By Nikolaus Fecht
The days of traditional machining practices are over. "Without using digital data, it would often not be possible to supply tools in time," emphasizes Prof. Dirk Biermann, Head of the Institute of Machining Technology (ISF) at TU Dortmund University.
"It would also be almost impossible to continue developing high-performance tools effectively without simulations." He adds that these procedures also considerably reduce the amount of time and effort required for experiments.
Research departments often take on a leading role here, with the ISF currently examining how the interaction between cooling lubricants and chip formation can be improved by using 3D simulations.
According to Biermann, the leading companies in this area are often from the aerospace and automotive industries. And mechanical engineering is also benefiting from their pioneering work: "Even small toolmaking companies are already active in this area," observes the Head of the Institute. In five to ten years, mechanical engineering will therefore presumably tackle tasks which previously seemed impossible, also with the help of machine learning.
"We are currently in the very early stages of using new informatic technology methods. Training the specialist staff needed is one of the main challenges here," says Biermann. Informatic technologies students in Dortmund therefore also go to the ISF to work on machine tools. These unusual activities are primarily the responsibility of Prof. Petra Wiederkehr from the Faculty of Computer Science, who addresses the exciting topic of "virtual machining." "We were able to successfully implement this collaboration thanks to the many years of cooperation with informatic technologies," says Biermann. He continues: "Students of informatic technologies go to lectures to gain insights into processing on machine tools at an early stage."
Help from the cloud
Prof. Frank Barthelmä, CEO of the Gesellschaft für Fertigungstechnik und Entwicklung [Association of Production Technology and Development] explains how cloud and sensor technologies are used to optimize the supply of lubricants. "The production machines in small and medium-sized companies sometimes require different cooling lubricants," he says. "Each machine is therefore equipped with its own supply." Sensors transfer the generated machine data to a cloud, where the lubricant distribution is monitored.
The option of using a tablet to manually enter the target values of the cooling lubricant supply alongside the automatically recorded data ensures ongoing process control. Additional sensors can be integrated into the system to measure the room temperature or humidity, thus ensuring the holistic monitoring and control of the process. Therefore, automatic evaluation means that the user always has an overview of the cooling lubricant supply for every system. The user is also able to create trend analyses based on the recorded data.However, Barthelmä does have some reservations: "Even a self-optimizing machine tool can only work if it communicates both internally and externally. And the tool will continue to play a decisive role here."
Software as a Service
Open cloud platforms are also a helpful technological innovation. Mapal Präzisionswerkzeuge Dr. Kress KG in Aalen has established a start-up company which provides programs to manage data and processes using "Software as a Service" (SaaS) technology. "The administrative workload for tools and 'C' items in general is quite high," says Giari Fiorucci, Managing Director of the new Mapal subsidiary. "The actual machining process often doesn’t take too long, but ordering, planning and reprocessing tools, on the other hand, require a lot of time."
These tasks produce a lot of data and many users still manage them manually to a great extent. "A lot of the same data is used multiple times," says Fiorucci, who goes on to explain: "Despite this, everybody involved generates and maintains this data on his own. A typical example is the regrinding of tools." The SaaS cloud solution provides support here. The solution's programs manage the tools, bringing about collaborative data management between customer and supplier. Digital twins are created on the platform - along with all other parameters, such as cutting data. All authorized partners can then access this common data, meaning that no data set needs to be created multiple times. "Digitalization of manufacturing can only work if we also digitalize the management of the supply chains," points Fiorucci out.