Good morning, everyone, and welcome to our webinar on transforming production with SAP Digital Manufacturing. This is the fourth in our webinar series where we previously focused on PPDS, and now we're shifting that focus towards digital manufacturing. Today, we are very excited to dive into the world of Industry 4.0, manufacturing execution systems and also the capabilities and benefits of digital manufacturing. Over the next one and a half hours, we will present the transformative power of these technologies and how they can revolutionize your production processes. We really encourage you to stay engaged in the session and we actually have a facilitator here. So if you have any questions throughout the session, please just write it in the chat and he will try to answer them at the best of his abilities as well. And then also to note, we have a Q&A session at the end of the session where we can talk to you about the questions and hopefully answer them as well. Without further ado, let's have a look at the agenda for today. So first and foremost, we'll just set the scene with a welcome and introduction, and then we'll move on to one of the harder topics I would say, which is Industry 4.0. Then we'll talk about manufacturing execution systems, some of the benefits and some of the things that you need to think about when choosing your MAS system as well. And then we're going to dive into the history of manufacturing from an SAP perspective. After that we're going into SAP digital manufacturing. And then I think personally is the coolest part, which is the demo where we'll see a physical robot performing movements that are triggered from SAP digital manufacturing. And this is also integrated with S4 HANA. So you will be able to see that as well. Then as mentioned, we have the Q&A session, and then we'll just finish off with some closing remarks. So that is the plan for the next one. So that is the plan for today. And before we really get started, I want to present the team that is here today. And it is my name is Max. And I'm here along with my dear colleagues, Sophia and Hase. And we will guide you through this webinar with the topics of Industry 4.0, MAS and SAP digital manufacturing to get today. Together, we have extensive experience and expertise in these areas. And we are very excited to share insights and knowledge that can help you translate the and transform your production processes moving forward. So let's move on and talk a little bit about who implement is. So for those of you who have not heard about implement consulting group before, we are a Danish born management consulting firm that was founded in 1996. And as you can see on the map, we have offices in multiple cities around EU. And we also have an office on the other side of the pond, actually, in Raleigh, North Carolina, as well. So we also have some physical presence there as well. We are around 1,600 consultants working globally with global customers in multinational projects. And today, we are actually sending live from our headquarters based in Copenhagen, Denmark. To set the scene a little bit about our expertise and what you've maybe seen before in the past couple of webinars, we are really experienced within comprehensive solutions for end-to-end planning and execution. We also focus on system selection and implementations for systems. And we are around 150 consultants specializing within supply chain planning and execution with a heavy focus on SAP. In total, there are 450 consultants in implement that is actually working with supply chain management. And we we are, of course, a part of those 450 as well. And if we just shift the focus a bit to the left and the planning pyramid that you hopefully have seen before, maybe in a previous webinar as well. This is just to tie back to where we have been and where we're going today. So previously, we've had some webinars on IBP. And the past three webinars have been focused on the third layer, which is the operational planning and scheduling. And now we're moving down one element and going into the release and execution phase. And we really hope that you will get insights that you can apply in your organization around this. And just to say, thank you very much, everyone, for joining. We are very excited to see so many participants joining us today. And we really appreciate your participation. As you can see, there are participants from all over the globe. And a really special thanks for those who are attending from outside the EU since we are sending on EU time here today. So a big thanks to you. And now to set the scene a little bit more about the past, present and future on the webinars. And we have previously presented a lot on the PPTS. And this is the fourth webinar in our series. And now, as you have heard, we are shifting that focus towards digital manufacturing. But the road ahead is not fully clear. We have some topics on digital manufacturing that we know we want to present to you. But we really would like your input as well at the end of the session on what you would like to see when it comes to digital manufacturing. Furthermore, these webinars will not be the only thing that you'll see from us when it comes to digital manufacturing. We'll also create articles, articles and blog posts around this area. So we'll keep you posted and updated on things that are happening in this area. Once we are done with the webinars of digital manufacturing, we also have the aim to continue with this webinar format. And we have some future topics in mind, for example, extended warehouse management, transportation management, and Signavio. That could be potential topics for the future webinars as well. And now, before we really get started, we want to take the polls a little bit from you and ask you two questions around the upcoming topics that we are to present here today. So let's get started with that. You will see a poll here showing up on the screen. And the first question is, where does your organization currently stand with SAP Digital Manufacturing? The first option is, we have fully implemented SAP Digital Manufacturing solution. Number two, we are planning to implement SAP Digital Manufacturing soon. Number three, we have started implementing SAP Digital Manufacturing but are not fully there yet. Number four, we know we need to implement it but are unsure how to get started. And number five, we have not started with SAP Digital Manufacturing yet or have the ambition to do so. So let's have a look at what the audience says here. We can see there are a few that have not, doesn't have the ambition to do so yet. And there's a little bit of a mix at the moment. Some need to know, need to implement it but are unsure on how to get started. And some have actually started implementing it as well. Cool. But it looks like the majority at least have not started with SAP Digital Manufacturing yet or have the ambition to do so at least. So let's move on to the next question. What best describes your organization's approach to Industry 4.0? And the options then being number one, we have a clear defined roadmap for Industry 4.0 adoption. Number two, we have an overall strategy for Industry 4.0. but still working on the details. Number three, we have started to define our Industry 4 .0 strategy but it's a work in progress. Number four, we are just starting to explore Industry 4.0 and haven't defined a strategy yet. And number five, we do not have an Industry 4.0 strategy or roadmap at the moment. So from the poll, we can see that we're just getting some answers and it is the latter two options that are leading right now. So to say some have also an overall strategy, but still working on the details. Okay. But that's great, great input. Then I think we can move on to the next next slide. So why should you care about digital manufacturing? Well, digital manufacturing is essential for shape staying competitive and efficient moving forward and under investing in the digitalization within manufacturing space can lead to critical organizational challenges in the long term. And as you can see, there are a lot of challenges and symptoms that we can see if we do not invest in this going forward. And I have just picked out a few of the ones that I did. I believe have a large impact on the organization and the shop floor operations. And the first one being that the lack of real time visibility and this prevents us from getting the real time data, taking fact based and timely decisions. And that is a big, big thing that is not very good in the shop floor and also moving forward. We have the data silos where we'll have fragmented data, disconnected processes and slow operation and increased amount of errors that we'll get from this data silos. The manual processes is also something if we do not digitize our processes, we'll stay with the paper based and the manual workflows, which will cause delays and increase the amount of human errors that we see on the shop floor. Furthermore, if we do not digitize, there's also a risk for miscommunication and ineffective communication between departments, which can lead to conflicting priorities and misunderstandings and also production delays in this as well. So just in general, these challenges highlights the need for digital manufacturing to bridge the gaps and provide real time insights and optimize operations in full. And what do we typically see then when we implement digital manufacturing? Well, it's a transformative force for operational efficiency and supply chain performance. And some of the key improvements that we usually see is that we gain a 10 to 30% increase overall equipment efficiency, we get a 10 to 20% increase in the reduction in production cost. And we also see a 10 to 40% in improved asset utilization as well. So these improvements demonstrate how DM can significantly improve operations and can be a crucial cornerstone in boosting efficiency and performance in the supply chain. Moving on to the next topic, which is industry 4.0 and Hase will present that to you in just a few seconds. Thank you. Great. Thank you, Max. And thank you everyone for online for your kind of interactions there. Please keep coming with more questions and comments in the chat. And if we don't answer them in the chat, we also have our Q&A session available. And we'll see you in the chat a bit later where we get a chance to actually answer those questions that might be a little bit too difficult for our facilitator, perhaps. To start, we wish to invite you to an outside-in perspective on industry 4.0, the fourth industrial revolution, before we deep dive into MES, specifically manufacturing execution systems. And kind of setting the scene here, I will take you through some quotes that we often hear about this topic. And one common one could, for example, be, we use paper on the production floor, and you might have a desire to digitize your current production processes. It could also be the OT engineer who says, how might we automate our production line? And finally, we might have a manager or a leader in the distance yelling fancy buzzwords like digital twin, IT, OT, architecture, PLC, SCADA, MES, unified namespace, manufacturing integration, digitization automation. This is the topic for today, and I hope we can kind of shine a little light on these subjects here in our presentation. Great. So, at implement, we typically do not think of, let's say, digital initiatives and operations excellence to be two separate things. Together, we see these as having kind of a, these two will have a symbiotic relationship where we can accelerate existing initiatives, but also create new opportunities to have a more lean organization. essentially lean on steroids, as it says there, when we combine the two and kind of reap the benefits of having, of having that combined force. For this, for this to be actually successful, we have to focus on the business impact and purpose for, for our digital initiatives. We also need to be having a very engaged and involving leadership to kind of drive this forward. We also need to have end to end data transparency and flow throughout the organization. And last but not least, we have world class IT architecture and connectivity. And these topics we'll get through throughout the session and hopefully we'll cover all these ones throughout the presentation here. Now, achieving digital transformation requires a kind of structured sequence of steps, each building on the next. And before we dive into the differences between industry 3.0 and 4.0, I'll give a little bit of a brief history lesson and I, I promise I'll keep it relatively short. And the first industrial revolution came by in 1760 with the invention of the steam engine to drive machines. This was the first industrial revolution. The second industrial revolution came with mass production, essentially more like line production spearheaded by Henry Ford in the US. That's the second revolution. And then we get to the third one. You also see here on screen, we talk about computerization, connectivity. This was the invention of the PLC. This was the invention of the PLC in 1968. And today we talk industry 4.0. We talk internet of things, we talk robotics, we talk AI, and essentially the transformation that we have in the technology we have today, we live in the fourth industrial revolution. And when we transition from 3.0 to 4, we already had in the industry 3.0, we already had automation, we already had production systems that actually ran into the by themselves. However, transitioning into industry 4.0, we talk about visibility, seeing what is happening. We talk about transparency, understanding what is actually happening. Or, yeah, why does it happen as well? And then we have predictability, trying to predict, be prepared, try to actually capture before something happens, what can we do? And then adaptability, the last one, the highest step on the ladder, if you might say it like that. It's all about self-optimizing systems, systems making decisions. We have algorithms that can actually, let's say, take the decisions based on the data that is available. And we use this a lot, this maturity, this case here you see, and we use that for kind of classifying the maturity of different companies. And we look at IT systems, we look at the organization, we look at the culture within the organization as well. And for most companies, they actually land between a 2.0 and a 3.0. That's probably the most normal one, the most common one we do see out there. And there's a handful of 4.5s. Of course there is. But thought leaders already, they're kind of talking about industry 5.0, what's actually after 4.0. But at least from our experience, there's so many people that are still stuck in automating production. There's so many people that still need to gather the data to get the visibility into the production, and even talking about industry 5.0. And even talking about industry 5.0 is maybe a little bit too early. So focusing on the core, focusing on the steps that we see here is what we see adds value. And if we kind of move on and talk a little bit about why do we do this? Why do we want to strive to become digital businesses? Why are we talking about industry 4.0? And one of the reasons could be latency. is if we actually look at how we react to changes and let's say unplanned events that could be market changes, it could be smaller operation hurdles like production stops. An event can happen like this and we'll have a latency related to the insights, gathering insights. We have a latency regarding analyzing this event, also taking the decision and ultimately actioning on that decision. Digital transformation aims to if we look at the same graph, but in a digital organization is not in a digital organization. We aim to squeeze that together. We want to ultimately react faster to changes, shortening reaction times, decreasing any loss across the whole value chain. And there's some drivers to that. Essentially drivers that can drive that we have a faster or less latency and a faster response. It could be stuff like real-time capabilities. For our insights. For our insights systems integrations and there's also is one there that's called the cyber physical systems all the way at the end which are in fact these systems that make the decisions themselves. So we squeeze in the PDCA cycle. We make faster decisions. We do it with reduce by reducing latency. And if we actually move on and we take a look at something like like if we look at from an industry perspective where our organizations actually at today. And we can look at something like the Siri index that we have here. It stands for a Smart Industry Readiness Index. It's essentially a maturity model or a industry segmentation model that focuses on processes. For example, advanced planning, shop floor automation. It focuses on technology. That could be the connectivity between the technologies we have, the intelligence that we can build within them. And we also look at the organization, so the workforce. How do we facilitate learning within the organization? The change management aspects. This is not all about automation. Having a high level of automation is not enough to rank you highly in this index. I've seen automotive manufacturers with 400 million DKK fully automated painting lines, but essentially, this is the orders that how the orders flow into that painting line is that they, that they actually do it by Excel or they do it by a printed PDF. And digitization is not just automating a painting line. It's across the value chain. It's across the whole business. It's across the factory. If we dive into some of the specifics here on the slide and the kind of industries that we can see here, we can see stuff like electronics, semiconductors, and pharma production ranking very high in the digital maturity. Electronics and semiconductors are also high variance. And that means that there's also high variance between the maturity levels. Some factories might be super mature and some factories might actually not be so mature. So there's a high variance there. Looking in the opposite direction, we see like general manufacturing. We see food and beverage and textile, which from an industry perspective are actually less mature. However, they have a lower level of variance. And that means that they look a little bit more like. So using something like here, the smart index here, smart readiness index for industrialization, we can actually have a look on the industries and we can, we can maybe get a little bit of inspiration. If we are a general manufacturing or we are in the textile industry, we might want to take a little bit of inspiration from some of the other industries. And I want to just take some time to introduce you if you're not familiar already with the global lighthouse network from the economic world economic forum. So it's essentially initiative that's led by the world economic forum and all about identifying and promoting factories. Or is essentially entire value chains that are leading the way in adopting 4.0 technologies at scale. And I think at scale is actually very important. Right now there's about 190 lighthouse factories and that number changes all the time. But you should think of this as kind of the hall of fame for digital transformation in manufacturing. And the goal of lighthouse network is to show that transformation is not just possible. It is actually happening out there. So there's actually companies that are doing the digital transformation. And there are kind of these beacons of innovation, but you cannot just not not every site can become a lighthouse. There is a rigorous selection process in order to actually become a lighthouse to qualify. The site must demonstrate that they have not only a adopted digital technologies, but also adopted digital technologies, but also that they have actually achieved significant business value from that. That could be cost reductions, improved quality, faster delivery times, or potentially lower carbon emissions as well. If we turn these these factories are the kind of leaders. And we also see them here highlighted on green on the slide. And while many companies are well, the lighthouse factories are kind of leading the way in technology adoption in technology adoption. And also, of course, getting value out of it. We have many companies that are still are many factories that are still caught in kind of this pilot purgatory. And pilot purgatory is where companies find themselves when they try to adopt new technology or new systems or new digitally enabled solutions that they have where they never up actually where they never end up actually deploying at scale. Actually, 84% of the pilots, they they never gain the full value of what they could have achieved if they've actually scaled the solution. And that could be many reasons for that. It could be that the company is not clear on the problem, that the business case hasn't been straightforward. We failed to actually involve the stakeholders that we need to. And can also, of course, a very common one be resistance to change. It is simply easier to stay in the pilot phase. And there's too much work in actually the company being able to be able to scale this. So this technology adoption curve. And that's something we experience a lot. There's a lot of pilot purgatory out there. And it's also something that is voiced in the World Economic Forum's Global Lighthouse Network documentation. The companies that manage to scale, what do they actually achieve? And that's what I want to talk about here if we dive into into the businesses and kind of financial business and financial impact of digital factories. On the left, you can see some of the key KPIs that that that they actually use within the global lighthouse network. They've categorized them into production, productivity, sustainability, agility, speed to market and customization. And here you can see a kind of impact range observed. You can see that in some cases, they're a bit extreme like four to 200% in factory output in the market. And that might be an extreme case. And that might be an extreme case, having 200% increase in your factory output. But the notion here or the important thing here to mention is that the ranges observed, even the bad ranges, are still a pretty good case. And you can also, for example, if you take out inventory reduction or lead time reduction, you still see almost double digit reductions in those two parameters as well. And it might lead some people to people to ask, do we maybe we should actually stop up and ask, do we even really need to build that new factory? Is that really necessary when we can get these improvements? Of course, keep in mind, big investments, right? It's big investments in digital factories, digital solutions, Industry 4.0 in general. So, if we look a little bit more into the use cases and kind of the areas where these solutions have been adopted and implemented and have added value, we see that the typical use case takes between 20 or 10 to 20 months to implement. But over the next three years, it will pay for itself approximately three times over. So a two to three X return on investment over three years, which is, I mean, a good business case, we can't really argue too much with that. Focusing in on some of the capabilities where we do see these improvements, there's a lot of focus on quality, there's a lot of focus on integrated planning. And I will say the analytics part and actually doing analysis of data is also something that is exponentially growing. If you look at the Global Nighthouse report today, there's AI all over it. And of course, there is. It's the trend right now. But some of these core capabilities are still the ones that shine. And we do see an average break even of 2.7 years to actually break even with a lot of these digital use cases that we implement. Great. I'll move on and talk a little bit about architecture. Because in the start of our presentation, I mentioned that a world class architecture, that's a requirement. So let's dive a little bit into that. Some people claim that the Egyptians actually created the pyramids. But it is in fact, the ISO 95 standard. That's the pyramid you see there on the left. And that's a traditional automation stack. That's how we traditionally think about the automation stack when we talk about when we talk about ISO 95 at least, or when we go out to organizations. This illustration appears quite often. In this illustration, we have ERP on the top. We have MES in the middle sandwich layer. We have DCS and SCADA systems moving down to the control layer. And then we have PLCs. And then at the end, the lowest level of the pyramid, we have sensors. We have any signals. We might be picking up robot arms and a lot of other, like the physical process of manufacturing. Traditionally, when we are integrating in a pyramid structure like this, we build point-to-point integrations. So we build an integration that goes from the ERP system, down to the MES. The MES builds upon that, enriches the material perhaps, enriches a route potentially. And then the MES actually conveys that to the SCADA system. The SCADA system conveys that to the PLCs. And they move the actual robot arm or the actuator or the pump that we have in production. That's the traditional one. We build point-to-point and we need to flow through all these systems before we actually get to a real production process at the end. Today, we see that this pyramid is dissolving from the top. Everything is becoming more, let's say, a lot of things are moving to the cloud. For example, ERP systems moving to the cloud. We have data lakes. We have any third-party, potentially a lot of cloud-based SaaS solutions that we can also have in our landscape. But if we look to the future and kind of into the vision of tomorrow, as it says here, we say it's a microservice architecture. And microservice architecture, it's not just implement that say that this is the future. It's not just Gartner that says that this is the future. But top companies are running with this today. That's how top companies have their architecture. And it's all centered around, actually, it focuses a lot on IT-OT convergence. Here we are fully converged. There's not a clear separation that IT owns ERP and that the SCADA system is owned by OT. Here it's fully converged. We have one system of truth. Be that unified namespace or something like that. There's many names for the same here. But we're moving into that microservice architecture with the flexibility of quickly swapping out apps, but a shared data structure in between them. And just to elaborate a little bit on IT -OT convergence so it's as clear as can be. IT systems traditionally or IT and OT and we talk about convergence. It's a little bit of a buzzword as well. But IT traditionally have owned the kind of enterprise systems. We talk ERP. We talk the Outlook solution we have in Microsoft 365. Kind of these bigger enterprise systems. Where OT teams have the operation technology teams have always focused on machinery, PLCs, SCADA, everything on the kind of factory network. And traditionally, these networks have also been isolated, right? And in many cases, most cases, they are also today totally isolated networks. But with an MES, MES sits right in the middle of IT-OT. It is converging the two. So, even if you try to implement an MES or you go into a microservice architecture, you're forced to take into considerations that there are some blurred lines here. We need to work together. We need to break down the silos between the two. Before I move into MES specifically and what that is all about, I just wanted to highlight a little bit on the organization side. Because adopting Industry 4.0 technology or digitally transforming your factory, of course, impacts the organization. And we have, we essentially, if we have an example like this where we have Linda. Linda today focuses a lot on her quality control. So, she actually uses a lot of time on controlling quality. She might prioritize or schedule tests, calculate parameters, and also kind of adjust these production parameters on a machine. So, she focuses on controlling today. For her future, her future when we have implemented, we have become more digital, we have a digital factory, we have been successful with these Industry 4.0 initiatives, and we have digitally transformed. Her job will look a lot better. Her job will look a lot different. Her job will focus on quality improvement and not that much on control. Because many machines, intelligent algorithms, and other stuff have these feedback loops and they can take the decisions and actually also act upon this. For this presentation, we will not dive further into the kind of organizational impacts, but new skills in the organization are, of course, necessary. There's a constant learning and development and, of course, a reshaping. There's a constant learning of job throughout this process. Now we will dive into digital manufacturing, specifically, SAP digital manufacturing, we'll just talk a little bit about MES in general. And for some of you, you might already have an MES system. And some of you, you might even have SAP DM implemented already, as you could see. And for other organizations, MES actually just stands for Microsoft Excel sheet. That's very common because essentially defining MES is not easy. If there was two people in a room that said, I want MES, they would not be asking about the same thing at all. If we bring up the pyramid again, not by the Egyptians, but by the ISO 95, we can look at this structure again where we have ERP on the top. If people said, I want an ERP system, we're pretty clear about it. There's not so many vendors. We can choose SAP, for example. And if we, for example, went and said, I want a SCADA system, that would also be a relatively easy, or at least it's very clearly defined what you actually want. You want a system for supervisory control and data acquisition. That is what it does. It supervises, it controls, and it collects data. That's a SCADA system. MES, however, that's a little bit of a different beast because it is not so simple. In some cases, MES is actually, contains all the necessary systems for a given plant to run and execute production. And essentially, it's a technology stack on itself, MES, and it can be in many cases. And I think we can agree on that MES is actually positioned between ERP and the SCADA system. And that makes sense. That's the area where it's located. And there's kind of these four main core capabilities within MES. And you'll see that in the majority of MES systems. That could be work order management. In SAP DM specifically, we talk about SFCs, software control. It could be scheduling, actually reacting instead of on the ERP side where it's enterprise resource planning. It's not execution. On the ERP side, we might do some scheduling as well. But on the MES side, we actually have insights about machine downtimes, availability of resources. And we can actually do that finite or that fine scheduling based on real data. OEE is also a core component of MES, of any MES system. Because OEE also has the last one, which is downtime tracking. Tracking when machines are down. Why are they down? MES systems typically have dashboards showing the machine machine being down. And then, of course, OEE falls naturally within the MES space as well. And we have a requirement to collect a lot of machine data. So, of course, for the analytics there, they fall under MES. And the reason why I said that if two people said they wanted MES, they will not be asking about the same thing. It can be, of course, kind of exemplified by some of the other MES capabilities we have there on the right. It could be that you're focusing on process automation. It could be that you want recipe management. It can be that you want to store a set point value for a temperature for a specific oven or the RPMs on a pump. How fast does it pump? That is very company specific. When we're looking into why we would actually choose or what is it actually we choose MES systems based on, since 2000, there's been a survey that's been run by Gartner since 2014. This survey has always improving quality, improving data visibility and trace across sites and enforcing standard processes or best practice. They've been the kind of main ones. They've always ranked highly. But in recent times, we also see that at least from a trending side, what has become more and more important is the product traceability and regulatory compliance, as well as improving performance and asset utilization. These two are kind of hot topics and other ones that we see more and more are kind of leading the selection process within MES. And if we go into some of the benefits and some of the benefits that we have with actually running an MES system, of course, there's these six. We say that there are six key value drivers for MES. We say that there are six key value drivers for MES. It could be lower scrap and rework in production, production visibility and improved decision making, improved quality control, enhanced workforce productivity, improved machine utilization and paperless production. And that all sounds great. But what does that actually mean in terms of numbers? And based on our numbers and something we've experienced ourselves through the projects that we've done, we do see cost reductions, actually double digits, as well as lead time reductions. Work in progress, and we do see cost reductions, or WIP is super important. And we do see that MES implementations do drive us to actually have a reduced WIP in our productions. Productivity increases and of course, OEE improvements. These are all business results that we've seen out there when we have implemented an MES system. But implementing an MES system, deploying an MES system is not that simple. Essentially, there is those implications that you need to take into consideration in regards to time to impact, total cost of ownership and risk. And there's these three archetypes that exist within deploying an MES. You can choose to have an approach where you have a build approach. We actually go ahead and build your system yourself. In regards to time to impact for this case, we do see that there's actually a relatively high time to impact. And you might say, well, doesn't it make sense that I just buy something off the shelf and I would have an even higher time to impact? No, not necessarily. Because if you go with a build approach, you're actually able to kind of focus on use cases. You don't need to implement the whole thing. We can go live and have a kind of composable architecture. Start off with only going live with what we actually need to do. Start with that one specific use case. So the time to time to impact is actually lower here. Total cost of ownership comes with a big uncertainty when it comes to the build approach. Because we might be building something on some legacy old solutions or we might be building on top of something we already have. So please build with caution. We need a we need IT capabilities within the organization to do this and preferably skilled ones. So if we jump to the one on the right, buy approach. I should mention that no matter what MES system you buy off the shelf, it will still require significant customization. You cannot go live with an MES system and expect that everything will work just out of the box. And I'm not saying that SAP DM does not have the accelerators to build ERP integrations faster. Of course they do. And they do help and they do accelerate. But there is some some level of customization or configuration that is required when you go with a buyer approach. Here time to impact is actually on the high side. So here we can actually as well as the kind of total cost of ownership. But there's a big difference between the different MES systems that we actually have out there. There is a lot of MES that are very specific to industries, for example. Now, if we kind of combine the build and the build and the build and the build and the build, approach and the buy approach, we have this hybrid approach in the middle. And here we focus on function specific apps. We might have a core MES like SAP DM, but we have other applications that we've chosen just because of that specific use case. And it's very common that we see a hybrid approach. We, for example, have a very nice application, a function specific app for OE calculation. And we would like to continue to use that. If you have a kind of our vision of tomorrow, a microservice architecture, this will be no problem. You can integrate it and you can relatively easy adopt any function specific apps that are built for purpose and actually kind of shine in their area of expertise. All right. And that's it from my side. I am just going to hand it over to Max. He's going to talk a little bit about the history of manufacturing in SAP. And I hope you enjoy it so far. Okay. Thank you very much, Hasse, for giving us input on both Industry 4.0 and MES. And thank you for staying on for this session. Thank you very much, Hasse, for having us. So let's have a look at the history of manufacturing from an SAP perspective to get a sense of where we've been and what lies ahead on the horizon in the future. So if you're into SAP, then you know 1972 was a big year. 53 years ago, SAP released its first ever product, the accounting product R1. So that was the start of it all, a big thing happening. In the 1990s, we saw the introduction of MES products hit the market, but not from an SAP standpoint at this point in time. However, in the early 2000s, we can see that in 2005, SAP acquired something from Lighthammer, the company, which was the module MII. And in 2008, they also launched ME, which was initially called XMII. MII. And this was also an acquisition that they acquired from VisiPrice. And these have been two modules that have been very useful for SAP users for many years. And there has been some changes along the way. So if we just fast forward a little bit to some of the big milestones in SAP's journeys. In 2014, SAP introduces SAP HANA. SAP HANA. And then two years later, SAP S4 HANA. And then two years later, they introduced SAP S4 HANA that is built on the SAP HANA platform. Then in 2018, SAP changes its scope when it comes to manufacturing, and they released their digital manufacturing cloud product, which is released. And this is basically to enhance the cloud capabilities and the integration to improve the end-to-end manufacturing. So that was released in 2018. So that was released in 2018. And now we can see that in 2027, SAP is planning to sunset Netweaver, as you might know. SAP SACC is also being sunsetted. And you might have heard that you maybe need to move to S4 HANA during this time. And that goes for ME and MII as well. Those, the Netweaver that is the operational foundation for the system is sunsetted. So it will be the same implications for ME and MII. There will be available support until 2030, but it will be at an additional cost for that. So let's have a look at some of the implications that we see of the sunset of Netweaver and actually explain a little bit about more about what it is as well. So for the foundational operating system for ME and MII, is then Netweaver, and it's also the same for SAP ECCC. And it is two different technology stacks. So we have the Java stack that is for MI and ME. And we also have the ABAC stack, which is for ECCC. The critical days here is that it's end of life in 2027. And the end of the optional extended support is until 2030. But this will come, as said, at an additional cost. So what implications will that have for you if you have ME and MII today? What will be those implications afterwards? So you as a client can continue to use Netweaver as long as you have it installed on your server. So that goes to say that you can use ME and MII as long as you have Netweaver installed on your server. There are, however, risks without official support. As after 2030, there will be no further support from SAP. So these third party vendors will not have as much input and as much data to see how they can fix the issues after 2030. Because the source code will not be available for them after this point in time. So what you need to think about is to plan ahead. You need to consider the risks that there are to continue on ME and MII after 2030. And you need also to plan accordingly for the sunset of Netweaver as well. And if you are thinking about moving from ME and MII to SAP digital manufacturing, there are also some things that you need to think about moving forward. And the first and foremost thing is that a move from ME and MII to SAP digital manufacturing should not be considered a transformation, a transition, but a transformation. So it's not a simple migration. It's a transition that we need to do from ME and MII to DM. And it can involve reengineering of the workflows that you have today. And some of the key differences that we see in ME and MII is that SAP digital manufacturing and SAP ME and MII, there is more efficient machine integration in digital manufacturing that we've seen previously. And we also see that it's the advanced production process designer is more advanced than the previous in the predecessor MII, the business logic services. So what we need to do is to do from ME and MII. Some of the benefits then, if you're moving from ME and MII to DM, then we have the reliability and scalability part of it, which is that if you're going to DM, you're going to a cloud-based product, which is a cloud-based microservice architecture and patches and releases works seamlessly and will be updated seamlessly. There will be no local updates required at each site. You'll also have the automatic service replacement and this also makes sure to minimize the downtime that you see on the shop floor. You have further cloud advantages. So you have the reduced need for onsite infrastructure and local development. You have easier maintenance and scalability of your solution. So if you're planning to do a rollout, it is much easier to use SAP DM to use a template solution and rollout to multiple sites. And you'll also then achieve faster deployment. And updates for remote factories as well. So that is some of the things that you need to think about when it comes to the history and when it comes to what you need to think about after 2027 when the sunset of Netweaver takes place and what you need to think about when it comes to digital manufacturing. So let's move on and have a look at some of the capabilities with SAP digital manufacturing and also what sets it apart from its its predecessor as well. So SAP DM provides a standardized solution for rapid MAS deployment. Some of the benefits that you get from choosing SAP digital manufacturing is that you centralize a function to a functions to a cohesive capability. So before MAS is usually developed locally and also the responsibility is a local responsibility. But with DM, it centralizes this function to a more cohesive unit going forward. Another benefit with DM is the standardization of processes with SAP functionality going down to the shop floor and we'll be able to use the same terminology in all different departments if we're going with SAP DM all the way down to the shop floor. As mentioned before, we have the cloud based benefits as well. So we'll get seamless updates and it will be really minimizing the downtime that we see in the sites, which is a big plus as well. Another thing that I think is personally really great with SAP DM is that there's a lot of ready to deploy tools already set up in DM, which only need minor configuration for it to work and to get a good overview of it. And you'll see some of these things in the demo at a later stage. But one example is the production operator dashboard that you'll also see. And that is very easy to configure and set it up as you would like to have it with KPIs and so on. If you are thinking of switching and if you are switching, if you're thinking about switching MAS system in general, then it's really important that you evaluate the mass market and compliance needs from your business perspective. So there's a lot of industry specific systems and you need to really investigate which one would be a good fit for you. On the second point, then we also need to make sure that MAS fits to your functional and technical needs. You need to look at the end to end processes that you have on the shop floor and make sure that it can cover all that you're doing today as well. When it comes to DM, SAP digital manufacturing, it works best with SAP ERP as for HANA is an optional thing to have with SAP DM, but it also works with other ERP solutions as well. If we're looking into the data part of SAP DM, what it expects and so on. Of course, it expects master data from ERP systems to get material master, bombs, routing, etc. It expects that from the ERP system. Maybe if you can loop back to the triangle that has a show before, it expects some data. The use of SAP DM also supports automatic reporting for accuracy as well. And it enhances IT and OT data integration. So DM here acts as a bridge and translation layer between the shop floor and the ERP system. So to conclude, SAP digital manufacturing boosts MES functionality and integration and it also promotes operational excellence in manufacturing in full. So let's move on and have a look at what sets it apart and some of the capabilities that is different from SAP manufacturing execution. So what SAP digital manufacturing does is actually extending the traditional manufacturing execution. So there's a lot more capabilities and they have been developed from before. So ME and MII were products that were purchased a long time ago and the architecture and so on is a little bit limited because it's been developed by different parties. And now with digital manufacturing, we have seen a fresh start and they're able to set it up the way that they really want to. So that is super nice. And some of the things that we can see here is, for example, the scheduling and optimization. And with that, we get intelligent orchestration of label and resource services and we're really able to manage the shop floor in real time. We have the production and process automation. So there's seamless data exchange between the shop floor and the business application. So again, SAP DM acting as a translation layer between the shop floor and the ERP system. With DM, you'll also get a lot of insights from your shop floor. So with this deep production insights, we can also perform process improvements because with the real time data, we can take real time decisions. We can also make longer analysis to actually improve the processes. And as mentioned before, if we find out in one site that we have found a better setup to do it in digital manufacturing, then it's super easy to go back to a site that has previously been implemented with SAP DM and update those as well. When it comes to the quality management. When it comes to the quality management, that is also a super nice part with SAP digital manufacturing, because there are some capabilities here that you can upload a machine learning model. We can use photo recognition on the shop floor and we're able to actually spot products that do not meet our quality requirements as well. We have the execution and orchestration, which you'll see a lot more of in the demo that we will do. So you can also see out to the right in the picture here that we have production order operator dashboard as well. So it's really user friendly as well. And it's easy to execute on orders. But in conclusion, SAP digital manufacturing optimizes your production and manage quality and also drives continuous improvements in your shop floor as well. And now we just wanted to exemplify a typical setup of SAP DM and SAP digital manufacturing implementation. And as you can see, is again looping back to what has to spoke about in the MAS part, and that is the IT and OT convergence. So as we can see here, the IT ownership has traditionally been with the S4 HANA in this case, and any cloud integration middleware. that has been the responsibility of IT. That has been the responsibility of IT. OT, so the operational technology has been responsible for the solutions of SCADA, DCS, control systems and PLCs before. So historically, these two functions, IT and OT are very siloed departments, and these functions now need to work in tandem going forward. But introducing SAP digital manufacturing can also act as a bridge, compelling IT and OT teams to converge and work together and collaborate more effectively in the future to achieve improvements on the shop floor. When it comes to the ownership of the MAS, well, that is a tricky question. And that is basically can vary greatly from business to business. And often it is a shared responsibility. For those of you who are unfamiliar with SAP DM, it includes a crucial tool called production connector, as you can see down to the right as well. And this connector is vital for building machine connectivity and also communication with SCADA PLCs, DCS, IIoT devices and more. So to conclude by embracing this IT and OT convergences spoke about. Organizations are not just keeping pace with change. They're gaining a strategic edge over competitors. So that was a little bit about the history of DM and also some of its key capabilities compared to other MES systems. And now we move on to personally my favorite part, which will be the demo. So thank you very much for listening. And Sophie will be the best to see. Thank you very much. Thank you. Thank you. So that's the for the next one. And this is to generate what we call SFCs. These these as if C's goes in, as you can see, which is highlighted in the next in the production execution logic where we have set up some different flows. So when we execute DM will do whatever we are saying because we set up the flows before and configured whatever we wanted to do. Then when we release the SFCs, it go into the production operator dashboard. In the production operator dashboard the operator are able to see the different SFCs and release them whenever they are ready. They can also see, for example, the work instructions and whatever operation they need to start. So it is very easy for the operator to have an overview of what needs to happen. When they then release the SFC, it will go into the robot and into control system, we have set up some different paths that the robot will do and then it will start running. When it starts running, it will also generate some different data. It will, for example, generate the robot arm status, the arm position lock and which color that I picked. This transactional data will be sent back to DM. So in real time, whenever a robot pick, in our example, candy, the data will be sent back giving the robot arm status and which kind of candy it picked and the color and also confirm that it picked it. It will not only be sent back to SAP DM, it will also be sent back to S4 utilizing PAPI. So imagine that you have the data transparent in all part of your supply chain. So you have an end-to-end process where the data is very transparent. So you have the execution at the shop floor and you also have it in DM. But you also, as a supply chain planner, can sit in your ERP system and monitor that everything in the shop floor goes as it should and the inventory is going down whenever you produce something and you use some of the raw materials. So that was just to give you a little bit of how the data flows in SAP DM and with ERP and also going to the shop floor. Now we'll go a little bit deeper into our little example and our little demo. And to make it fun today, we did a candy production because most people love candy. And we have a plant called P100. And this plant, we have three different raw materials. We have the Apple Zing, the Strawberry Fizz and the Blueberry Bing. And we have one finished good that we want to produce, which is called Fruity Fringy. So let's take a little bit, go a little bit deeper and look at our resources. First, we have Max, our shop floor operator. Then we have Hasse, that is our site production planner. And then we have Sophie, the supply chain planner. And lastly, we have the robot, Robota. You may have the robot, you may have the robot, you may have seen these names before. And so, it's also to make it a little bit fun. Yes. So, we also draw up the flow. So to give you an idea of what we were going to in the demo. And first of all, we have the supply chain planner, Sophie, who is receiving an order from the client. And when she received the order from the client, she go into S4 and release the order. Then when the order is released, it's automatically going into DM as explained with IDOCs, where we have Hasse, our site production planner, who receive it. He can then release the order and then it generates the SFCs that we talked about before. And when it generates these SFCs, it goes down to the shop floor operator dashboard. And Max, our shop floor operator, will be able to see whatever that needs to be reduced. He can also see the work instruction if necessary and ease operation that needs to be done when he executes the flow. When he then releases the SFCs, the robot, the robot, will start picking up in our example, the different raw materials, AppleSync and etc. to pack our finish back. Lastly, this is monitored all the way around. So we have our, again, our site production planner, Hasse, who can track and monitor all the different data. So whenever something is released, Hasse can, with real time data, see whatever's happening in the production. So imagine that you have, you can monitor everything that's going on the shop floor when you're sitting as a site production planner. And it's not only Hasse that are able to see what's going on. So for the supply chain planner that is sitting in the ERP system and S4 can also see what's going on, because as we talked before, we have the integration to pack, so she can see whenever everything is confirmed, it will send it, it will both be sent to DM and to the dashboard, but will also be sent to S4. So she can also see if the inventory is going down and how many raw materials that is here. It's just to see, say that the data is transparent all the way to the supply chain and it really gives you a very good overview of what you're having and what you're producing. And it's also streamlining your processes and ensuring that it's transparent to the end-to-end process of your supply chain. So let's take a look at the demo and how it looks. Hello and welcome to this demo in SAP Digital Manufacturing integrated with its 4HANA. We have created this demo to illustrate some of the capabilities of SAP Digital Manufacturing. In this demo, we will explore different areas. In this demo, we will start with a release from S4 and then we will release an order from DM afterwards. Then we will go to the work instruction in DM and then we will illustrate a robot flow where we execute an order from DM. Afterwards, we will have an error flow with the robot and then a replenishment flow. And lastly, we will look on a dashboard and show some analytics. And then this demo will be done. First off, let's see how the supply chain planner release an order in S4 and how it's later on received in DM. SAP is for HANA serve as a core system integrated with DM. It provides essential data like bill of material, routing, material master, resources, etc. Data flows from S4 to S4 and back again, which will be demonstrated later in this demo. Here, Sophie, the supply chain planner, goes into S4 and then checks the order quantity and dates and release the order as you can see here. Once it's released, it automatically flows into DM, where the order needs to be released again. Now we will go into SAP Digital Manufacturing. Here you can see a large variety of apps. In this demo, we will start going into managed orders. In managed orders, you can see the order that we released from S4. We selected the order. We selected the order. We selected the order. We selected the order. We selected the order. We selected the order from S4. We chose the amount that we want to produce. In our case, we want just to produce one. And that's the food that finished back. Now the order is ready to be released, which will generate SFCs. The SFCs will automatically be transferred to the production operator dashboard, which we will take a look on next. The production operator dashboard is an app that is very customizable and we can configure it based on the need of the operator, setting what copy eyes we need, work instruction, etc. Now we will show you the work instruction that has been set up for this flow. The operator dashboard. The operator dashboard provides detailed works instruction. Operator can review, for example, recipes, 3D image, and how a simple goods and component are detailed. Let's start here with the example that we want to illustrate. We start with the Apple SYNC. Here you can see the component and the recipes. As you can see here, there will also be something for Blueberry Bing. Here you can also see a picture of it and also the recipe for the recipe. Then we have the strawberry Bing. Then we have the strawberry fish. Then we have the strawberry fish. I also can see the picture and you can also see the recipes. You can also see the amount of each raw material that we need to produce. Let's continue into the operator dashboard and start the flow. When you push start, the first operation will start. And in this example, it's the pick Apple SYNC. When we have pushed the button, the robot will start and pick Apple SYNC. Then the robot will detect the color, as you can see. Then the robot will detect the color, as you can see. And then when it has detected the color, it will put the piece of candy to the wall, to our finished good. Now it will send back the data to DM that the operation has been done and is ready to the next operation. This will be shown just now. As you can see here. As you can see here. As you can see here. And then you can see it will automatically start the next operation, which is Blueberry Bling. Now the robot will start and detect the color again and ensure that it is the correct piece of candy that it put into the finished good candy bag. As you can see, it's real-time data. So every time the robot does something, it will send it back to DM. DM will send it back to S4. And if you, for example, have some inventory or other stuff that you want to be sure that it in the data is updated, it can do that. Now you can see it will pick the last operation, which is the strawberry fish. It detects the color again and put it in to the finished good. The last operation is that it will simply the candy bag and will put it in to our outbound, which is our laying in the front, where we will send it to the customer. Again, it will come up that the operation has been done. And it will start the next operation automatically. As you can see here. It gives a really easy overview for the operator when they are at the shop floor. Now the robot will pick up and put it in to our outbound lane. And when that is done with all our piece of candy, the order will be confirmed and will be removed from the DM. You can also see here that we have our KPI's, which can be set up. So it also can see how efficient the production has been. And as you can see here, our production is very efficient. And we don't have any mistakes, which is not really realistic, but it is in this example. Now we have seen a happy flow. Now we have seen a happy flow. And now we will try to run an error flow in order to see if DM can handle this as well. Let's go to the shop floor. As before, we start the order. And the first operation will start, which is the apple sink. And the robot will, as before, pick the apple sink and put it to the color detector and put it to our finish. If you finish good. If you have a good eye, you can see that now we have a pink piece of candy instead of a blue piece of candy in one of our lane. So when it starts the next operation, which you will do as before, it will start the blueberry bling. And instead of picking a blueberry bling, it will pick a strawberry fish, a pink pink piece of candy, which is pink piece of candy, which is doing now. And then it will detect that it's not the right color. And then it will put it in to the lane where it should be in the strawberry fish. Then there will be real time data where you can see in the DM that it picked the wrong color. So it will be clear for the operator that there has been a mistake and it's put back to the correct lane. Now it will continue as before. And then it will try to pick the same operation, the blueberry bling, and detect if it's correct. And then the flow will continue as before. Now we will try to go to replenishment and illustrate how a replenishment flow could be. The replenishment flow, you just push a button in DM and then it will start to pick up the color and detect it the other way around. So we can also detect if it's the correct piece of candy and put it back to the lane where it belongs. And again, it's real time data. So then it will be sent to DM and then it will start the next operation and you can set it up that it also will send to ISPOR. Finally, a dashboard has been created to illustrate the real time data that is from DM and directly from the production operation. It shows the operation, the upcoming task and the completed order. This data will also be updated in ISPOR and be visible, which we will also illustrate. So let's take a look. Here you can see the production planner sitting and monitoring that everything is as it should at the dashboard. Let's go a little bit deeper into the dashboard. Here you can see that the order is coming in and then you can see the current operation that are being created. Here you can see the 0010, which will be the 0010, which will be the apple candy. Now it's switched to 002. We have speeded up the video a bit in order to illustrate it fastly, but this will be exactly the same time as the video with the robot where we went to all the operations and then it will just show it. In the corner, you can see a snapshot of ISPOR, where you can see the orders that are confirmed, but you can see the operation time of each operation that has been produced. So it's to say that all the data is not only being sent to DM, but it's also being sent back to ISPOR. The data is not only available in ISPOR, it's also available in multiple different external applications. In this example, we created the dashboard in Grafana, but it can also be in other systems. So that was just a quick going through of everything. And you can also, in the dashboard, you can have all kinds of data that you want to monitor. You can also have the average production time. You can see the production that we have produced over time. So it gives you a really good overview of everything and also what is currently happening in real time. data in our production. Thank you so much for watching this demo. I hope that you could use it. If you have any questions, you can reach out to one of the consultants that created this demo, which was illustrated in the first page. Thank you again. See you. Good. I hope you enjoyed the demo. And now we have talked a lot. So now we are really keen to hear your input and if you have any questions, both about the demo, but also about industry 4.0, MES, all kinds of general question is also something that we would like to answer. And as you can see here, has this also joined me now. So now there's two of us. So please take it away. If you have any questions, you can just write it in the chat and then we will answer it if there is anything you want to ask. And otherwise we will just stand in silence. Yeah, exactly. That's also fine. And we are going to use the full time. So we will stand here for, we are just kidding. Any questions? Any functionality related to plant maintenance in DM? Yes, there is. And to be honest, I would actually reference the SAP DM roadmap for this one because it comes and goes how much is actually in scope. Because there's also other solutions from SAP that are specific for plant maintenance. So there's one, I forget the name, but it's an asset something. So that also does exist. And to not kind of cannibalize each other, then they kind of focus on that software instead. There's some functionality regarding to it, in regard to plant maintenance. And to be honest, it's also something you could build if you had the desire to do so in SAP DM. Yeah, I hope I answered your question there. Yeah, any comment related to the PPDS functionalities? Yeah, you can also, that we also have talked about having a webinar about that you can having the PPDS running your planning and then you can put it into DM. And then it can run, so you can plan in PPDS and then it works very good also going to S4 and then from S4 going to DM. So we have this flow. Yeah. And ultimately, I think from a PPDS perspective, SAP DM will receive the orders once you release an order out of S4. So as soon as it's released, it'll be available to DM. And you can also integrate with planned orders, but in most cases, the implementations I've seen is when released from ERP, it hits DM. And you can do that with PPDS, right? So you can handle that throughout PPDS as well. Yeah. Great. How DM is suitable for converting from PIC to DM? Is it a conversion or a fresh implementation? I think Max also covered that a little bit. It is definitely a fresh implementation. I mean, of course, you can use some of the business processes that you have today, right? So some of the ideas and logic behind it, but you need to start from scratch. So you can start from scratch and build from scratch. So in this case, yes, you'll be starting kind of from scratch. However, I think that, again, you can use a lot of the process which you already have defined. Yeah. Interesting. How is ERP and DM integrated? That's a good question. I don't know if it's actually already been answered. I'm just reading off the screen here. But traditionally, if you integrate ERP and DM, you do use a point-to-point integration. Depending on you have on-prem or you have a cloud-based S4HANA, it's going to be looking quite different. Traditionally, we have, as Sophie also mentioned, S4HANA on the one side, it would typically pass through something like cloud integration. If required, a cloud connector if you have on-prem systems, but then you would actually transfer IDOCs. And it's the traditional ones. I mean, it's a, it's a, it's a, it's a, it is all the traditional IDOCs that we have, LoRVCS and so on and so forth, the traditional IDOCs we have for, for external communication. And there is kind of artifacts you deploy within cloud integration that enable this mapping and makes it a lot easier than, than, than a traditional ERP integration for an MES. So, yeah, I hope, Piotr, I answered your question there. Great. Next question is how much effort would it take to connect a CNC machine to an existing SAP setup? Both ways of communication. And when you say SAP setup, I think you, I'm going to assume you refer to an SAP DM setup. And there's going to be many, many ways to do that. Also, it depends a little bit on what you have there already. But integrating, for example, a CNC machine where we know that you're going to be able to connect a CNC machine. We need to collect data. If you already are collecting data on a form of, let's say, a KEP server, or we have a MQTT broker somewhere, we can leverage that to, to actually just integrate DM and that KEP server. And that would be recommended versus doing point-to-point integrations on machines. You can do that. SAP DM actually talks a lot of different things. You can, it talks MQTT. You can also integrate using REST. So, You have a lot of different opportunities. And depending on your architecture, that setup can look in many, many ways, I would say so. Yeah. I have a question. If it's included in the SAP IPP package. No. It is not. No. Unfortunately. Yeah. That would be great. Great. Good. Any more questions? No. No. We talked about briefly in our break and that when we had the DM and we talked about Papi and connecting DM back, that it's not something that needs that much of a work. It's really easy and standard. So, I think that's a good question. You can just send the data back easily. It's not something that requires that much to S4. You're not building custom Papis for this integration. You're using standard ones from SAP. Exactly. And it's just enabling them. And then you're pretty fast up and going with that. Yeah. And I can see that came one more question. Possibility to use DM to integrate SAP QM models to laboratory robots. Yeah. Of course. And right now. And right now SAP DM actually. I know it's on the roadmap for finished sampling, but if you do sampling in process sampling, SAP DM can handle that. So, let's say you have inspection lots on that are tied to a process order or something like that. Then you can report data collection in SAP DM through like laboratory equipment or something like that. And then SAP DM will facilitate communicating data that down into the Step All right. Cool. Should we end it here with the questions? Yeah. I think we had some good questions. Yeah, we did. So let's do that. Yeah. Thank you, everyone. Thank you, Hase. Hase will just step aside, and then I will just do a closing remark and wrap up fastly. I promise that. So we will just briefly say what is the benefits of SAP DIAM and the benefit is that you have real time visibility into your production processes, which enables fast decision making and improved operational efficiency. It also have a seamless integration with the SAP S-Wahana, which ensure that there's consistent data between planning, execution and analytics. It enhances enhanced productivity to automations and digital tools that reduce manual work. It improved quality control, which there was also a questions about with the real time monitoring and analytics. So it helped address all the defects that could be in the process. Lastly, it works in a process management with the configurable dashboard and enhances process control. So as Mac started, we had a lot of web air for three webinars before. This is our fourth, and we mainly talked about PPDS. And today we talked about MES and DM. And we want maybe to have one more webinar about SAP DIAM, but going more into what should a company do? How do you get ready to implement SAP DIAM? If that would be a little bit. And we're also talking about future topics, as Max mentioned, about extended warehouse management, transportation management, or Signavio. But we really want your input in order for us to do whatever you think is inspiring. So we do something that you want to listen to. And our only requirement is that it's focused on the end to end processes in SAP. So let us know in the chat if there's something that you want to hear more about. Then we will take it into consideration when we are planning our future webinars. And if you have anything, you can put it in now or otherwise, you can also put it in later or write us and then we will really take it into consideration. Yeah. If some of us missed the first three webinars and would like to see those, we have recorded them. Yes. Ah, it's just you. Yes. Yeah. We have recorded all the webinars. So if you want to see them as well, you can just go in and do that. Good. So there's not much more to say from us. We really enjoyed having this webinar and we hope you did as well. Thank you so much for joining and thank you so much for listening. We hope that you liked it. And also thank you so much to my colleagues, Hasse and Max. So yeah, thank you for today. And of course to Thomas that is having the chat and answering all your questions there. Thank you for today. Have a nice day.