Leadace intelligent platform for increased quality and efficiency in electrolyte filling

By Setform

Electrolyte filling production lines to benefit from platform

Electric vehicle battery and energy storage companies have found a new solution in electrolyte filling for lithium-ion battery manufacturing. Lead Intelligent Equipment (LEAD) introduced its artificial intelligence platform (AI) Leadace to monitor critical points.

Leadace not only monitors critical points but also accurately determines re-filling volumes and issue prompt adjustment instructions. This gives consistent, high-quality results.

Human intervention is minimised to provide a rapid, flexible solution that maximises booth production efficiency and product quality. The solution was quick to have an impact with manufacturers noticing the benefits quickly.

Real-time monitoring and adjustments was possible using the leadace platform, preventing manual interventions and adjustments. This led to non-confirming battery cells per upgraded machine dropped by 47 units daily. Yield improvements typically ranged from 0.01% to 0.1% on newer machines, and 0.1% to 2.5% on older machines.
Production losses at the electrolyte filling stage were significantly reduced by integrating AI to automate and precisely control dispensing parameters. This was reflected in the data, showing new machines saved 4.75 tons of electrolyte annually – resulting in 49,000 euros worth of savings.

The AI-powered platform can make tailored data to evolving environments, helping to improve analysis accuracy and multidimensional capabilities. This smooths workflows and makes response times faster.

It didn’t take long for the leadace to reach a 99.98% electrolyte filling yield, marking an improvement in production efficiency and economic benefits.

Before the implementation of the AI-powered platform, blockages, crystallisation, and leaks in the filling pipes could all cause downtime in production. This would result in manual adjustments and EL would correct non-conforming products. This would lead to delays and relies on operator experience. These problems can be avoided with the use of AI. 

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