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Commercial Vehicle Cluster - Main Projects 2015-2017

„Industry 4.0.“ and „Automated driving at slow speeds“ - focusing on Innovation management as the most important subject for SMEs

Derived from the Commercial Vehicle Roadmap 2030 "Intelligent Commercial Vehicles and reliable utility vehicle networks", which was issued on behalf of the CVC - Southwest by the Fraunhofer Institute for Experimental Software Engineering in 2014 with the help of authors and review partners from industry, science and associations, the board of directors of the Commercial Vehicle Cluster agreed on three lead projects:

Additive Manufacturing in the Commercial Vehicle production

Due to the highly heterogeneous customer requirements, the production of Commercial Vehicles is characterised by a high product variety. In order to stay in control of the large product variety and to supply a worldwide market, complex processing chains within the development- and production networks are required. Therefore the mastery of the product and process complexity is one of the central challenges for Commercial Vehicle manufacturers and at the same time a strategic key to success in the worldwide competition.

Additive Manufacturing (AM), as a new production technology within the digital factory, helps managing these challenges. By using AM it is possible to partially or even completely substitute existing process chains. Apart from the saving of production and assembly processes for individual parts, logistic processes within the development- and production network are omitted. New possibilities are created for Commercial Vehicle manufacturers, by being able to produce prototypes in the shortest of times or relinguishing cost intensive spare part storages. Due to the flexible usability of different AM - methods there are potential benefits for any size of Commercial Vehicle manufacturer or product range.

At the moment however more research and development is needed, regarding the use of AM in the Commercial Vehicle production. The project will focus on potential applications in series production. In addition the view is laid on the production of spare parts and prototypes. Furthermore it shall be examined which AM method is suitable for which Commercial Vehicle part. In that economic as well as scientific assessment criterions are considered. During the running of the project a concept for the designing of processing chains shall be worked out, which are changed by AM, to facilitate AM in the development- and production networks of the Commercial Vehicle producers.

Producers as well as suppliers in the fields of trucks, farm machinery and building machinery are included into the project.


Technical University of Kaiserslautern
Chair for production technology and industrial organization

Prof. Dr.-Ing. Jan C. Aurich

D - 67663 Kaiserslautern

Phone: +49 631 205 2618

Safe cooperation and navigation of automated commerial vehicles for slow speeds

According to todays state of the art in science and engineering, complete automatization of Commercial Vehicles still represents an unsolvable problem. On the one hand the complexity of autonomous systems would be inefficient at the moment, on the other hand building safe and reliable Commercial Vehicles, according to scientific methods, is only a partially solved problem.

The central tasks of this project deal with the safe cooperation and communication of several Commercial Vehicles and the reliable identification of objects and human beings.

Safe cooperation of several Commercial Vehicles includes the organisation of parallel and trace driving, which could be loading processes in the field of farming, transportation processes on building sites, mining areas, foresting as well as road construction. Concepts to optimize working processes of using special vehicles, for farming or on building sites are addressed with the clear goal of increasing productivity and reducing CO2 emmissions through optimized operating cycles. One major part of such concepts is the comprehensive data exchange between manufacturer. An essential requirement therefore is data security, functional safety, and data privacy. The basis for this is the modelling of business processes, the linking with technical processes and the laying – down of the meaning of the exchanged information.

Identifying objects and human beings means first and foremost identifying people i.e in the working environment of building machinery. Here amongst others weather effects have to be compensated, suitable sensors have to be chosen and the expansion and geometry of dynamic objects have to be estimated.

Producers as well as suppliers in the fields of trucks, farm machinery and building machinery are going to be included in the project. Essential participants in the project will be IT- businesses with solutions for safe software.


Technical University of Kaiserslautern
Computer Science Department
Robot Systems Working Group

Prof. Dr. Karsten Berns
P. O. Box 3049
D - 67653 Kaiserslautern

Phone: +49 631 205 2613



OEM-Besuch bei der BOMAG GmbH

25. März 2020
BOMAG GmbH, Boppard

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8. Mai 2020
Ministerium für Wirtschaft, Verkehr, Landwirtschaft und Weinbau, Mainz

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30. Oktober 2020
Daimler Truck AG, Mercedes-Benz Werk Wörth

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