Dispensing Technology – Enabler of Digital Transformation
RAMPF Production Systems has developed a new, universal user interface for dispensing systems and robots. The easy-to-use tool forms a key component in the digital strategies of manufacturing companies.
The digitalization and associated automation of production facilities are in full swing – and yet this is only the beginning. After all, we have by no means fully grasped, let alone exhausted, the potential of digital technologies to boost the efficiency, speed, and reliability of manufacturing processes.
With that in mind, s has developed a new, universal user interface for dispensing systems and robots.
Hartmut Storz, CEO of RAMPF Production Systems:
For manufacturing companies, this innovative tool forms an integral part of their digital strategy.
At the heart of the system are control solutions from Beckhoff Automation and Siemens. The software and hardware communicate via OPC Unified Architecture (OPC UA), which creates a comprehensive human-machine interface (HMI) that can be used with all RAMPF dispensing systems and robots.
The RAMPF HMI also serves as the basis for developing customer-specific HMI elements. This enables modular design and ensures reusability, thus significantly reducing the time and effort programmers have to invest on-site in customers’ projects.
Using this interface ensures systems can be connected to all standard mobile devices regardless of the platform, and the responsive design allows for universally adapted visualization, ensuring easy operation at all times.
At the same time, the low number of user levels makes for a simple, intuitive, and easy-to-navigate operating concept.
Alexander Huttenlocher, Director of Sales & Marketing at RAMPF Production Systems:
The new user interface is designed to support our customers’ digital transformation process and directly contribute to the optimization of their manufacturing processes. What’s more, we’re creating the ideal basis for handling future issues, such as flexible factories and predictive maintenance.