State-of-the-art software systems and the possibilities they offer in the context of digital networking are playing an ever greater role in mechanical engineering. Systematic use of the digital twin paves the way for sustainable, cost-effective manufacturing by maximising production, energy and resource efficiency. Condition monitoring gives end customers the link they are looking for to the world of digital production.
With Eplan and Rittal to the digital twin
Grab this opportunity to stand out from the competition and get fit for the future with the latest solutions from Rittal and Eplan.
Our performance promise:
- Thanks to high-quality data and accessibility to all system components in the EPLAN Data Portal
- Thanks to end-to-end engineering with intelligent software solutions from Rittal and Eplan
- Thanks to perfectly coordinated value-adding solutions – from engineering and sourcing all the way through to manufacturing and operations
- Thanks to fast, plausibility-checked product configuration with the RiPanel
- Thanks to efficient production planning with RiPanel Processing Center
- Thanks to the digital equipment and system documentation with ePOCKET
- Thanks to our intelligent modular system architecture comprising enclosure, power distribution, climate controle and IT infrastructure
- Thanks to global usability with standard-compliant, tested solutions and approvals
- Thanks to the availability and fast delivery of series products from stock
- Thanks to Rittal climate control solution with up to 75 per cent lower energy consumption and maximum flexibility as a result of multi-voltage capability.
- Thanks to the development of standard-compliant IIoT solutions for networking machinery and equipment such as smart sensors for enclosure monitoring.
- Thanks to smart service concepts for boosting system availability and service efficiency that are fit for the future.
- Thanks to Rittal Edge Data Centers for Industry 4.0 applications
- Thanks to real-time, AI-based edge data centres from German Edge Cloud for processing industrial data