1. According to Interact Analysis, within eight years 30 percent of all robots sold will be collaborative. What does this mean for Schmalz?
A lot of work – in a positive sense. As the market for cobots grows, the need for new grippers grows alongside it. The International Federation of Robotics predicts that the number of end-of-arm tools sold will reach 1.6 billion Euros in two years. However, lightweight robots have a completely different set of requirements in terms of end effectors than conventional industrial robots. To ensure their lift capacity is not reduced too much, they need to be light but still stable. The smaller robots are easy to program and learn new tasks quickly. Users also expect the same level of flexibility from grippers – whether that means the ability to exchange them quickly, use them universally or configure and deliver them in the shortest possible time. And since the collaborative assistants work in the immediate vicinity of people, we also have to take safety into account while designing all our components, for example with regards to DIN ISO/TS 15066. Vacuum generators have to be integrated, as well as sensors and interfaces that can collect data and pass it on to the higher-level controller. These new features enable functions that increase efficiency and productivity such as condition monitoring and predictive maintenance, which users expect for their cutting-edge production facilities nowadays. The automation of customized production – which is an area where cobots have now become an economical solution even for SMEs – is the future and can work only through digitalization.
2. The flexibility and intelligence of individual components are two decisive factors that are frequently mentioned in the context of modern production. What effect does that have on your development processes?
There are many ways to give the user the right assistance with suitable solutions in an ever-changing production environment. One is to develop grippers that can handle workpieces that are not identical. For instance, our area gripping system FXCB/FMCB provides a gripping surface for cardboard boxes or components of different shapes, sizes and characteristics thanks to its flexible foam. Another goal is to allow users themselves to configure and even modify their grippers. Our modular systems for vacuum end effectors make that possible. We are now taking these developments one step further with the lightweight gripper SLG, produced in 3d printing: It, too, can be configured by the user, and we have developed our own engineering tool to do so. The starting point in this regard is always the handling task to which the solution must adapt – irrespective of whether it is flat or includes free-form surfaces. Since our expert knowledge provides the basis for the software, the user can put together the right gripper without any specialist expertise. In just a few clicks and – thanks to our additive manufacturing process – with a very short delivery time, the end effector is ready for operation. Of course, the simple commissioning of the end effectors is also crucial alongside their rapid availability. NFC interfaces simplify parameterization significantly, while IO-Link interfaces supply the intelligence at actuator and sensor level. They make the vacuum generators and grippers visible in the digital production environment and therefore increase the efficiency of the overall system.
3. It sounds like the course for the future is already set. What are the challenges?
Even though digitalization is a topic we’re now quite familiar with, there are still some issues to be resolved. One challenge is the subject of communication: each robot has its own operating system. Our grippers should theoretically be able to do anything. Therefore, one goal for the future is to enable simpler communication between grippers and the robot control system. Furthermore, lot of our attention is presently focused on the issue of how the collected data can be analyzed. The data only becomes valuable if the right information can be extracted from it – in real time where possible. Machine learning (ML) and artificial intelligence (AI) are playing an increasingly important role in this regard. We have already entered into the field of ML – with monitored learning processes for error classification in the vacuum system and regression models for wear forecasting for predictive maintenance. But that’s just the start. It gets really interesting when the grippers themselves can learn and therefore autonomously adapt to changing or unfamiliar workpieces. To do so, however, they need to gather more information, for instance, by connecting to a camera system. That is also important when it comes to separating objects that are supplied in a chaotic way, which requires hand-eye coordination. There is much potential for development here, too. As you can see, digitization has opened the door to a whole new world for us, which we are gradually discovering and exploring.