German filling and packaging systems supplier KHS has developed a new self-learning filling valve to optimise production processes and reduce time and effort in filling operations and machine maintenance.
“To date, depending on the beverage and container, around 20 different types of filling valve are used,” said Jochen Ohrem, an expert in research and development management at KHS. “The beverage industry is increasingly calling for versatile filling systems. Digitally networked line and machine systems are also in high demand.”
The development is part of a DnSPro research project. KHS and six other partners – Infineon, Wibu Systems, Epos, the Ruhr University in Bochum, Ostwestfalen-Lippe University of Applied Sciences and Krohne Innovation – worked to create an intelligent filling valve that can be used to fill all liquids into all existing types of containers.
“We developed cyber-physical systems for this purpose, with the help of which the valve can determine how to best fill a certain beverage into a certain container as quickly as possible,” Ohrem explained.
According to KHS, the filling process is analysed with the assistance of a camera. This continuously monitors the inclusion of bubbles and foaming to prevent excessive foaming and, therefore, product loss.
With the help of microcontrollers and the camera’s evaluation electronics, the filling valve is opened to varying degrees by a stepper motor depending on the fill level. “The focus was on ‘learning’ a number of skills: self-configuration, analysis, self-diagnosis and, ultimately, self-optimisation,” added Ohrem.
KHS now plans to test the prototype valve. Meanwhile, the company is developing ideas for its future use. For example, Ohrem explained that, instead of a filling computer centrally positioned on the machine that regulates the process of all valves, this task could be managed locally by miniaturised computers installed on each valve group.
This would allow a simple sensor such as a pressure sensor to be inserted into each filling valve which documents and analyses the pressure curve, resulting in a process which optimises itself of its own accord. “As less effort is involved in installation, this should yield a number of cost and time benefits, for instance during commissioning,” Ohrem concluded.