Grupo Siro Embraces Industry 4.0 with the IoT and Machine Learning | SAP TechEd in 2020

Grupo Siro Embraces Industry 4.0 with the IoT and Machine Learning | SAP TechEd in 2020

Show Video

Hello, everyone. My name is Elvira Wallis and I'm responsible for Internet of Things at SAP. It will be my pleasure today to speak to you about Internet of Things use cases and in particular the implementation of Grupo Cerealto Siro and their specific way of implementing Internet of Things. Therefore, I would like to introduce and hand over to my co-speaker. Juan, would you mind introducing yourself? Hello, everyone. Thanks Elvira for the invitation to participate with you in this important event and to share some of the lessons that we have planned in the prior year of implementation.

Wonderful. Your audience, I will start out by outlining SAP's Internet of Things strategy and positioning, followed by walking through how the Internet of Things enables Industry 4.Now and in particular, what does Industry 4.Now mean with a couple of use case examples and then we hand over to Grupo Cerealto Siro. So with that, let me take you on a journey. Internet of Things and business processes.

What is it all about? When we are looking at bringing real world data, Internet of Things data into the enterprise, there are a number of technology enablers. Of course there is cloud computing, there is Internet of Things itself of which many aspects are running in the cloud and there is of course also Edge computing, meaning the processing of data right where it occurs. All of that data is brought together. It is integrated between IT and OT to horizontally integrate business processes across the enterprise.

There is the aspect of intelligent assets, intelligent factories, intelligent products and the empowered worker and so let me walk you through some of the examples that we have here. When we are referring to Industry 4.0, we also like to say it is about Industry 4.Now,

meaning the time for digital transformation is now. Whether it is about cloud processed data or data processed at the Edge and there are several aspects to it. It is about intelligence assets that are set by real world data. It can be intelligent factories, intelligent products, or the empowered people and let me walk you through a couple of examples for each of these. Let's start out with intelligent assets.

When you're looking at the asset space, it is all about understanding the assets health and handling data centrally to achieve higher uptime and efficiency. For what purpose? For increased asset lifetime. That is what it's all about.

Whether it is about anomaly detection, product replenishment, dispatching field service or predictive maintenance. It's all for the purpose of increasing the asset lifetime. Let's look at the area of intelligent factories. A Smart Factory ought to be adaptable, it ought to be agile and decisions need to be taken right there in real time on the shop floor, that means at the Edge where the data occurs. So SAP IoT runs business processes at the Edge or applies it in the cloud and the key here is to apply business logic already Edge, at the Edge where the beta occurs on the shop floor and then by aggregating the data in the cloud, there's multi-factory visibility and it allows really for real time processing, increased availability and manufacturing excellence.

Let's look at another example. Intelligent products. In this case, the enablement that an Internet of Things brings about is about being able to design and being able to service intelligent highly customized products and for that, you need to have embedded technologies. SAP IoT connects the product usage data in order to enhance the customer experience. Whether it is about remote monitoring, whether it is about product or service or simply use a tracking and insights to then have later on a better delivery Instance and finally, let's not forget to empower the worker. Let's give employees the tools they need to do their job effectively.

Ultimately increasing reliability and worker safety. So let's look at the use case here. The use case will make all of what I've just mentioned very tangible by putting it into the context of a real life story. Our story here starts on the left side. Let me introduce you to Amelia. She's the production planner at the company.

Let's say at Pharma Limited, a chemical company, and for the production process, Amelia needs control of the flow of her liquids. She orders valves from a valve manufacturer. Now during the shipping process from the valve manufacturer to Amelia, Amelia can use real time insights provided by SAP IoT enabled delivery insights in the context of S/4HANA.

Why? Well thereby, she receives data about the expected delivery date, the geographical location and current health condition of her valves. For example, she can see if any sudden shocks or drops happened that could affect the product quality of the valves. Now let's go one step back and let's look at the valve manufacturing. In the past, the company only process the mechanical parts like the body, the bonnet or trim and the packaging of the valve. In contrast today, the manufacturer connects these mechanical parts with Internet of Things sensors. This enables the valve manufacturer to offer a completely new customer experience and a completely new customer offer.

Namely value added services, which open up additional revenue streams for the company. A smart valve manufacturer is also using Internet of Things technology in its own production. For example with SAP Internet of Things enabled Kanban. IoT-enabled Kanban helps to assure that the required material is available during the production process without disruption. At the same time, it helps to make sure that the material is only provided for actual demand.

In this way, the valve manufacturer avoids over stocking and wasting money. IoT-enabled Kanban is used to replenish sensors from a sensor supplier and the mechanical parts from a mechanical supplier just in time. Now, let's look at enterprise product design. Our second path starts with the production process of Pharma Limited on the left side of the picture. The valve manufacturer can now leverage data from the sensors connected to the valves of Pharma limited and many other customers and by that, detect potential pain points of the product. In other words, the valve manufacturer can see the specific kind of valve in a specific environment as a specific ethic and specific time and this knowledge enables important engineering changes of the product.

For example, detecting frequently occurring issues with the sealing off the valve. In this case, the manufacturer needs to think about ways to improve the ceilings. Bank's still using SAP Internet of Things. This engineering change management happens fast and reliably. It helps the valve manufacturer to consistently improve the products so that customers get what they need and also when they need it.

Now let's look at the maintenance aspects. Our second path starts again with the production process on the left side the picture. A maintenance service team is currently working on a valve that has a defect. Luckily, the maintenance service was triggered by the valve manufacturer before it could have cost a production downtime.

Why? That is because the valve manufacturer had already known that this defect could happen before it happened. Such a service is called predictive maintenance and service and SAP predictive maintenance and service enables the valve manufacturer to monitor the conditions of the valves. That way, it helps to estimate when maintenance should be performed. Thereby, saving costs and time because tasks are performed only when warranted.

In order to avoid production downtime and the high costs linked to it, Amelia used to be able to rely on impeccable performance of the valves and to guarantee this performance, the valve manufacturer needs to rely on real time data. However, in case of very high latency, this performance can be a challenge. Now how can we solve this latency challenge? In order to solve it, SAP provides SAP Edge services, which enables the processing of data close to the source of data.

Intelligent technologies continue to evolve and that allows real time processing of sensor data with low latency at the Edge. Meaning, the business process can run at the Edge. Now this in turn helps run autonomous decision making and analytics securely at the location where the data is generated and sent data only selectively to the cloud. And one valve for Pharma Limited, a mechanical part needs to be replaced and luckily, the valve manufacturer always has enough spare parts in the plant's automated warehouse. Why is this possible? This is possible because of Internet of Things enabled replenishment.

IoT enabled replenishment enables real time visibility into materials stock levels and ensures higher stock availability. In our example use case here, it automates the replenishment process or spare parts without manual human intervention. The sensors are replenished from a sensor supplier.

As I walk you from the series of use cases, you could see the ample applications in intelligent factories, intelligent assets, intelligent products of Internet of Things in the context of Industry 4.Now and after the series of examples, I would like to hand over to Grupo Cerealto Siro and Juan will walk you through this implementation. Enjoy the story.

Thanks a lot Elvira. First of all, I want to give a little explanation of our company, Ceralto Siro. We are a multinational company in the agri-food sector in Spain and we are specializing development on manufacturing cereal based products, specializing in the category itself biscuits, breakfast cereals, snacks and pasta.

We have a deep knowledge of our customer and we rely on products that respond to the different nutritional needs with a higher level of innovation. We have to bar both. We cultivate dreams to notice more people every day. It's the science of our daily life because we want to reduce the amount of people without food. To get this propose, we have three strategic levers. One of them very related with Industry 4.0.

One is the growth, the growth of the company in base of the knowledge of our customers and the other side is the culture and the leadership, empower the people and the middle is the operations of the company, the factories. The factories have five edge and one of them is industrial zero, technology. How can technology can help their factories to produce better, to produce safer and to produce more effectively. We think we are convinced that technology is an enabler in the generation factory senses and values in all the process and organization, not only in office, but always in the factories. The factories have a big improvement option with the IoT, with their technology and we think that that is all reality. We need to learn three parts of in this kind of projects.

IT, because IT has the knowledge of the cloud, of the new technologies, of these kind of things. OT is the owner of the factory. It's the person who knows how can get to the fact, to the line, to the device and cyber security, to protect all the system. These three areas should work together to achieve the efficiency and in this project, was working together to get it.

We can see some figures of our company. One of them is very important for us in relation with this project because we are in several, in five countries with 16 factories and we need to create an extra day of the IT of Industry 4.0 that should be managed and governance from Spain and should be easy to development, rollout to all over the countries and we think that is one of the things that SAP can help us to do this strategy. Some part of our clients, two kind of clients, B2B and Retail. We are specialist in manufacture our products or their products with our, in our factories is our company and these are some of our products. Here are some of these products that should be in your breakfast, in your meal and is our more responsibility to put this products in your kitchen every day with the best quality and the best price possible.

As I said, technology is very important for us not only in factory but always in factory. So the idea is to go in 2015, we development a project called Paperless Factory with SAP, with SAP product and in this project, we introduce the operation, in the operation floor of our factory SAP, S-A-P. It was an award project and this project gave to the company one thing, to see that SAP is can be a functionality, enough functionality to manage all the information in a factory, in the front of the factory. Not only as an ERP, it's always on financial system, now is for a factory production and manage all the information about it. The ability, orders, check process and this transform our factories. It was a process of legalization, a retired paper and the process of started to change our company.

But it's not 4.0 project because within that information comes from the machines to the device, to the SAP, in this case, through a person, not directly. In this moment, we start our vision of Industry 4.0. How can we capture the information of our machines, very different machines but different lines not more than machine in the one case or that years but not always a machine that can, has the connection by herself by default.

And should we think that would be fantastic for us to take the information from the machine to SAP directly, to our factory, for Paperless Factory. When we talk about technology SAP which is how our panel in this journey. We know SAP a lot.

We have been working with SAP a lot of years. We share good things and a lot of good things but SAP we think that can help us in this project because our main information was seen in SAP, in our ERP and we need that tool to transform the information from the machines or to gather information from the machine to our SAP and SAP with this technology, with IoT technology can help us or could help us directly. But in the journey arrive to Industry 4.0, we seem to have three stage.

One of them is the connectivity. How can we connect to the machines in our situation, with different machines, when all machines and sometimes not machines that come being connected and this step, with this goal was achieved with the project, with this project and is something good. There are other two things talking about industrial 4.0. The big question is to identify what is information that they need to take from the machines, what I need to listen and why I need to listen to this information? What is the purpose to get this information to transform it? Because if not to answer this question, the project will be very difficult to transform because the first question is a technical project. Very important but that is something that we have solved with SAP, but the other second question this two question is something that we need to answer at this moment. And this two, the third question or third stage is the predictive and putting value on the data.

OK, I have the data, the cover data I need to put in value and give business outcome for the project. With one slide, it's similar to this. We are starting the project. We identified what was the machine that we need to, that we want to connect.

In this case, it was a machine to produce cereal based, lot of cereal per minute, thousand, hundred, hundred. But identifying what will be the business necessity that we need to cover with this solution. Identifying problems of quality that we could be solved getting information. Thinking in the last part to offer information to the plants and how can reduce prevalence of quality in a predictive way. It was the dream.

The problem of connection of it towards is the first challenge. How can we need to connect to the machines. Machines that are isolated, different brands, different problem.

We need to be fine in the first part of the project on a standard of information that we see on the system. This is done, that should be easy to deploy in all their factories is easily and we need to define this framework to work with the data and there are other thing that was important for us. We have all our factory information in our Paperless Factory in SAP and the assistant to start to board with Industry 4.0 should be easy to connect our transactional data, our data in SAP with the data that we get from the machine, of the machines. So this was something that we need to put in value from this first moment.

How can I get information of this line and a line or join with the number for that we are producing. To get these, we deployed this architecture. In the first part of the slide, we have 4 machines, different machines of the factory. One more older or over newer, newest and we have the system where do we connect this machines, Edge service. This server is on-premise in our CPE and with this server, we plan connectivity.

We can connect easily data from these machines. Through ethernet connection, we can get information in real time of these machines, different parameters, different things of the machines. We can see in the next slide some information. With this server, we can send information easily to the cloud, to sub IoT to start getting information in this cloud and start to the next step, prepare the data to join with ERP. In some cases, we can send information to the ERP and in the other side, we can add information of the ERP through the platform of cloud, cloud connector, all that other pieces of software that are in the cloud platform. One thing that we can do with this information, one more thing is through SAP Cloud Analytics, we can deploy easily several dozen of works with this information.

Here, we can see different protocol, so different ways in how we can get information for our teams and the weight there. We can get information through the P protocol in the model. Another machine is a camera and take picture of the bar, cereal bars. We can get information through multiples more easy protocol, more than protocol. They can get more than 3,000 measure per hour.

A lot of information about our bars. If we see all that additional machine, all the machine without connection by the default, we can get information, connection with a data directly connection through the PLC and gather information in her memory. Or in the other way, in the other machine, gather information through a connection by Telnet, different way to get information. So we have one system, one central system that allow us to get information from different machines. A press goal of the project workforce of course get positive. And in the right of the slide, we can see the different functionalities that allow us to make that service.

Not only get information, that is our main goal. Give value to the information on the Edge, in our plant, in our CPD. A filtering or other things that we can do with this information. Another thing that's important for us if we lose the communication with an internet, our at least server can buffering the information and avoid to lose information. So with this architecture, with this system, we can get connection easily to our machines.

Now we are doing some, several last words, some application to put the value, to put the information in value for the company. To answer the question in the factory access, I need information of these machine. How can I get information? Yes, we can show this information through this application. Really that works. And the factory can get information, can get the value, it's value OK.

The future of vision of this project. Well we have solved the first part of the project, how can we connect machines, how can I get information. The issue would be the first stage to answer this four point. How can we abort effectiveness, efficiency to the factory, how can this data allow us to detect in an early way a quality problem, quality uses and applying machine learning, how can be predictive with the problems, how can detect patterns of issues and solve problems in the first part of the line not when the product is near to finish and at the end, is reduce or another way is reduced manual process that now we are doing.

We have, we take a lot of data of quality in the line. Least data can be taken automatically with these process. And these are three learnings, the three important learnings that we have to get in the project. One of them is OK, SAP is a good partner for this project.

SAP can help pass a to get information, to deploy Industry 4 0 projects. Help platform, all their platform is good, it's enough and it does allow us to manage the connection with the machines. Allowed to manage with, not only in the front of the plant getting the information, we can add value with a SAP Cloud Platform with different pieces of software that there are in SAP Cloud Platform. In the second point and very, very important in this kind of project is necessary, it's mandatory to involve the plant in this project. It's not an IP project because it is a for the companies operate for the plant and ITs enable to offer to the project and other point is identify the first moment or as soon as possible what are their needs, the information that the plant needs. The machine that you need to connect and get information and putting value as soon as possible to the team of the plant to solve some problems because if we offer a quick win, the plant will be more involved in the project.

Thank you very much for your time and we will continue working with technology to help us to fulfill our purpose. We cultivate dreams to notice what people every day. Thank you very much. Thank you for your presentation, Juan and with that, I would like to introduce to you further learning experiences you can enjoy at SAP TechEd in 2020.

Check out the links below, take advantage of all the learning opportunities and thank you very much for your attendance and definitely enjoy what you can find on the Learning Hub. Thanks for attending the session and we hope to meet you in another session.

2020-12-23 12:20

Show Video

Other news