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During the development of a new carbon fiber tank, large variations in burst pressure were found between different versions. Tanks must meet strict pressure limits for safety and quality. The challenge was to identify and reduce these pressure fluctuations to ensure reliable products and pass market approval.
Voith HySTech GmbH bundles Voith's expertise in hydrogen storage systems with a focus on solutions for the decarbonization of heavy-duty transport, including the first 700 bar, 350 liter H2 tank certified for on-road use in Europe.
During the development of the above-mentioned tank, which is a complex carbon fiber product and the first of its kind, large variations in burst pressure occurred between different versions of the tank during the production process.
This posed a serious problem because the burst pressure of all tanks must be within a certain narrow target corridor: Obviously, a tank must always withstand a certain minimum pressure. But there is also a maximum pressure that the tank must not exceed without bursting. This is an important criterion for a reliable, consistently high-quality product, and therefore also for product approval.
So the challenge was to identify the causes of these fluctuations in burst pressure between different tanks and reduce them to a minimum to achieve the best possible product and to pass the market approval process.
During the production of each tank, a large number of process parameters is collected. The basic assumption was, that somewhere in this data were hidden factors and dependencies, which directly impact the burst pressure of the tank in a way yet unknown. Thus, the AI engine powering Process Booster, aivis®, was fed with the raw historical process data of all so far produced tanks. aivis® then performed a Root Cause Analysis (RCA) with a report that unveiled the most critical influences on the burst pressure in a comprehensible.
Based on the insights provided by aivis® AI, it was possible to understand previously unknown relationships in the production process that have a direct influence on the tanks burst pressure. As a result, the production process could be quickly and decisively improved, leading to a 75% reduction in fluctuations in burst pressure.
Based on the insights provided by aivis® AI, it was possible to understand previously unknown relationships in the production process that have a direct influence on the tanks burst pressure. As a result, the production process could be quickly and decisively improved, leading to a 75% reduction in fluctuations in burst pressure.
“Vernaio’s AI analysis has helped us to reduce the variation in quality characteristics of composite structural components by 75% through the optimization of manufacturing parameters.“
Carolin Cichosz, CTO Voith HySTech GmbH
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