Industrial Edge: the optimal technology mix
The advance of digitalization is bringing countless benefits to business and society, but at the same time is presenting new challenges in dealing with the huge volumes of generated data. When processing this data, edge computing offers enormous advantages to manufacturers and is evolving as a technology of the future.
Basically, edge computing means decentralized data processing at the edge of the network. Although the term “edge” is increasingly being used in the context of industrial production these days, many companies are still not sure how they can fully exploit their potential with the technology. Some may not even know what the word means.
Podcast: Edge Computing - more than a hype!?
The new podcast series "Talking Digital Industries" for technologies and trends that drive industrial enterprises. In the first episode Moderator Chris Brow is joined by three Edge enthusiasts discussing how Edge Computing will bring about a renaissance on the shop floor.
The accelerating spread of digitalization and related Industrie 4.0 are affecting our private lives yet having an even greater impact on companies. This is presenting challenges to the processing industry, such as ever-shorter innovation cycles and the increasing individuality of products and production processes. In order to master these challenges and remain competitive, companies must be able to react as flexibly as possible to changes. Fully networked production and fast processing of the generated data are essential here – and this is where edge computing comes into play.
Whether it handles data locally, centrally or via the internet, each company has its own strategy for recording and processing production data in order to improve processes. One must keep in mind, however, that data volumes in industrial production are enormous. Thousands of bits of information are generated each second in a production plant: A large number of sensors continuously measure key production parameters such as the condition of the machines and the quality of production. The more extensively a plant is networked, the greater the volume of generated data, whether at a given location or worldwide.
The best of two worlds
Companies that rely on local data processing soon reach their limits. That's because of the numerous different systems that are difficult to harmonize, but also because they lack the computing capacity for processing data on site, and company-wide, global processing is not possible. But the alternative of cloud computing also reaches its limits in specific applications, due in part to massive volumes of data, legal regulations or latencies. The difficulty here primarily lies in the need for real-time processing, since every second counts on the production floor. Data transfers to and from the cloud may not be fast enough. Moreover, sending large volumes of data to the cloud for processing requires a high bandwidth – a costly matter, especially for smaller companies.
A combination of local data processing directly in production, down to the automation level, and processing in the cloud can be the optimal solution here – and open up enormous potential for industry – especially in the area of smart manufacturing. This combination gives manufacturers the opportunity to take full advantage of the cloud, while still meeting market demands for maximum flexibility and responsiveness. When large amounts of data are processed by edge computing, a company’s storage and transmission costs are reduced – since only relevant data is transferred to a cloud or IT infrastructure.
No reason to hesitate
Some manufacturers may have concerns that edge computing is possible only with expensive investments in new automation systems. But the technology should in fact be seen as a supplement to existing equipment. With Siemens’ Industrial Edge, edge data processing devices can simply be connected to existing automation systems, fully integrated with them, or delivered with the systems themselves as a standard component. As a result of this flexibility, implementation costs should no longer be an issue, not even for SMEs. Moreover, edge technology also enhances automation systems by adding data analysis capability and other features to take full advantage of the IIot while increasing production flexibility and efficiency. By using a software standard docker, Siemens relies on the platform-independent scalability of applications and thus ensures maximum flexibility and futureproofing.
Edge as well as cloud computing are becoming increasingly important for a growing number of processing industries. The most sensible strategy, then, is to utilize the best of both technologies, since they optimally complement one another. By combining both technologies, data processed by edge computing can be used in the cloud to train AI algorithms. The resulting findings can then be downloaded back into the edge infrastructure, making possible an ongoing optimization of the entire manufacturing process.
Smart manufacturing does not simply mean collecting vast amounts of data with the help of sensors. Far more decisive is the ability to use that data to automatically generate information that helps improve production results. This, in turn, depends to a great extent on high computational and processing capacities located in both a central site (cloud) and on the periphery (edge).
Cloud services undoubtedly offer huge benefits. By analyzing data in a cloud, new insights into a production process or machine can be gained, leading to greater efficiency and availability. Transferring all data into and out of the cloud, however, is time-consuming and in some cases not practical, since every second and minute counts on the factory floor. Manufacturers must have the capability to quickly and securely analyze and utilize data to improve their production results.
With Industrial Edge, Siemens offers a solution for edge computing that includes the required hardware and software. Edge devices enable manufacturers to locally process their production data. This system can monitor all connected devices, install and update apps and software, and transfer functions from the cloud to the local manufacturing system.
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