Machine learning, autonomous agents, and engineer-to-order processes with 3D printing will feature prominently in SAP’s Open Integrated Factory at Hannover Messe 2017.
Away from mass production to ever smaller quantities and more individualized, increasingly autonomous manufacturing — these are the aims of the Open Integrated Factory, which SAP demonstrates in a showcase at this year’s Hannover Messe.
SAP’s Ralf Lehmann, senior director of Solution Management, Digital Manufacturing, explains the concept: “The customer configures the product at home, and the processes are fully integrated with the production processes, so no one at the factory needs to type in anything at a later stage. Integration gaps become a thing of the past.”
In other words, manufacturing becomes one seamless flow.
IoT: You Can’t Create Value with One Thing Alone
The Internet of Things (IoT) shouldn’t be seen purely as a means of analyzing mass data. To really tap its benefits, it should be dovetailed with business processes. “It’s not enough for a sensor to communicate with the network,” explains Rüdiger Fritz , director of Product Management for SAP Plant Connectivity.
The IoT only proves its worth when actions result from the data gathered: “The question is not how you bring together individual automation cells, but rather how you create value from the information – how you control a machine or optimize production.”
Communication Between Things and IT: Three Patterns
The world of the workshop transcends the world of the things themselves. That’s why communication between things and with the machines and processes is so important. Fritz identifies three communication patterns:
- Notification: A machine or component gives information to an application in the cloud.
- Query: The application in the cloud needs information and asks specifically how the “thing” is, whether it’s working reliably, or whether action is required.
- Reaction: An event happens that needs a rapid (and preferably autonomous) solution. For example, a tray on the production line is empty and requests a new order. In communication with incoming orders, the tray is assigned a new task – with no human intervention. In this case, the instruction is issued by the “SAP layer,” which “speaks” with autonomous units such as the tray. “We break the installation down into individual service components and then orchestrate these possible services,” Fritz says, explaining the approach.
3D Printing, Machine Learning, Autonomous Agents: The Three Innovations
This orchestration approach also means new technologies can be integrated more flexibly. For example, 3D printing can be embedded into the end-to-end processes, quality issues in production can be identified and addressed with the help of machine learning, and autonomous agents can make decisions on their own.
Engineer-to-Order with 3D Printing
The end-to-end process from the customer’s order to the delivery of the product can be interrupted to, for example, cater to a customer’s individual wishes. Any structural changes to the product will require a visit to the CAD workstation. This is what happens in an engineer-to-order process. It’s important to note that the data from the design program is not only converted into STL files that a 3D printer can handle. 3D printing is also incorporated into the end-to-end process chain as an additive manufacturing process. “Everything’s linked up,” says SAP expert Lehmann. From the first sketch to manufacturing, the process or document chain remains unbroken.
Machine learning is particularly useful in quality management. By analyzing the sensor data from the process, patterns can be found that always occur before a quality issue is identified. For example, if vibrations are detected in returns, it is now possible to weed out the product during the production process – as soon as the pattern is detected – rather than wait until the product is finished and ready to be collected by a robot. “Vibration patterns and product characteristics can be combined,” Lehmann explains. Machine learning helps pinpoint defects in good time, be it by knowing the right default settings to select for screws or figuring out what the product in the rotary feeder should weigh.
Let’s assume that a product requires manual finishing, and that this is part of the regular work process. Up to now, the SAP software – SAP Manufacturing Execution System or SAP ERP – decided where this finishing should take place. But in the future, these “resources” won’t be precisely defined, because this job will be assigned to an autonomous agent. In the showcase, this is a Raspberry Pi, a single-board computer the size of a chip card. It negotiates with the resources, makes decisions with them about where the product should go and informs the “mother ship,” as Fritz calls the SAP software. “Using edge processing, we outsource individual decisions and thus take the load off the cloud, which just stipulates the general direction. Processes become more dynamic and more flexible,” he says. It’s the first step toward swarm intelligence in the production process.
The Open Integrated Factory’s Product: SAP IoT Simulator
To experience the Internet of Things in this largely autonomous manufacturing process, SAP developed SAP IoT Simulator, which measures temperature, air humidity, position, light intensity, vibrations, and magnetic fields.
“SAP IoT Simulator is a physical device individualized by customers before manufacturing starts. It can be, for example, blue, orange, and green, with or without screw joints. It connects with a personalized smartphone app immediately after manufacturing,” explains Kai Wussow, head of Digital Transformation and IoT at SAP Digital Business Services.
The sensor data that the hand-sized device measures is continuously transmitted to SAP Cloud Platform, which raises the alarm through a smartphone app as soon as certain threshold values are exceeded.
According to Wussow, “SAP IoT Simulator is one example of how we at SAP Digital Studio make the digital transformation and the Internet of Things come alive for customers and — together with them — develop strategies and prototypes.”
SAP IoT Simulator: Create Your Own IoT Scenarios
SAP IoT Simulator contains some inbuilt scenarios such as the “beverage vending machine” smart product and the scenario for indoor environment quality. If the air is too dry or the temperature is too low in the office, the app issues an alert. Using their imagination and according to their business requirements, customers can decide for themselves how they want to use the connected sensor and analysis capabilities.
The app gives customers guidance about developing their own scenarios based on threshold values and their own rules. It even provides 62 IoT business model patterns, including IoT-specific business models such as object self-service, where coffee machines order new coffee when supplies are running low, as well as condition monitoring.
“This is a fun way of introducing customers to the basic principles of the IoT and enabling them to better understand how the IoT can transform their business models, products, and processes,” Wussow explains. All you need for this is SAP IoT Simulator and its smartphone app, which continuously analyzes the data and monitors parameters. It’s that simple.