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                    <title><![CDATA[BMW Group Newsroom Australia & New Zealand]]></title>
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                    <pubDate>Thu, 28 May 2026 13:47:00 +0200</pubDate>
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                        <title>BMW Group and Mistral AI advance AI in crash simulation</title>
                        <link>https://newsroom.bmwgroup.com/apac/en-au/bmw-group-and-mistral-ai-advance-ai-in-crash-simulation/</link>
                        <guid>https://newsroom.bmwgroup.com/apac/en-au/bmw-group-and-mistral-ai-advance-ai-in-crash-simulation/</guid><pp:caseid>776699</pp:caseid><pp:summary><![CDATA[+++ Use of industrial datasets for AI model training +++ AI improves crash simulation analysis +++ Combining engineering expertise and advanced AI capabilities +++]]></pp:summary><description><![CDATA[<div class="imported-article"><p>
  <strong>Munich / Paris. </strong> The BMW Group and Mistral AI are
  partnering to advance the use of AI in crash simulation. The aim is to
  improve quality, accuracy and speed in complex engineering tasks. The
  collaboration marks a first step towards scaling domain-specific AI
  across further areas of vehicle development and the BMW Group value
  chain.   </p>
<div>
  <p>“For the BMW Group, the use of industrial data is a key factor in
    translating artificial intelligence into value creation,” said Dr.
    Franz Decker, CIO and Senior Vice President of the BMW Group. “By
    combining our engineering datasets with Mistral AI’s model training
    capabilities, we are building specialized AI which supports complex
    development tasks.”  </p>
</div>
<div>
  <h3>
    <strong>Complexity and Data Volume in Crash Simulation</strong>  </h3>
</div>
<div>
  <p>The scale and complexity of crash simulation at the BMW Group
    underline the need for domain-specific AI. Each week, the company
    runs thousands of virtual crash simulations, generating vast amounts
    of engineering data. Over time, this has resulted in a historical
    dataset of over one petabyte of crash simulation data. It provides
    highly detailed insights into vehicle structures and material
    behaviour, forming a unique foundation for training an industrial AI
    model.  </p>
</div>
<div>
  <p>“As Industrial AI becomes the new frontier for AI, we are proud to
    partner with the BMW Group” said Marjorie Janiewicz, Chief Revenue
    Officer of Mistral AI. “This collaboration shows how industry
    specific AI models can help solve complex engineering challenges
    such as crash simulation.”  </p>
</div>
<div>
  <h3>
    <strong>Large Industry Model as technical foundation</strong>  </h3>
</div>
<div>
  <p>To scale this approach, the BMW Group is focusing on so-called
    Large Industry Models (LIM). These are AI systems trained on
    industry specific engineering and simulation data from vehicle
    development and safety testing. Unlike general‑purpose AI systems,
    LIMs embed domain‑specific knowledge directly into the AI model.
    This requires not only industrial data, but also deep domain
    expertise and technical environments that allow AI systems to learn
    directly from BMW’s development processes.  </p>
</div>
<div>
  <p>The partnership highlights the importance of industrial data for
    the next phase of data‑driven value creation and strengthens the BMW
    Group’s AI and innovation ecosystem.  </p>
</div>
<div>
  <p> </p>
</div><div class="import-contacts-wrapper"><div class="import-contact">Press Contact: Leanne Blanckenberg<br>Tel: +61-3-9264-4238<br>E-mail: <a href="mailto:leanne.blanckenberg@bmw.com.au">leanne.blanckenberg@bmw.com.au</a></div></div></div>]]></description><category><![CDATA[Research &amp; Development,Press Release,Software Development,Artificial Intelligence,Innovation,Digitalisation]]></category>
            <pubDate>Thu, 28 May 2026 13:47:00 +0200</pubDate>
            <pp:lastModified>Thu, 28 May 2026 11:47:00 +0000</pp:lastModified>
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                        <title>Where it all comes together: What does a data scientist do in high-voltage battery production?</title>
                        <link>https://newsroom.bmwgroup.com/apac/en-au/where-it-all-comes-together-what-does-a-data-scientist-do-in-high-voltage-battery-production/</link>
                        <guid>https://newsroom.bmwgroup.com/apac/en-au/where-it-all-comes-together-what-does-a-data-scientist-do-in-high-voltage-battery-production/</guid><pp:caseid>776706</pp:caseid><pp:summary><![CDATA[+++ Artificial intelligence and data analytics in high-voltage battery production +++ AI-supported quality assurance for zero-defect manufacturing approach +++ An interview with Patrick Zimmermann, data scientist and IT project manager +++]]></pp:summary><description><![CDATA[<div class="imported-article"><p>
  <strong>Munich.</strong> The high-voltage battery is a vital component
  of every electric vehicle. With the high-voltage batteries for the
  sixth generation (Gen6) of BMW eDrive, the BMW Group has made a big
  step in technology, delivering major improvements in energy density,
  charging speed and range. In readiness for series production, the BMW
  Group is currently building five assembly sites across three
  continents: in Irlbach-Straßkirchen (Lower Bavaria), Debrecen
  (Hungary), Shenyang (China), San Luis Potosí (Mexico) and Woodruff
  (USA). Before the series launch, production processes will be
  developed and tested at the BMW Group’s pilot plants for high-voltage
  batteries in Parsdorf and Hallbergmoos, and at the Research and
  Innovation Centre (FIZ) in Munich. As a data scientist andIT project
  manager, Patrick Zimmermann is responsible for implementing the
  Industrial Internet of Things (IIoT) and data analytics in the
  high-voltage battery production of the BMW Group. His role is to weave
  all relevant software strands together.</p>
<p>
  <em>
    <strong>Patrick, what do you do as a data scientist and IT project
      manager in high-voltage battery production?</strong></em></p>
<p>
  <strong>Patrick Zimmermann (PZ):</strong> I coordinate an
  interdisciplinary team that oversees the entire data processing chain:
  from data provision at the manufacturing facilities to edge
  applications that transfer our production data to the cloud and to
  analytics platforms.</p>
<p>
  <em>
    <strong>What kind of expertise do you need for that?</strong></em></p>
<p>
  <strong>PZ:</strong> First and foremost, the job requires a solid
  understanding of the technologies used to manufacture our high-voltage
  batteries. For this latest generation, which uses the new cylindrical
  round cells, we’ve developed a completely new production process. Of
  course, strong IT knowledge is also essential – with a clear focus on
  the software architectures behind the data analytics and artificial
  intelligence. Understanding the individual software modules and
  interfaces is crucial for choosing the right solutions for our
  production from the wide range of technologies and applications available.</p>
<p>
  <em>
    <strong>This means you always have your finger on the pulse and can
      anticipate IT trends?</strong></em></p>
<p>
  <strong>PZ:</strong> Data analytics and AI for production are evolving
  at a tremendous pace right now. That's why it’s important to keep an
  eye on new approaches and evaluate whether they’re suitable for BMW.
  Or whether they could even replace existing solutions – perhaps by
  offering lower costs or enhanced features. Not every analysis or AI
  solution that performs well in a particular industry or use case can
  be directly applied to battery production.</p>
<p>
  <em>
    <strong>Production of Gen6 high-voltage batteries is groundbreaking
      for the BMW Group. What, in your opinion, makes this project unique?</strong></em></p>
<p>
  <strong>PZ:</strong> One unique aspect is the end-to-end
  responsibility – from data provision and data transfer to the cloud,
  all the way through to selective and even continuous analyses. We
  process both numerical data and visual representations from the
  equipment. Throughout the process, we maintain a consistent
  zero-defect approach to producing our high-voltage batteries. Highly
  intelligent, AI-supported quality checks are integrated into the
  production process to help us achieve this. We rely on OPC UA
  interface technology for plant connectivity. This enables us to model
  standardised digital twins directly at our plants, eliminating the
  need for additional data processing. Data is transferred to the BMW
  Group's clouds, using the same data structure across all production
  sites. This allows us to roll out standardised analysis dashboards
  worldwide and, for example, implement process optimisations more
  rapidly. We’ve already established this IT architecture at our
  high-voltage battery pilot plants. We have now been able to transfer
  our analysis dashboards to the first series production plants with
  minimal effort.</p>
<p>
  <em>
    <strong>Entire new plants and assembly halls are being built for
      production of the new Gen6 high-voltage batteries. Is this
      beneficial for the IT structure?</strong></em></p>
<p>
  <strong>PZ:</strong> Absolutely! Building several plants for Gen6
  high-voltage batteries on greenfield sites gives us a whole new level
  of design freedom. This allows for much bigger leaps in IT, compared
  to integrating new solutions into existing plants – a so-called
  brownfield. I, for one, find it really exciting to help shape the
  Industrial Internet of Things and data analytics on such a large scale
  right from the start<strong>.</strong></p>
<p> </p>
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                <td align="left" valign="top"><p>
                    <strong>INFOBOX: How the BMW Group builds Gen6
                      high-voltage batteries </strong></p>
                  <p>With its innovative production processes, BMW
                    Group’s pilot and series plants are setting new
                    industry standards for battery production. Examples
                    include, among the consistent zero-defect approach,
                    the use of digital production twins for tasks such
                    as employee training, as well as leveraging expanded
                    AI databases to optimise supply and production
                    logistics. All production steps undergo seamless
                    in-line monitoring with comprehensive data storage,
                    enabling maximum process stability and continuous
                    data-based optimisation.</p>
                  <p>The BMW Group sources battery cells for its
                    high-voltage batteries from leading cell
                    manufacturers, who produce the cells to the
                    company's specifications. The highest technical
                    standards apply. Upon receipt of goods, additional
                    measurements – such as voltage checks – are carried
                    out. Next comes cell clustering, where the battery
                    cells are connected to coolants. This step ensures
                    optimal insulation and cooling of the cells. The
                    cell clusters and cell contact system are then
                    laser-cleaned and welded with pinpoint precision.
                    The in-line inspection continuously monitors each
                    weld seam in real time. An innovative foaming
                    process follows, ensuring that all elements are
                    protected as a mechanical unit. The foam thus
                    guarantees the safety, stability and durability of
                    the high-voltage battery. The housing is then
                    closed, sealed and riveted. In the final assembly
                    step, the Energy Master – the central control unit –
                    is installed onto the high-voltage battery. A
                    permanently elastic sealing adhesive is applied to
                    ensure a reliable seal. Finally, each high-voltage
                    battery undergoes a 100% end-of-line inspection to
                    ensure quality, safety and function.</p></td></tr></table></div></td></tr></table><div class="import-contacts-wrapper"><div class="import-contact">Press Contact: Leanne Blanckenberg<br>Tel: +61-3-9264-4238<br>E-mail: <a href="mailto:leanne.blanckenberg@bmw.com.au">leanne.blanckenberg@bmw.com.au</a></div></div></div>]]></description><category><![CDATA[Research &amp; Development,Press Release,Locations,Production Plants,Production,Drive Technologies,Industry 4.0,Information Technology,Artificial Intelligence]]></category>
            <pubDate>Mon, 18 Aug 2025 08:30:00 +0200</pubDate>
            <pp:lastModified>Mon, 18 Aug 2025 06:30:00 +0000</pp:lastModified>
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