BMW Group is making logistics robots faster and smarter
Munich. In future, the BMW Group will be increasing
its use of high-performance computer technology, particularly
artificial intelligence (AI), in logistics. Top priorities include
intelligent logistics robots, data analytics and the high-definition
simulation of logistics processes. These AI applications can optimize
robotics and material flow, as well as take simulations in the
planning process to a new level.
In a first pilot project, the BMW Group has equipped logistics robots
and smart transport robots (STR) developed in-house with
high-performance technology and special AI modules.
This improves the robots coordination as well as their ability to
recognize people and objects compared to the technology used
previously. The enhancements to the navigation system allow robots to
identify obstacles such as forklifts, tugger trains and people faster
and more clearly, which makes it possible to calculate alternative
routes in a matter of milliseconds. This AI-based technology enables
the robotics applications to learn and apply different responses to
people and objects.
“The use of high-end AI and visualization technologies to redesign
our logistics is revolutionary. Our collaboration with NVIDIA is
allowing us to develop state-of-the-art Industry 4.0 technologies,”
comments Jürgen Maidl, Head of Logistics in the BMW Group’s Production
Network. “With this high-end technology, we can further optimize our
logistics innovations and processes. Combining our innovations with
NVIDIA’s high-performance technology is a huge step forward.”
Faster and more precise thanks to high-performance computers
The BMW Group is currently working on developing five AI-enabled
logistics robots to improve logistics processes. This involves the
previously announced Smart Transport Robots (STR) for autonomous
transportation of materials, as well as logistics robots to select,
grab and handle components and load carriers. Developed based on
NVIDIA’s ISAAC robotics software platform, the robots utilize a number
of powerful deep neural networks (DNNs), including perception,
segmentation, pose estimation and human pose estimation. In addition
to real data, the robots are trained to render ray-traced machine
parts in a variety of lighting and occlusion conditions. The real and
synthetic data are then used to train deep neural networks on DGX
servers. The robots are virtually trained and tested on the ISAAC
robotics software platform, operating in Omniverse virtual environment
where multiple BMW Group personnel in different geographic locations
can all work in one simulated environment.
Optimized virtual logistics planning
The BMW Group already uses high-performance computer technology in
conjunction with artificial intelligence in its virtual logistics
planning. AI 3D scans can recognize different objects – such as
containers, building structures or machines – and use this information
to create a virtual layout plan through high-resolution 3D scans of
entire buildings and factories. The technology allows the engineers to
remove individual objects from the 3D scan using 3D planning software
and then change them one at a time. This makes it easier to simulate
and comprehend layout changes within the production halls.
The BMW Group production network
In 2019, strong customer demand and new models kept capacity
utilization high across the BMW Group production network. Production
volumes for the BMW, MINI and Rolls-Royce brands reached record
levels, with output totalling 2,564,025 units. Of those, 2,205,841
were BMW vehicles, 325,729 MINI, and 5,455 Rolls-Royce Motor Cars.
Approximately one million vehicles were manufactured by the German plants.
Uniquely flexible and highly efficient, the BMW Group production
network is able to respond quickly to changing markets and regional
sales fluctuations. Expertise in manufacturing is a key contributor to
the BMW Group’s profitability.
The BMW Group production network uses a range of innovative digital
and Industry 4.0 (IoT) technologies, including virtual reality,
artificial intelligence and 3D printing applications. Standardized
processes and structures across the production system ensure
consistent premium quality and allow a high degree of customization.
The use of Artificial Intelligence (AI) as a key technology is an
embedded element in the process of digital transformation at the BMW
Group. The company already employs AI throughout the value chain,
enabling it to generate added value for customers, products, employees
and processes. “Project AI” is the BMW Group’s centre of excellence
for data analytics and machine learning. It ensures rapid connectivity
plus knowledge and technology sharing throughout the company. “Project
AI” therefore has a key role to play in the BMW Group’s ongoing
digital transformation and underpins the efficient development and
scaling of new technologies. The BMW Group’s D³ portfolio provides
transparency on the use of technologies making Data-Driven Decisions
(hence the name D³). It comprises over 400 use cases at present, more
than 50 of which have already been made available for regular operation.
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