Production data is gathered with an open multi-protocol edge solution and linked to a new or an existing digital twin. Manufacturers are able to utilise the insights by visualising, forecasting, and optimising.
When the movements and attributes of raw materials, components or products are linked to a digital twin, it’s easy to, for example, visualise where the possible bottlenecks are, optimise needed resources, and identify vital factors for yield and capacity prediction.
Capture the reality with the most suitable sensors
Get real-time insights from rich sensor data
Control processes or give user feedback to enable end-to-end optimisation
Edge computing can make existing manufacturing processes more intelligent and autonomous. By moving computing closer to the edge of the network, for instance, to the production equipment, these automated manufacturing systems are now not only able to act by themselves without human intervention, but also to react and make decisions based on changes in circumstances.
Artificial intelligence, especially machine learning, not only enables the software at the edges to detect patterns in the data it receives, but also to learn about correlations between data patterns and desired outcomes. When we let a computer analyse data and draw conclusions, we can give it positive or negative feedback so that over time the software will more often draw the desired conclusions.
Learn how emerging technologies can reveal bottlenecks in the production process, enhance capacity management, and improve the predictability of your production.
Find out some of the most beneficial use cases for your business.