Smart Edge Analytics

What is Smart Edge Analytics?

Collecting data is an essential part of Industry 4.0. However, storing and evaluating it is very time-consuming and resource-intensive - even though much of the data collected is not even used later. Smart edge analytics offers a time- and cost-saving alternative here: Instead of collecting all the data collected from machines and systems unfiltered and uploading it to the cloud or sending it to an external data center, for example, the first evaluation is already carried out directly on site - at the edge of the network. This not only enables cost savings in the forwarding and storage of data, but also increases the ability to act and production stability.

Data evaluation directly at the machine

Use Cases for Smart Edge Analytics

Machines, systems and sensors continuously collect data during the production process and evaluate it automatically. As a result, deviations in process stability and machine capability are noticed immediately and can be remedied without delay. For separate storage, only the data that has real relevance is passed on. Thanks to a programmed algorithm, Smart Edge Analytics recognizes important data and sends it on for storage, while irrelevant data is deleted immediately. This saves time and storage resources.

Extensive analyses of production trends and forecasts, as well as the condition of machines and equipment, allow maintenance schedules and production conditions to be customized. This results in lower maintenance costs in the long term. Breakdowns can be better predicted and averted in advance through targeted measures. This improves production stability, saves time and resources, and prevents costly downtime.

Real-time evaluation of data directly on the machine itself makes it possible to react faster and in a more targeted manner in the event of an emergency. Abnormal production conditions or results are detected immediately and reported to the operator without delay. For example, wear parts can be replaced preventively. Depending on the programming, the output of the respective machine can even be automatically reduced or adjusted if necessary. This prevents downtime, supports production stability and prevents expensive production errors.

Prerequisites for Smart Edge Analytics

In order to benefit from the advantages of Smart Edge Analytics, entrepreneurs must first invest in the appropriate hardware. This includes, for example, camera equipment, lighting units, PLC edge gateway and communication interfaces. During a detailed consultation, our experts will be happy to explain how Smart Edge Analytics can also be implemented in your company.

Advantages of Smart Edge Analytics

Transparency

Real-time data collection and analysis allows production problems to be identified immediately and communicated to the operator.

Reduced Maintenance time

The evaluation of trend analyses helps to identify the actual maintenance needs of machines and thus introduce realistic maintenance schedules for maximum time savings.

Zeit-Kostenersparnis

Thanks to the avoidance of maintenance support, significant time and cost savings are possible.

CO2 reduction

Because data is evaluated for relevance directly on site, excessive storage of irrelevant data volumes and the associated consumption of resources can be prevented.

Data security

Since data no longer has to be routed to an external data center or uploaded to the cloud in order to be analyzed, data security is noticeably improved.

Analysis

Businesses in rural areas where there is limited bandwidth available for data uploads can still get reliable data analytics thanks to Smart Edge Analytics.

FAQs about Smart Edge Analytics

For whom is Smart Edge Analytics worthwhile?

Smart Edge Analytics is worthwhile for all manufacturing companies that want to ensure production stability, optimize data use and security, and reduce maintenance times. Smaller companies in particular can also benefit from real-time data analysis.

Why can Smart Edge Analysis improve data security?

Without smart edge analytics, gigantic data streams are usually forwarded unfiltered to external data centers or uploaded to the cloud. This creates a data security risk per se. This is limited solely by the fact that far fewer data needs to be transmitted thanks to smart edge analytics. For these, in turn, special encryption mechanisms can be developed so that data misuse becomes impossible.

Richard Stegmann Digitalisation

Your contact person:

Richard Stegmann
Manager Digital Solutions

Do you have any questions or would you like us to send you an offer? Then simply send us your request!

 

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