Jungheinrich is working with Monolith to accelerate the development of battery-powered industrial trucks by applying AI modelling to battery test data.
Under the collaboration, Jungheinrich’s engineers analyse early battery test data using Monolith’s AI-powered engineering tools to derive predictions for product-relevant performance metrics. Machine learning models are trained and validated using real-world test data, providing insights at an early stage and reducing the scope of physical test campaigns.
Jungheinrich carries out battery tests throughout the development process, generating substantial volumes of technical measurement and test data. These datasets are transferred to Monolith’s engineering tools to train and validate predictive AI models.
As Jungheinrich expands its electric product portfolio, the collaboration aims to optimise the evaluation and selection of battery technologies by transforming test data into predictive models. Research by McKinsey suggests that AI-supported approaches could accelerate R&D processes in complex manufacturing industries by 20% to 80%.
Monolith’s engineering software is designed to reduce the need for prototypes and test campaigns, enabling engineering teams to focus on design and validation. Jungheinrich will also gain access to a central engineering intelligence platform where teams can access test data, model knowledge and recommendations for future experiments from various development programmes.
“As we continue to expand our range of electric industrial trucks, the ability to evaluate battery technologies quickly and reliably is crucial to maintaining our competitive advantage. By working with Monolith, we can make better use of our test data to identify critical battery performance characteristics earlier and make smarter technical decisions that support the next generation of more efficient, sustainable products,” says Dr Andreas Münz, head of HW testing, corporate infrastructure & test methods, Jungheinrich.
“Electrification is key to future-proofing the industrial equipment sector, and optimising battery performance is now a crucial factor in determining how quickly new products can be developed and brought to market. By using AI to analyse test data, we are helping Jungheinrich’s teams to transform complex battery datasets into actionable insights – which in turn enables them to make faster and more confident decisions whilst reducing their reliance on costly physical testing,” says Dr Richard Ahlfeld, CEO and founder of Monolith.
Image: Jungheinrich
