Machining in the Digitized, Virtualized Future

Trends, by definition, are hard to trace. By the time an idea has taken hold with the individuals who pursue it, the circumstantial evidence is everywhere and all the new adherents want some credit. Big-stage events like IMTS are a good opportunity to see trends in action — but how can a prospective visitor know now what trends to be watching for in September.

“Smart manufacturing” is almost certain to be one of those ideas taking hold of IMTS attendees. Even as manufacturers are still preparing for the fully connected reality of the Industrial Internet of Things (IIoT, aka Industry 4.0), they should be prepared to make the next step to Smart manufacturing, the concept describing the full digitization of sensors, actuators, devices and components within a manufacturing system. In advance of a separate (but tangentially relevant event), AMB – the International Exhibition for Metal Working, September 13-17 in Stuttgart, Germany, Prof. Dr.-Ing. Christian Brecher, offered some insights on the emerging trend of manufacturing digitization and virtualization.

It’s already a fact that machine tools are becoming increasingly faster, more precise, and more efficient. However, as Prof. Brecher — who is the chairman of the Machine Tool Laboratory at the prestigious research university, RWTH Aachen University — has explained, the basic principle of the metal cutting machine is changing very little. While several rotatory and linear axes are combined differently within a closed housing, the control units are not readily accessible. The pervasive influence of IIoT means that machine tool functions must be made more open, more accessible, and more addressable.

So, what will machining look like in the Industry 4.0 future? “In our opinion, two aspects are crucial,” according to Brecher. “Digitalization or virtualization of machine tools and their networking.

“In the first case engineering will be substantially optimized both through meaningful models of mechanical, i.e. static, dynamic and thermal behavior, and control technology behavior (e.g. the drivetrain or control models),” the expert explained. “The objective here is to simulate the subsequent machine as far as the process and detect challenges at an early stage.”

Networking will have more of an effect on the following operating phase, he continued. “Future machine tools must contain semantic interfaces in order to provide, for example, process data in high resolution for more in-depth analyses, if possible in real time, or be functionally integrated in networked systems.”

What will be the effect on machine tools of the increasing levels of process automation, especially robotics? Brecher noted that automated production cells are already quite standard in several discrete applications, such as toolmaking and moldmaking.

“However,” he said, “we have identified major challenges relating to cost-effective operation of these cells (robots, machine tools, bearings) in multi-variant small series — meaning, the typical product range of small and medium-sized businesses.

“Processes often cannot come on stream in parallel with production time,” he said, “or the expertise required in this case is not available. To date, there have only been a few approaches to define a functionally extensive interface between a machine tool and a robot that can be integrated into the CAD/CAM-NC chain or the RC chain. This becomes very exciting when we consider flexible automation, e.g. by means of collaborative robotics. We also see great potential here for SMUs and small series.”

Brecher revealed that he and his colleagues are RWTH Aachen are currently establishing a working group to examine this issue, in both the research lab and via direct industrial cooperation.

And what has become of the previous intelligence on robotic work cell arrangement, i.e., the six-axis concept that only recently was considered the future standard for machine tool automation?

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