In modern times, digital business models are the fundamental differentiator of future competitiveness in Industry 4.0 and are becoming increasingly important. In order to better understand data-driven business models, the platform industry 4.0 provides a number of examples of why they are advantageous for the future.
For a smooth “just-in-time” material delivery, orders as well as participants musst be coordinated. Systematic data processing helps with this. Everyone receives the relevant information and a translation service prevents misunderstandings.
The collaborative use of data offers valuable insights to all parties along the value-chain, which can be used to optimize products and processes.
Farmers are highly dependent on weather and soil. Smart farming combines, for example, agricultural data with weather data in agriculture to be able to take timely measures against negative effects. Thus, product quality, quantity, and pricing can be optimized.
In viticulture, external factors such as the weather play a major role in determining the harvest yield. Through the analysis of past and current weather data, linked with the weather forecast, IoT devices support the planning and optimization of the vintage.
Mistakes and errors slow down production and cost money. How to prevent it? Wouldn't it be ideal to identify defects prior to production? “Frontloading” with digital twins can do the trick.
With consistent standards, Umati and the Data Intelligence Hub enable efficient data exchange in the industry.
Intelligent mobility applications require large volumes of data. An OEM that sources, analyzes and utilizes this data, has a good chance to stay competitive.
There are various dependencies between the players in beverage production. A roles and rights system prevents unauthorized access during the exchange of production data.
Intelligent networked machines improve the process chain and products in manufacturing companies. The Data Intelligence Hub makes Industry 4.0 possible.
With smart monitoring, service technicians can easily monitor machines and production processes and react earlier – the Data intelligence Hub offers such an analytics service.
Intelligent waste management means, waste bins equipped with sensors send their filling-level and geographical location. With this data, the ideal time for collection is calculated.