine has either stopped or is simply less performant and therefore it becomes necessary to install a spare part there. In this case, once we have access to the Customer Service Platform, the customer can then select a spare part via a menu tree or also via a 3D view. So, by using this approach, we can identify and select the items through the shopping cart and the request process again. This request is then received by us as a ticket. This ticket is then used internally by us to route this request through the internal processes. But our main focus is actually on this close and fast communication between us as PIA Automation and our customers. We are convinced that this will help us to counteract the shortage of skilled workers and also this increasing complexity of the systems. This is how we want to offer a lot of added value.


You have a really great feature with your Industrial App Suite that the applications not only run on your systems, but you can also integrate systems from other manufacturers. This solves the problem that the user often has a wide variety of systems from different manufacturers in their plant. This heterogeneous system is solved and managed on an application site. You can actually use it to manage analytics, optimization and maintenance of a wide variety of systems across platforms with your Industrial App Suite. That’s totally charming and I actually think also at the end of the day your USP with the complete app suite.

You had also mentioned MQTT as a protocol. There are possibilities to integrate any type of control, systems, and so on. This is really a nice advantage to highlight here again. Do you have any experiences from the project that you would like to share with the listeners? I think many are now going down the path, other mechanical engineers who are now taking such learning curves as well. Do you have anything else you might want to share where you think there’s something to learn from?


From my point of view, the decisive factor was that there was extremely open and trusting cooperation right from the start. The competence profiles of PIA and us are indeed complementary. Therefore, it was clear from the beginning who had which role. From that perspective, this was a wonderful project that was fun for everyone to be involved in. Here, one also likes to write to one’s client, i.e. me, the PIA, or Tobi, even on Sundays, if something is still pending.

Tobias, what was it like for you? Do you want to share any experiences from the project as well?


I can confirm what Stephan says. I think it was very decisive that there were contacts at eye level on several levels. On the technical level, we have the situation that the responsible parties on both sides very quickly found a constructive way of working together. Stephan and I established a connection with each other in parallel at an almost breathtaking speed. This connection on several levels was the whole thing that made the project so successful. This is a learning, you should always build this connection at the very beginning of the project. Then you have good prospects.

Now you said earlier that it’s also a solution that’s developing right now. I think Tobias said that about a three-step process. What’s coming or where do you think you’re going? What can we look forward to in the future? Stephan, you are also in the development, you support it and you see the developments. What can we look forward to in the future?


So service is a focus topic of digitalization in plant and mechanical engineering. Of course, we also see other target functions such as product management, development and quality management, through to directly marketable digital products and services. My belief is that the market here will evolve dramatically and hopefully PIA will too. There are also new technologies coming that are really drivers, like artificial intelligence or also machine learning. Sooner or later, such new technologies will become standard in machines and plants in the industrial environment. I think we have created an excellent initial basis here to be prepared for these new technologies in the future and to develop them further.


I think these technologies that Stephan is talking about will certainly keep us busy. We will certainly find one or the other use case there. I think from our point of view today, it doesn’t just affect the spare parts business, but of course other areas as well. In the end, I think you can definitely expect well thought out and developed software concepts from PIA in the future from us and our partners.

Very nice. I could ask many more questions now, because it really is a very exciting project. If you out there find this exciting now, feel free to contact Stephan and Tobias. The contacts are linked in the show notes. We can then discuss in detail a wide range of possible common starting points, including those of a business nature. In this episode, we have learned a lot and gained valuable insights. First of all, what are the systems, what are the added values, what are the use cases, what is the business case for Tobias, for you, and what can be done with them. We talked about how to do that, from data recording to processing to analysis. Therefore, from my side, thank you very much for the presentation. I believe it is not very typical to provide such open and valuable insights like this. Therefore, I would like to take this opportunity to thank you very much and perhaps hand over the last word to you.


Thank you both first of all for the great project and now also for the podcast. I repeatedly come across three key points when it comes to the topic of digitalization. One thing is, I am absolutely convinced that everything that can be digitalized will be digitalized. Second, anything that can be networked will be networked. And third, data is the new gold, even in the industrial environment. My message is still: Anyone who believes they can master this digitalization alone and without a partner will have a very difficult time in a networked, digital world.


I agree with you 100 percent. I firmly believe that every company must focus on its core competence. For this reason alone, the future will live on more cooperation and partnership. We at PIA, and now especially with you, Digital Enabler, are already living this credo. On the supplier side and on the customer side, we want to push this even further through our digitalization and our service portfolio.

That was a wonderful closing word for today. And with that, many thanks to you. And I wish a nice rest of the week for you.


Thank you too. 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