Enhancing gigafactory efficiency and EV battery quality through a holistic approach
The automotive industry is experiencing changes to meet high global environmental standards. A major trend in automotive is the implementation of new drive concepts based on holistic manufacturing analysis powered by artificial intelligence.
Generally, a holistic approach has been discussed for the production of batteries for electric vehicles, but not much has been done because of the difficulty of achieving complete end-to-end control of the entire EV battery manufacturing process.
The key challenge is the inability to integrate and analyze data from all types of machines and test equipment located during the manufacturing process.
Gigafactories currently store data in an endless array of data structures that prevent us from integrating them to create a holistic end-to-end process control.
What is the solution to this major problem?
With AI algorithms and prediction models, and automated root cause analysis capabilities, we can overcome this multi-data structure problem and optimize the quality of EV batteries and the efficiency of gigafactories.
The holistic view of the manufacturing system consists of understanding the system by automatically analyzing the relations between multiple sources of data as testing data instead of analyzing only machines independently.
A complete Analytics solution for batteries manufacturing needs to:
- Integrate process with entire factory data
- Collect and unify factory data into a digital twin database
- Analyze factory data using AI algorithms
- Visualize BI Analytics for the factory
QualityLine AI technology combines inspection and manufacturing processes to create smart connected assembly solutions that realize the vision of Industry 4.0 and drive innovation for EV batteries.
AI prevents electric vehicle fires caused by battery malfunction, and there are many other improvements that you can learn more about by getting in touch with us at firstname.lastname@example.org.