Integrate Industry 4.0 into Your Intelligent Enterprise | SAP TechEd in 2020
[MUSIC PLAYING] Hello, and a warm welcome to SAP TechED. And our session today around industry 4.0 and how it integrates to your intelligent enterprise. My name is Dominik Metzger. I'm part of SAP Product Engineering. And I'm responsible as the Program Lead for our Industry 4.0 program, which is our strategic program around industry 4.0.
With me today is Rob. Rob, you want to introduce yourself. All right. Thank you, Dominik.
My name is Robert Noce. I'm a Chief Architect in Digital Supply Chain. And in my role in central architecture, one of the focuses is ensuring a consistent and flexible architecture for industry 4.Now. Very good.
I want to start by taking a look at our agenda. So we've got a couple of very insightful topics we want to go through. We want to start by laying a little bit the foundation and looking at what is SAP strategy in and around Industry 4.0, in other markets, especially if we have views today from North America. You might call it the Industrial Internet of Things. In Asia, you might refer to it as the Industrial Internet.
Here in Europe, we call it Industry 4.0. And Industry 4.Now is our strategic response to requirements in and around of these technologies. The special focus for today will be on the technology enabler. So, what technology do we need to make the Industrial Internet of Things or Industry 4.0 a reality? And then we'll dive even deeper and look at what does a North Star architecture look like with SAP when deploying technologies with Industry 4.0.
Very important components of those are Edge computing and also Industrial Big Data management. So how can you really harvest the tremendous amount of industrial data that is being generated in and around your shop floor, your manufacturing, or asset operations to gain significant business value? And we'll close it with a few selected customers that have been successfully adopting Industry 4.0 and Internet of Things capabilities. With that, let us just jump right in and start with a strategy overview. So Industry 4.0 or Industrial Internet of Things is not a new topic.
It's been around for a couple of years. And we at SAP have been heavily invested in Industry 4.0 from the early days. What we have noticed when working with partners such as McKinsey or doing market research is that we found that the adoption of industry 4.0 still remains very low.
Below 30%, in fact, where companies have scaled up from maybe a prototype or a proof of concept in one plant to a large scale of deploying Internet of Things capabilities. The reason we believe why this is the case is that in order to really scale up Internet of Things capabilities, you require a high degree of standardization, right? The way how you integrate to your machine layer to your sensor layer. And when these technologies were first introduced, there was obviously a very limited that we say level of standardization across companies from the producers of automation equipment to manufacturers of SCADA, RPOC devices, and then to the enterprise software layer to allow a very easy ITOT, so Information Technology and Operation Technology Integration.
Now is the time where we believe that this problem has been solved because numerous standards have been introduced. Think about the Asset Administration Shell, think about OPC UA, then that's automation markup language E class. There's a tremendous amount of standardization that we, at SAP, have adopted in order to be able to integrate very seamlessly into automation providers. We believe that industry 4.0 is still as relevant as ever.
We've observed that especially in the early days for the last five, six years, a lot of the initiative started in the factory, right? So companies started to prototype and run proof of concepts and select the plans of factories in implementing Internet of Things capabilities in the industrial context. Now, we believe that there is significantly more value potential when scaling these initiatives out of the factory and into the entire enterprise. So essentially, connecting machine device data with your overlaying enterprise processes. For example, made available by the Intelligent Enterprise from SAP, so your ERP or S/4HANA business processes. So our strategic response to these capabilities is our program Industry 4.Now, where we believe the focus needs to be starting with customer requirements because we notice that many customers have a huge requirement in the individualization of products.
So it doesn't matter if you are in consumer products and you're producing sports shoes, or if you're an industrial machinery components, automotives, or even in life sciences. Many requirements across those industries are increasing demand of individualization of products with very, very fast response time to customers. And in order to do that, we believe yes, you need to reinvent production. But you also need to connect the entire company from the shop floor, device, and machine data through the top floor where you have analytics and instead capabilities.
This is the, let's say, strategic focus for SAP and to also give you an outlook where we are investing. So with Industry 4.Now, we are seeing four major themes that we are investing into. Those are structured across as I introduced, of course, factory and plan processes.
But we start actually earlier with intelligent products. So we believe companies that gain close feedback loops, so insights, how their products, how their machines that they're manufacturing are being used. If you can use this information to improve your design and your engineering processes that this is a significant value. So the way how you introduce, how you develop, and engineer products is a heavy investment area for SAP. That's also where our partnership with Siemens lies in achieving a end-to-end digital thread.
So from the moment an industrial asset, let's say a big manufacturing machine, right? Or a vehicle has been engineered and designed in the engineering department when it's been manufactured and assembled on the shop floor when it's been dispatched, when it's been deployed at the customer site, and assembled again when it's being operated until it's being sunset. Managing this entire digital thread is a key pillar of our strategic investments in intelligence products. The second big pillar, intelligent factories.
We mentioned that obviously the shop floor is still very much in focus. And where we are heavily invested in is and having a highly scalable architecture, combining the best out of Cloud and Edge capabilities. We'll talk about this in our chapter around Edge computing later a little bit more. But the sneak preview is that we have a capability with our SAP Digital Manufacturing Cloud to run entire manufacturing operations both mature execution, but also material insights, and shop floor insights from the cloud, but with a highly scalable, and also reliable performance Edge component. Also, very important is the deep integration of supply to line processes.
So how does supply, such as the material flow from the warehouse gets integrated to your production processes? This is a heavy area of investment for us where we, for example, integrated tightly our extended warehouse management capabilities with the Digital Manufacturing Cloud. And last but not least here at this pillar is AI, artificial intelligence. So we believe that there is significant value potential in bringing Artificial Intelligence to the shop floor. We've done this, for example, in the area of quality management with visual inspection, where we've partnered with Google in order to bring a machine learning algorithm that analyzes visuals from a camera, for example, to detect quality issues, and then race a non-conformance with worker.
Intelligence assets is all around how you are operating your assets, or your machines, or your manufacturing. So here, we are heavily investing in, as we mentioned earlier, in staying up-to-date with the latest standards that are available to have a very easy plug-and-play type ITOT convergence, and also have a very let me say integrated asset performance and strategy process with asset let me say, asset maintenance processes in your ERP system. So to have a holistic grip on your OEE, your Overall Equipment Effectiveness.
Last but not the least in this pillar is we have significantly invested how we can make use out of industrial big data. We'll talk about this in our industrial big data management subject on the agenda later. And last year on the pillars is the power people aspect. Because we believe no matter the maturity of technology, there will always be maintenance crews. There will always be operators in plants and factories. And we believe it's important to keep these workers safe and also to enable them within a tough decision support that if very unexpected events that even with prescriptive techniques weren't foreseeable that those can be resolved by a cruise on the shop floor with the right decision support.
And this all is based on our business technology platform and our technology foundation that we're going to talk a lot about today. And it's also extended by our business network strategy because we believe we're Industry 4.0, or the Industrial Internet of Things is very heavily focused on optimizing what's happening in your own four walls in your company. Yet, we believe by close collaborating between companies for quality processes, manufacturing processes, but also product engineering processes, achieving these close loop, so getting a very tight collaboration going in how your products are being used and managed is a significant value. Looking at the technology enablers that we want to talk about today.
So you've seen already the big picture. We've just covered our strategy and the different strategic themes, such as intelligent products and intelligent factories that we are focusing on. And keep in mind, this is all in the context of bringing real-time data from the shop floor, from devices, from sensors, or from your actual products in production to enterprise business processes.
Now, what we want to now really delve into is the technology enablers that make this possible. And you see them here at the bottom layer with Cloud computing and Edge computing. We believe that especially in a shop floor context, there's always a necessity for an Edge component. Why? Because any manufacturers listening in today know the significant business impact and disruption it can cause if there is a standstill of production, even just for seconds or minutes.
And obviously, in cloud application has never the, let me say, availability as an Edge device or an on-premise device. So here, our latest architectures, we need to combine the best out of both worlds because the issue with pure Edge computing or on-premise computing, even in factories is, and same with warehouses, well, you have to deploy it factory by factory, warehouse by warehouse with a deployment in those plants. So our strategy is to have best out of both worlds, have a very leading edge in the plants and warehouses that ensure availability while having a very scalable cloud that allows you cross plant across factory visibility. Internet of Things and Industrial Big Data Management, well, obviously, with Industry 4.0,
huge value lies in the automation of the shop floor of your processes, automation by automation hardware, right? Whether that's different, let me say, production techniques or production hardware, whether it's AGVs, Autonomous Guided Vehicles, whether it's modular production that you run automated, whether it's automated warehouses. But automation is key with Industry 4.0. And with the Internet of Things and the Industrial Big Data Management, we make sure that we orchestrate the operations. Meaning that we guide based on shop floor, orders, work orders, the machine layers. So it's a true-- let me say, integration of steering the actors some of the machines of the devices, but then making use out of the tremendous amount of data that is produced, the failure coach of machines, the positions of AGVs in a, for example, in a factory, in a plant, the, let me say, non-conformance of quality checks, so making use out of this data to run predictive or prescriptive business scenarios. And hence, running Artificial Intelligence.
Another area of investment for us is in 5G cellular networks. So obviously, still a relatively new technology, we're talking here of private 5G networks that would be deployed in factory settings. But this is the big picture. Amd I think another big picture is in our application landscape. So before we delve deeper into the technologies, I wanted to give the big picture on what are the different applications that we provide to deploy Industry 4.0 capabilities as part of our Industry 4.Now strategy.
And what you can see here on top is, again, our big pillars, the intelligent products, intelligent factories, and intelligent assets. And this on across what we in SAP called the designed to operate process. So from the design and engineering of products, planning them, demand and supply, manufacturing them, assembling them, delivering them to wherever they need to be deployed, and then operating those assets and products, all based on a common business technology platform. So what I want to call out here is under the product design. Aspect is our product enterprise product development, which is really our key application to manage anything around product requirements.
So how do I, as an engineering department, keep track on what are really the features and capabilities my product needs to have? With an integration, for example, to SAP Qualtrics to understand customer sentiment, but also with very tangible quantitative feedback that we get by having connect the products based on IoT. Here is also, well, a Siemens partnership lies, and of course, orchestrated by S/4HANA, our product lifecycle management, which ensures a consistent product data foundation across the entire lifecycle of a product. In planning is our integrated business planning application, which orchestrates sales and operations planning, a demand planning, supply planning.
So how much demand we expect from our products? How much supply do I need to procure and manufacture? And then, of course, how much inventory do I need to keep? We have S/4HANA here in the center., especially on the manufacturing side, we're supporting actually a very high range of manufacturing scenarios. Because manufacturing isn't manufacturing, right? There are tremendous differences if you have, for example, a configured to order or even engineered to order scenario where you have obviously highly customized products versus if you have a classic make to stock or more medium, make-to-order scenario. And what we are supporting, especially with S/4HANA and our manufacturing for production engineering and operations are highly complex configured to order scenarios.
With our Digital Manufacturing Cloud, we support a huge variety of manufacturing scenarios in the cloud, combined with Edge capabilities that we will talk about in a little more detail later. What you can see here by these little color codes in the corner is whether the applications are in the cloud, on-premise, whether they can be deployed on either, or if they're on the Edge, especially as we talked about earlier, the combination of a manufacturing Edge and Cloud is here, for example, symbolized in our digital manufacturing clouds, obviously deployed from the cloud, and then an Edge component deployed on-premise. Deliver, obviously, we already spoke about it, the tight integration of our manufacturing solutions with SAP Extended Warehouse Management to allow this supply to belying the seamless integration between the warehouse processes and your production scenarios. And last but not least, there is asset operations. So how you manage and actually run maintenance tasks also with mobile applications like SAP Asset Manager that allows maintenance crews to have always the latest insights in the maintenance tasks that they are to perform, as well as our Assets Strategy and Performance Management and our predictive maintenance and service, which allows us to choose the right balance between equipment health, productivity, and availability of an asset while ensuring that we have predictive or even prescriptive maintenance capabilities. So this is the overarching business application landscape.
And this all runs based on our business technology platform, where we have, of course, analytical insights and where we have a huge integration framework, and other business technology capabilities. Good. Now, I think this is more than enough to introduce what is our high level strategy in and around industry for now. What is our business applications landscape? I think this is the right time to delve a little bit deeper into our architecture. So, how does this all fit together for a customer that deploys these solutions? Thanks, Dominik. So fantastic introduction to the vision and really you're getting an appreciation of those things.
I think it's fairly clear. The focus of those things really is what's bringing together those use cases, what's really making industry for now possible. And really, this architecture is the underpinning behind that.
So from a technology perspective, what you're looking at is our overall industry for all architecture. And it's really reflecting how machine data is embedded into the industrial process and delivered to the operational users. This architecture has some guiding principles behind it. First and foremost, it's secure.
So when we're dealing with IT and OT convergence, when we're taking information from the shop floor from the warehouse, it's really important to have a secure communications. This merging of cyber physical machines into our technology stack means this overall architecture needs to be secure, used to be interoperable. So the ability to interact with different stacks portable. So Dominik did a great job mentioning some of the aspects of Cloud and Edge, where one cold line can execute business processes that could be run on the Cloud, could be run on Edge, factory floor on-premise, open modular, affordable, extensible, a lot of key principles that are driving this architecture. And what I'd like to do is just walk you through a couple of aspects here. Let's start on the left.
Left, we see machines, devices that are connected. We have an Edge platform, multiple edge solutions to help pick up that machine data, process data, analyze it on the Edge, bring it up, store it in the Cloud. And what you see across the top or multitude cloud application. So in the previous slide, you had a good sense of what the applications were from design, applications, planning, manufacturing.
Well, these applications now have access to that data. They can enrich the data. There are steps within the data processing, things like adding acid health scores as an examplE, and as Dominik mentioned, the decision support for things like visual inspection. What you can see in addition to the consuming applications that really makes this architecture robust are the various integration points. So you'll see integration with our business technology platform to things like S/4HANA, ECC, this might be in private Cloud, maybe on-premisem and in addition to additional data sources that you'll see in the bottom right corner.
Take a slightly deeper look into the architecture now. So while SAP offers fully managed cloud solution for the projects and our applications, this architecture is designed for choice, openness, and extensibility. So again, starting from the left, you can see the choice to have machine data brought in from our Edge components, but also from partner clouds, from partner providers, hyperscaler, IoT solutions. So there's a choice in acquiring the machine data, as well from the data storage. So industrial data lakes and how this data is accessed is really a key pillar behind the overall architecture.
There is a choice behind having that managed fully within SAP or also leveraging your investments with your current providers. Overall, again, choice of deployment. We see applications that are available in the cloud, being able to run and execute on the Edge, the overall solution portfolio they have here, supports multiple hyperscaler. So we deploy our digital supply chain applications in our industry for .Now applications, on AWS, on Azure,
as an example. But ultimately, all of this centers around the business technology platform. So we leverage the business technology platform to take advantage of services, such as an integrated authorization, integrated authentication, and really allowing our applications to focus on that domain promise, and lock those fantastic use cases that were described by Dominik previously. An important aspect of the architecture, again, shining a light on the IT and OT convergence. So we talked about the architecture being open. Let's take a look at plant connectivity.
Plant connectivity, you might know from manufacturing execution from our MII product, really is a shop floor component. It supports a multitude of protocols, centering on open protocols like OPC UA, Modbus, MQTT. But in addition to that, there's also an SDK to integrate to a variety of additional providers and controllers on the shop floor.
Working together with PCO, in a Planty Connectivity is our Edge services product. Edge services really providing that general connectivity layer to also connect additional IoT devices, providing other aspects of storage, persistence, and also capabilities to run modules, such as machine learning or predictive scenarios. So now that we took a look at some of the technology, I'll hand it back to you, Dominik, to talk through a few elements of Edge computing. Yeah, very good. And I think we're already in the middle of it. So we've now covered what I think is a very, very crucial point that Rob walked us through is how do we really connect to the shop floor or the, let me say, real world Internet of Things, right? So the real things that we want to get data out, right? And we talked about plant connectivity.
We talked about SAP Edge Services. Now, in order to go a little bit deeper into that, especially when we look at the example I gave at the start, how do we make the best out of Cloud technology and Edge technology, right? Which is a little bit of a conflict. Because as I mentioned earlier, whenever we run production, manufacturing, or warehouse processes in factories, and plants, and warehouses, we have highest expectations to connectivity, in availability of the solutions, reproduce significant amount of data volume and require bandwidth.
But at the same time, it slows us down tremendously when deploying to 30, 40, 50, hundreds plus factories and plants if for each individual location, we need a deployment. So the hybrid architecture that we have launched is to combine, as I mentioned earlier, the best out of both worlds. So with our Digital Manufacturing Cloud Edge Device, we are now, for the first time, offering to deploy a hardware, a piece of Edge appliance in a factory, which is extremely lean. I've been seeing their pizza box sized hardware appliances, which allowed to run the most critical business transactions from our manufacturing solutions on the Edge, so that if there is an issue with connectivity, if the internet connection stops, if there is a huge, let me say, bandwidth we want to run through it. There is no disruption, whatsoever, to the business operations. So in order to achieve that, we deployed a flexible lifecycle management, which allows us to deploy our applications in a containerized architecture on two, for example, based on a Kubernetes spec onto this hardware appliance.
It's a very flexible deployment, so almost not only by application, but even by application function, we can containerized capabilities and make them available on the Edge. And this achieves a high elasticity, an extremely high availability because even with a failing internet connection, your Edge device that maybe is just executing a production order, or it's just doing quality inspections, or is just reporting back the statuses of a production order, that this is running independent on your internet connection. And when it reconnects that you can retake up the Cloud deployment or that the Cloud operations. And this has a huge advantage of also decoupling centralized site operations, so that you can run in your sites, in your plants, the most critical transactions on the application, but still have a true shop floor to top floor visibility from the cloud across dozens or even hundreds plus plants, which it makes it much easier to deploy these solutions, and much more in order to achieve a much faster return on invest. Rob, do you want to talk a little bit about how this architecture looks like? So what we have here, looking at the DMC edge. I think this is a great example of taking the portability aspect of one of the principles of the architecture.
It's portable because we can, as Dominik mentioned, half of the manufacturing execution, business process is now executed on the edge. It's not dependent on the connection. It will pull information from the cloud, but great example of being able to take this cloud process, have it run in the edge. And what you can see here from the architecture involves some components.
On the top right there, you'll see DMC, Digital Manufacturing Cloud, taking advantage in building upon our edge lifecycle management capabilities. There's a policy service that governs the applications, the life cycle of the app itself. And core to moving the data is the business objects [INAUDIBLE] service. This is really about moving the actual business objects that are created in the cloud. So as the order is executed, it is dispatched.
The edge components are made aware. And operators on the factory floor, by way of the edge appliance, by way of their production operator, dashboards that they see on their shop floor have access to information. So a really great example of a cloud edge scenario here working in tandem. And what you'll see in our overall architecture as things evolve, we've picked the execution scenario. This is a critical one when it comes to manufacturing.
But a lot of those scenarios that you saw in previous slides about the themes go beyond manufacturing execution. We'll see future enhancements on our edge, include things like analytics, pushing the data, the processing really down close to the machines, close to where the data rely. So it's really about data federation, so being able to access data, being able to take advantage of the data where it lies. In this particular case, we're looking at addressing manufacturing needs by allowing execution to take place in the cloud, but also giving an option on the edge.
And we look to our partners as was stated before by Dominik. In this great example, we have our Azure Edge Appliance that is a fully managed box that has multiple profiles, that has connectivity to the particular components sitting on the shop floor. Building on top of our Edge discussion on execution, again, looking at our Edge Services.
So the Edge Services component is what's delivering our business objects sync synchronization. But besides it's usage on Digital Manufacturing Cloud Edge, it also has a very nice spot in being able to connect to a variety of IoT devices. It provides additional services, so things that you need to extend those microservices and make portability from the cloud a reality into the edge, being able to deliver on a policy service, extend some of your core business functionality that exists in your SAP system. There's support for streaming per system.
And as I mentioned in the past, Custom Edge Modules that can be deployed to meet a variety of specific use cases. Moving quickly along on the path of Industrial Big Data Management. So that overall architecture had a variety of applications. We discussed multiple types of data sources. Well, really what's key behind this is how do we make and manage that data, and have it effective, and deliver it for the various stakeholders.
So what a data scientist needs may differ from what a business analyst needs, from what a shop floor supervisor might need. So data is really the key behind enabling these cross functions between the applications. So I want to shine a light now on our Data Lake Integration.
Our SAP IoT component delivers an abstraction and ultimately back to one of the core principles of choice. So a choice to store data in a fully managed data source within SAP. So we have a cloud service that allows our applications to build on that data that's either maintained by our IoT service. Or second option is something that you as a customer partner might have in your environment. So we are in our current version here offer an Azure IoT Hub, Azure ADX or Azure Data Explorer capabilities, which ultimately brings the choice of management of that data to your hands.
We have some products that were previously described in our solution blueprint that are currently available using our Data Lake Integration, things like enterprise product development, predictive assets insights. Both are available in our queue for 2020. So with that, that concludes the discussion on the Data Lakes. And really, I wanted to just wrap up this architecture section by going back to a couple of those key principles.
So as I've mentioned, what we saw with the Edge computing, what we saw with Digital Manufacturing Cloud Edge, with this Data Lake Integration, or discussion on Artificial Intelligence, really the ultimate takeaway, we look at the architecture and those enabling technologies at making the overall industry for now themes a reality. And I'm happy to say that in the years that I've been working on this now, this started as a targeted architecture. But we're at a great spot where we see this architecture now as a reality. It's a reference architecture and a longer target architecture.
And I think it fits perfectly with the tag line that we have as industry for all is happening now. So over to you, Dominik, for the customer references. Perfect. Thank you so much for the deep dives. Now, to close it out, I want to showcase a few examples where this reference architecture or parts of it have become a customer reality. And the first customer we've chosen for this is that INDEX [INAUDIBLE],, which is a very traditional German manufacturer of C and C production machines, so classic industrial machinery manufacturer.
And what they have done with-- you see here also highlighted the intelligent products theme. So they have deployed Internet of Things capabilities across their manufacturing machines in order to extract critical sensor and device data, so exactly what we've just discussed. INDEX is analyzing this huge amount of industrial data in order to achieve for their customers the next level of maintenance and service capabilities, so that they are able to get much, much better insights in the usage, in the failure codes, et cetera, of the machines that they have deployed at their customers. A key component to that is also our SAP Asset Intelligence Network, making sure that the data deployed at the customer site can be accessible, and that INDEX can provide maintenance instruction, service instructions, spare parts instructions to their customers.
There are many more customer examples. There are few more for your references here in the back that we're going to skip over now for the interest of time. In order to come to the wrap up. So we see a huge amount of customers that have been deploying Industry 4.0 capabilities
and especially this year, the year of let's say a crisis, where global supply chains have been challenged in their status quo, of internationally optimized supply chains. We see that the necessity to run efficient operations on the shop floor with your assets in asset operations and intelligence products has never been greater. So in wrapping up, you'll find that, and I think Rob already mentioned a couple of key highlights that we have a North Star architecture available that we divide or provide a Manufacturing Cloud Edge component in a hybrid landscape that SAP IoT and IT services are the complimentary services to integrate to device machine and sense of data, and that this is all in a part of a very open and interoperable architecture.
What I don't want to miss is please join us for two other sessions. So we're going to have an architectural deep dive with the team, looking deeper into our supply chain architecture. And Robert and I will also be available to ask any of your questions. So if now, during our sessions, you had a couple of question marks going up on your minds, please join us for the Ask The Expert Session. There's lots more in terms of content that you can read. There is a detailed technology white paper available on our website as well as a business strategy white paper that I really want you to take a look at and to have a glance through.
Takes you much deeper into what we've discussed in our session today. Closing up, continue to join our TechEd sessions. There's much more content.
So join us for more exciting sessions. And I'm saying thanks a lot for joining us today and talk to you soon. [MUSIC PLAYING]