With all the current challenges, concerns and forecasts for German production and logistics, what will the German industry look like in 10 years' time? Can we turn things around? In part 3 of our exclusive expert interview, Prof. Dr.-Ing. Johannes Fottner, University Professor of Technical Logistics at the Technical University of Munich, takes a look into the future.
Missed the first parts of the interview? Here you go:
Click here for part 1: The 3 biggest challenges in production and logistics
Click here for part 2: How logistics and production will benefit from AI
Maurice Brodhun: With all the opportunities and possibilities - what would you say 5 years into the future, what relevance will AI and AI robotics have in production and logistics?
Prof. Dr. Fottner: "I would like to start on a positive note and say that I think we sometimes underestimate a little how far we are already using it today. I'm always a bit conservative and cautious, because we've already achieved it quite often. Even with AI in the 90s - because we demanded far too much from the new technology - the level of disappointment was so high that the technology died as a result. That would be a shame, because the power of this new technology - which includes AI - is already enormous. If we look at where we use it today, in some adaptive cruise control systems we work with image recognition, so we recognize what's going on and also recognize how it changes. That's the first step. Today, we have safety systems in intralogistics, in forklift trucks and many other areas where we can differentiate: do we now have a "target" here, which is a person, where we have to warn at a very early stage? So we are already taking a very good approach here. Pattern recognition in particular, recognizing articles, where do I have to reach, that's all already a use case for AI.
We still have a nice topic in logistics, the so-called "mixed case palletizing" problem. A mathematically unsolvable problem of picking and packing items on pallets of completely different sizes. Even in packaging, if we optimize really well today, we can find great solutions that allow us to transport and continue working very efficiently. So if you simply look at the current status and then perhaps extend the whole thing over 5 years, then you can say that we are off to a good start. There will be more and more established solutions, more and more secure solutions. The trick is to do the right thing with the right data and you often have to rely on yourself, because unfortunately the largest of our data sources is now a little unreliable: There's just a fair bit of error on the internet already. So where do you get the best data? That also applies to us humans: By observing ourselves. I would like to go back to self-optimization, but also process optimization. Simply from systems that accompany us in our everyday operational business within logistics and production and within the handling of goods. If they observe us a little, then we will suddenly be able to automate things that are still too complex today."
Maurice Brodhun: Let's fast forward another 5years + keyword shortage of skilled workers. Will Germany manage the turnaround in 10 years? Will we have efficient production/logistics or is the issue still prevalent?
Prof. Dr. Fottner: "Oh, well, 15 years ago I always said to my employees "If we reach a point where we can all be satisfied and nothing can be improved, then I'll retire at the drop of a hat" - and I'm still convinced today that I'll retire when the law says I can, and then there will still be enough potential for optimization. But perhaps a clearer answer: I believe that we will achieve a lot in the next 10 years. I am afraid that we will absolutely realize that our strength lies in the connection between developing, producing and marketing something, in all three parts. By that I mean that value creation will continue to be of great importance to us. Back to the question: we MUST solve the problem. We MUST see how we can get there. Will this happen by increasing automation and autonomization? YES! Will that be the only solution? NO!
We must continue to ensure that we not only have highly intelligent doctoral students in this world, but equally intelligent skilled workers, and we must value and utilize them. Because we as humans - and I would say for the next 50 years - we have such great skills that you can't transfer them completely into a machine for normal money. BUT we can be supported by technology and therefore not just the gripper, the robot, the transport device, but also the EAP system, the organization, the process design, the process optimization - if we are more efficient there, then we already have a big advantage. Then I think we can manage with slightly fewer people. But we really have to make sure that we motivate more people again and this is asocial phenomenon: that doing something, carrying out something operationally, is in no way worse than being a great manager or scientist."
