Meeting the current challenges in production and logistics - what role does artificial intelligence play in this? In the second part of our expert interview with Prof. Dr.-Ing. Johannes Fottner, University Professor of Technical Logistics at the Technical University of Munich, he paints a realistic picture of where our industry stands today - and in which areas AI will really deliver added value in the future.
Click here for part 1 of the expert interview: The 3 biggest challenges in production and logistics
Maurice Brodhun: "Where there are challenges, there are usually also solutions. A lot is happening now in terms of technology, especially with AI. How are the challenges being met today, what solutions do you see?"
Prof. Dr. Fottner: "Yes, you anticipated a good part of my answer. The good news for us engineers is that technology can actually score points here, so we can achieve something through technology. Why? Because in the last 20 years we have managed to resolve the so-called "dilemma" between automation and flexibilization to some extent - today we have wonderful automation solutions that are both flexible and scalable. In addition, and this is the first keyword - with AI, let's not get ahead of ourselves: in most cases, the systems are still not very intelligent - but they are at least much more adaptive than before. They can adapt a little to the changed environments, especially in terms of capacity. On the one hand, the number of small-scale solutions, such as smaller robots, gives us the opportunity to scale up simply by using more of them, but we are also moving in a direction where "AI" really comes into play: I observe myself and optimize myself in the process via production, including procedures that are quite common in retail. Packaging, picking, that's where you can really score points. Last but not least, the business administration, which is in the background and with the concept I mentioned above, it is slowly but surely possible to implement new business and financing models."
Maurice Brodhun: "You have already mentioned AI as a possible solution. What added value do you expect from AI?"
Prof. Dr. Fottner: "We can say today that it could be a great solution in the future - we have some good initial approaches where we are simply using AI for self-optimization. As I mentioned earlier, we can significantly improve the adaptivity and adaptability of the systems. We can also improve the process per se with the help of the technology and, ultimately, I would see the hope for the future development of AI more in the responsiveness and robustness of the systems. In other words: I can adapt to something much more quickly. If we think about the fact that we couldn't have predicted the pandemic in 2020, for example, we wouldn't have been able to achieve much even with today's view of AI, because we need historical data for what we understand it to be today. However, my view of AI is the extreme acceleration of learning processes. This means being able to react more quickly to changes in the market, in technology or changes in processes than is the case today."
Maurice Brodhun: "Let's take a look at our neighbouring countries or the world: are they on the right track for longer, how is progress towards AI and new technologies going?"
Johannes Fottner: "If you look outwards, you are always positively surprised, of course, by the countries, especially China and America, which simply represent extremely fast implementation times in many areas. If we now look at the negative example, the full sales driving of the famous US car manufacturer, which in the end - sorry - is not significantly better than what we understand by assisted or supported driving. There's a bit of marketing behind it - I'd like to take up the cudgels for us: I believe we can also be agile or fast. To the outside world, we very often have the impression that we are too slow, that we are losing touch. Why? Because we disregard what is fundamental to agile - namely to virtually omit planning. I think that's a misunderstanding of the agile approach - it should only plan ahead in reasonable portions so that we know what we're doing. I believe that a planned approach is still a great advantage for us, especially in the engineering sector. I think we do a lot of things very efficiently and I think we should keep that up. We just need to be a bit careful with the doubting sometimes and a lot of time is often wasted because we don't know what to do. I believe that a planned approach is still a great advantage for us, especially in the engineering area. I think we do a lot of things very efficiently and I think we should keep that up. We just need to be a little careful with our doubts sometimes and a lot of time is often wasted because we think through problem possibilities A, B, C and D beforehand instead of simply focusing on the possible solutions. And we try to rule out the problem options. But I think that's often a very psychological and marketing phenomenon that we display. Yes, from the outside there are countries that appear to be faster, but I believe that the substance of what we have already achieved with AI in a wide variety of areas, including in application, is quite respectable."
