Autonomous transport systems, artificial intelligence and Industry 4.0 are at the heart of BMW’s “Logistics Next” project, which won the German Award for SCM 2019.
The commitment of top management to logistics as the centrepiece of the production process and a clearly defined roadmap
were the preconditions for the success of the large-scale project comprising the key attributes “autonomous, transparent, interconnected and collaborative”. Work is being performed simultaneously on different technologies at four major production locations – Dingolfing, Leipzig, Regensburg and Munich – and numerous system partners are sharing their new insights with each other. New technologies have been tested step by step and integrated in the value stream of the plants.
The “Logistics Next” transport and intralogistics project was launched in 2016 and is geared towards using the latest technologies to be able to respond to change easily and rapidly. These technologies include artificial intelligence (AI), Industry 4.0 concepts self-driving transport vehicles, electromobility and other alternative drive concepts, but also picking, transfer, sorting and positioning robots as support systems for the work performed by humans. The project is rounded off by the use of data glasses and paperless logistics processes as well as the intensive integration of specialists and management executives in the modification and improvement of operating routines.
The BMW Group plays a pioneering role in the use of autonomous transport systems both indoors and outdoors, as in the
pilot project in Leipzig. A self-driving outdoor transport robot called an “autotrailer” autonomously moves semitrailers from their parking space to the loading and unloading station. At the Dingolfing plant, a machine known as the “autobox” transports loads of up to 25 tonnes within the plant fully independently using a guide-free navigation system.
The “sortbot” is already in series operation at the BMW Group plant in Leipzig. It detects small load carriers with the help of
a 3D camera and artificial intelligence, identifies the optimum gripping point and then stacks the containers on the pallet using a suction gripper – thereby obviating the need for employees to perform these heavy and unergonomic tasks. Moreover, with the
“pickbot”, the “smart transport robot”, the “placebot” or the “splitbot”, the BMW Group logistics experts already have a number of further robots for complex applications either in the pipeline or in trial operation.
The jury's decision
The BMW Group project won the day against two other strong finalists, namely Airbus Operations GmbH and Loxxess AG. The key factor in the decision of the 17-member jury headed by Matthias Wissmann was that “Logistics Next” is a project in which the digital transformation is already well advanced. “The long-term nature of the objectives and plans, the stringency of the implementation concept and the enthusiasm of the protect participants as well as their team spirit are refreshing, innovative and exemplary – is as the cross-location cooperation between production, logistics and IT. The whole package really impressed us”, said Wissmann.
Supply Chain Sustainability Award - Strengthening combined transport
LKW Walter came out on top in the competition for the Supply Chain Sustainability Award 2019 presented jointly by the BVL associations in Austria and Germany. Second place went to logistics start-up Urban Cargo from Berlin, third place to Rail Cargo Austria. “In short, the aim of the winning project is to reduce the number of trucks on the roads”. To this end, LKW Walter has entered into a commitment to move road transports to the railways and waterways within the framework of combined transport concepts, and the company is investing in state-of-the-art combined transport equipment. LKW Walter is continuously expanding its network for combined transports from Austria, Germany, the Benelux countries, the UK and Scandinavia to Southern and Eastern
Europe in the form of unaccompanied trailers on trains or ships. It is also making use of environment-friendly engine types and optimising its transport planning processes.