Production logistics make use of artificial intelligence

With the help of AI, Landshut University of Applied Sciences wants to optimise internal company logistics and therefore increase the competitiveness of production industries in Bavaria

No other technology is changing our society and world of work quite as rapidly as artificial intelligence (AI). To be economically successful in the market, in addition to a good product, optimised and intelligent production processes are of considerable importance.

A research team at the Technology Centre for Production and Logistics Systems (TZ PULS) at Landshut University of Applied Sciences is currently addressing the topic of intelligent planning and management of internal logistics on an intensive basis. In this context, over the next four years, the new AIProLog – AI in Production Logistics project, which is being led by Prof. Dr. Sebastian Meißner, will develop concepts, methods and algorithms for the optimisation of AI-based production logistics so as to further strengthen the competitiveness and growth of industry in the region, especially of SMEs. The project has received some 600,000 euros of funding from the Bavarian State Ministry for Science and the Arts, an amount that has only been approved for eleven other universities in Bavaria.

Preventing errors, increasing working efficiency

Due to the increasing range of product variants and processes, modern production systems are increasingly dependent on intelligent management systems. With the use of artificial intelligence, the research team now wishes to optimise the flow of materials in the factory. The focus of the project is on intelligent data analysis and machine learning. “Our goal is to reduce the frequencies of error, increase the working efficiency and to support people with their decision-making through the provision of targeted information,” says Meißner, explaining the project.

Partial projects that lead to the goal

With the overall project, which is divided into two partial projects, the research team of six expects a considerable innovation boost for the further development of production logistics. The first partial project aims to optimise the processes in the provision of materials. Supported by real-time data, intelligent logistics systems should be able to gain knowledge, and thereby identify and eliminate bottlenecks in the logistics chain independently.

In the second partial project, historical data will be analysed and forecasts will be made. Subsequently, self-learning algorithms will be used to optimise the control and design parameters accordingly, so that the manual planning workload can be significantly reduced and users can receive solution suggestions on how to improve their production and logistics systems.

Strong support from industry

To establish the necessary practical relevance, the project is being supported by four industry partners, MANN + HUMMEL, KÜHNE+NAGEL, NeoLog and AGROTEL. The cooperating companies are able to try out the developed results at their locations and carry out process optimisations using AI systems together with Landshut University of Applied Sciences on site. The project is also being support by the Technical University of Munich (TUM) in the areas of research and cooperative doctoral studies.

“We are very pleased to have been able to gain four highly regarded and regionally based industrial partners for our project, and to have TUM on board at the same time. This demonstrates that with our project, we have our finger on the pulse,” explains Meißner enthusiastically.

A learning and model factory as a practical example

At the end of the project, the key goal will be to combine the research results from the two partial projects in the learning and model factory at TZ PULS. At TZ PULS, the project not only aims to demonstrate the added scientific value, but also to highlight the practical implementation of an increasingly extensive digital infrastructure. “At TZ PULS, on the one hand, we transfer research and development work into practice, while on the other, we provide interested companies in the region with clear access to the project results,” explains Meißner.

About the project

The AIProLog – AI in Production Logistics project is to run from January 2021 until October 2024. The project manager at Landshut University of Applied Sciences is Prof. Dr. Sebastian Meißner, Director of the Research Focus on Production and Logistics Systems (PULS) at Landshut University of Applied Sciences. In terms of the research focus, at the scientific level, the interdisciplinary project is being accompanied by Prof. Dr. Sascha Hauke, Professor of Intelligent Energy Networks, Prof. Dr. Mona Riemenschneider, Director of the “Engineering Education” course, Prof. Dr. Sven Roeren, Deputy Director of TZ PULS and Vice Dean of the Faculty of Mechanical Engineering, Prof. Carsten Röh, Professor of Automotive Economics, and Prof. Dr. Markus Schneider, Scientific Director of TZ PULS. The Bavarian State Ministry of Science and the Arts is funding the project with 600,000 euros as part of the research priorities programme pillar for the expansion of research structures of the 6th round of funding of the programme to promote applied research and development at universities of applied sciences/technical colleges.

Wissenschaftliche Ansprechpartner:

Prof. Dr. Sebastian Meißner

Weitere Informationen:

https://www.haw-landshut.de/en/partnerships/technology-centres/production-and-lo… A research team at the Technology Centre for Production and Logistics Systems is currently focusing on the “AIProLog – AI in Production Logistics” project