BMW Group Plant Regensburg varieties a part of the GenAI4Q pilot undertaking that goals to utilise synthetic intelligence (AI) to enhance high quality management effectivity ranges in automobile meeting. At its core, the answer ought to present tailor-made inspection suggestions for the 1,400 (approx.) automobiles manufactured every day.
“Using synthetic intelligence helps the digital transformation of BMW Group manufacturing in direction of an intelligently related manufacturing facility – for instance, we’re utilizing AI for high quality management in automobile meeting,” mentioned Armin Ebner, Head of BMW Group Plant Regensburg. “On this approach, we’re optimising our manufacturing processes and creating added worth for our merchandise and, finally, for our prospects.”
The AI-based high quality inspection answer was developed at BMW Group Plant Regensburg with Datagon AI.
BMW’s automobile manufacturing
Making certain that BMW’s automobiles meet excessive product high quality requirements, Plant Regensburg completes a number of high quality checks all through the manufacturing course of. Earlier than automobiles go away the plant, they bear a ultimate inspection the place educated specialists study the entire automobile yet another time to make sure high quality requirements are met.
On the plant, a brand new automobile rolls off the meeting line each 57 seconds, with every automobile designed to fulfill particular person buyer specification necessities. Autos with inner combustion engines, plug-in hybrids, and absolutely electrical fashions are all manufactured on one manufacturing line, in addition to a wide range of fashions and tools variants.
Rüdiger Römich, who’s accountable for Check Ground and End in Regensburg’s automobile meeting, defined, “Our AI software generates a person inspection catalogue for every particular buyer automobile.”
How the AI high quality inspection works
The AI expertise works to analyse the massive quantity of information created by the customized specs, together with automobile knowledge (e.g., mannequin and tools variants), and real-time manufacturing knowledge for every particular automobile.
By recognising patterns and correlations, the AI system will shortly and mechanically analyse the scope of the inspection earlier than organising it inside a smartphone app. Moreover, the AI capabilities handle speech recognition and transcription, utilising standardised coding.
Römich concluded, “Intuitive usability makes it straightforward to file findings. Staff can even entry further features when wanted – for instance, a microphone icon within the app prompts voice recording.”
