Today, public cloud systems can be used for outsourcing computationally intensive applications and storing large amounts of data. However, these systems are not designed for millisecond-accurate control of machines in production environments. They are not freely configurable and are difficult to connect to real-time-capable networks.
In contrast, companies can use local cloud systems to monitor their machines and plants and exchange sensor information. Now, the Fraunhofer Institute for Production Technology IPT presents the hardware and software architecture of the Fraunhofer Edge Cloud.
Fraunhofer Edge Cloud locations.
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In production environments, cloud technologies have not yet achieved widespread use. One reason for this is that many companies are reluctant to store their valuable machine and manufacturing data outside their own company. The other reason is that conventional technology is not capable of sending data back and forth in real time.
In most cases, therefore, machines and industrial robots are still connected via cables to the control center, which monitors them or switches them on and off. They only ever do what they are programmed to do and are generally inflexible. If machines are required to take on new tasks or manufacture new products, technicians usually have to head out with a laptop to install new software or design templates onto the machines. This is not what flexibility looks like. As part of a research project, therefore, Fraunhofer IPT has developed a cloud solution tailored to the needs of the production sector — the Fraunhofer Edge Cloud, which can control the production process on site at the factory or at several locations at the same time. Unlike the conventional global cloud, the Fraunhofer Edge Cloud keeps the data in the hands of the production companies.
"An edge cloud like this is beneficial for companies in a number of ways," says Pierre Kehl, an expert in edge cloud solutions and Group Manager for Digital Infrastructures at Fraunhofer IPT in Aachen. “For example, it allows entire machine parks to be controlled securely and quickly using centralized software. If the machines require updates or new software versions, these can simply be installed centrally. That saves the technicians on site from having to do a lot of running around.” Kehl also explains that the machines are able to send their current operating parameters and sensor values to the edge cloud. The Fraunhofer project team is currently developing, among other things, intelligent analysis software that detects conspicuous vibrations, which can give indications of impending damage. In this way, a fault on a milling or grinding machine can be detected before anything untoward happens.
Thanks to the fast mobile communications standard of 5G, all of the necessary data can be transmitted between the cloud and the machines in fractions of a second. Time-Sensitive Networking (TSN) is also used to send data in real time. This allows swift work processes to be controlled securely and centrally from the cloud. The benefit here, once again, is that changes to the production parameters can be transmitted to the machines via the cloud.
Fraunhofer IPT offers small and large companies that are interested in an edge cloud solution the opportunity to develop and simulate application scenarios with the aid of the Fraunhofer Edge Cloud. "This allows companies to test the potential that the solution has for their production environment in a secure setting without having to invest in edge cloud technology right away," says Kehl. One of the development partners is the company German Edge Cloud, which provides the technology – for example, adapters for retrofitting, which enable the machine controller to communicate with the cloud via 5G and TNS. The software solutions, on the other hand, come from the Fraunhofer institutes that are involved in the project. The fact that companies are able to collect data centrally in their own edge cloud also offers them the advantage of being able to use the information for other purposes – for example, to optimize production or to make processed data available to others. Machine manufacturers, for example, may have an interest in learning more about how their machines are performing at their customers’ sites so that they can refine their technology.
COMPAMED-tradefair.com; Source: Fraunhofer Institute for Production Technology IPT