Logistics processes’ share of the added value in the automotive industry has been growing for years. In times of decentralized production, simulation helps to manage logistics processes that are becoming more complicated all the time. Dr.-Ing. Christian Schwede, Head of Information Logistics and Assistance Systems at Fraunhofer Institute for Material Flow and Logistics IML in Dortmund, on the trend of simulating in simulations.
Simulation in logistics: How far have companies come?
Many companies use simulation in the classic case, when logistics systems are redesigned or planned. They avoid expensive bad planning in this way. What applies to the relatively static classic systems, of course applies all the more to the new highly flexible Industry 4.0 systems. When Audi announced in 2017 that they were getting the startup Arculus to replace the classic assembly line with flexible assembly islands with autonomous transport robots moving bodywork between them, I was very surprised. Drivers are turning to solutions with flexible, driverless transport systems in logistics too. Simulation is becoming indispensable when planning these systems. What’s more: Daily management of these types of systems will not be possible without simulation either. Simulation must be used in operation and permanently, based on a digital image of the processes, the digital twin. Audi realized this. As a result, Arculus’s work focuses on the simulation of Industry 4.0 systems.
Dr.-Ing. Christian Schwede
“As far as parts supply is concerned, logistics experts may also become the digital keystone for future car production – not only through the physical transports but also the data which they provide.”
So, what are the challenges?
There are two movements in the development of new simulations. Firstly, how can I use simulation in operation? This takes the form of decision systems for day-to-day planning. Logistics assistance systems use digital twins as the basis for simulation, they call up data in real time, save it and make it available at the touch of a button.
Secondly, the requirements of industrial production are tackled. As described, this is currently very important in the automotive industry, for example in oder to organize decentralized assembly. Current simulation tools quickly reach their limits. The existing production systems have become so flexible that the manual effort to draft the many possible scenarios for simulation becomes infinitely high!
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Can you explain this using an example?
Yes, for example in the production of vehicles that are manufactured at production islands instead of on a line. Here, autonomous transport systems supply the islands and have to decide when they approach which island with existing stock at which point in the production and must at the same time take the most efficient route.
However, what happens if all the parts have to be at an island at the same time, if I have to drive past some islands, if there are traffic jams or waiting lines? In order to be able to control these decisions, we have to decide how far ahead the transport systems can see, i.e. how far they are allowed to simulate their own future. Here, the simulation of the simulation is also important.
How can this problem be solved?
The challenge consists separating the control from the simulation modules and creating a system that is both process-oriented and highly flexible. Another important topic is: How do we obtain data for permanent simulation in operation and how do we prepare this data? We have already been working very intensively on this topic for a long time.
And this is where the logistics experts come into it?
Exactly. The topic is of great importance to car manufacturers since they also have numerous different IT systems. Logistics providers also have immense amounts of data, with this data coming from a wide range of sources and from several different IT systems. As for many data analysis topics: All the available information must first be prepared in order to make it possible to analyze it. As far as parts supply is concerned, logistics experts may also become the digital keystone for future car production – not only through the physical transports but also the data which they provide.
Research and practical application
The right information in the right place at the right time – this is the simple slogan for the activities of the Information Logistics and Assistance Systems department in the Fraunhofer Institute for Material Flow and Logistics IML in Dortmund. In 2016, approximately 260 employees worked at IML. DB Schenker entered into a research partnership with IML and, in 2015, was the first international logistics provider to set up the “DB Schenker Enterprise Lab for Logistics and Digitization” at IML.