Scalable data integration secures the efficient ramp-up of gigafactories in battery production
The realization of mass production for battery cells requires high-performance integration of machines, MES systems, and intralogistics. By standardizing millions of data points in real-time, a foundation is created for seamless traceability and AI-supported process optimization, which massively accelerates the complex ramp-up of global manufacturing sites.
Performance metrics
Savings of over €540 million per site through the significant reduction of production scrap during the start-up phase 10% reduction in machine-related investment and operating costs through highly efficient and automated data connectivity High-performance processing of 3,000,000 data tags to ensure data integrity under maximum system load Avoidance of potential revenue losses in the billions through proactive safeguarding of the global production ramp-up
Overview
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Use case in detail
Immense financial risks associated with delayed production starts
The construction of gigafactories in battery production involves extreme requirements for precision and scheduling. A delayed production ramp-up can lead to massive revenue losses between €1 billion and €2 billion. At the same time, the sheer volume of data—often exceeding three million tags per system—requires an infrastructure that pushes conventional solutions to their performance limits. Instabilities in data processing jeopardize not only the analysis but the entire physical material flow and quality assurance.
High-performance data standardization for mass manufacturing
To handle these enormous volumes of data, industrial connectware serves as a central integration layer. The software standardizes signals from the heterogeneous machine landscape and intralogistics to transmit them without latency loss to cloud systems such as Azure Event Hubs and Databricks. This architecture enables precise traceability of every single battery cell throughout the entire creation process and creates the necessary data density for complex analytics models directly in the cloud environment.
Maximum value creation through optimized material usage
Digital sovereignty over production data leads to a drastic increase in business value. By identifying quality deviations early on, scrap can be significantly reduced, saving triple-digit million amounts per plant alone. The speed gained during ramp-up and the increased efficiency in material consumption secure a decisive competitive advantage for companies in the global market for energy storage and electromobility.
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