Siemens and Voltaiq collaborate to optimise battery manufacturing

This collaboration aims to bring together the production-proven capabilities of both Siemens' Insights Hub and Voltaiq's Enterprise Battery Intelligence (EBI). Customers can gain access to unparalleled capability specific to battery-domain companies to help rapidly scale operations smoothly, from initial testing to full-scale production lines.

Our collaboration with Voltaiq aligns with Siemens' ongoing mission to continue delivering Industrial IoT value. By integrating our efforts, we not only help to enhance operational decision making but also assist our customers to accelerate the digital transformation of organisations, contributing to a new era in battery manufacturing, says Raymond Kok, Siemens Digital Industries CTO.

Tal Sholklapper, CEO and co-founder of Voltaiq, says: The battery industry is struggling to scale and needs to improve quality and decrease scrap rates rapidly in order to stay competitive. By joining forces with Siemens, we're able to deliver a complete solution to help accelerate toward an electrified future.

The world is relying on battery-powered products more than ever, from the largest vehicles to the smallest personal devices. Experts are forecasting a 14-fold increase in battery demand between 2018 and 2030 and a five-fold growth in battery cell production from 2020 to 2030 for electric vehicles (EVs) alone. The increased demand for battery manufacturing introduces numerous challenges and complexities to manage, including quality control, production efficiency, waste reduction and cost minimisation.

Siemens' Insights Hub proven industrial IoT solutions combined with Voltaiq's comprehensive suite of battery-specific monitoring, visualisation, and advanced analytics capabilities provides customers with a seamless end-to-end solution for managing and optimizing battery cell manufacturing.

The joint solution addresses the challenges faced in the critical finishing stage of battery production which makes up a significant portion of the production costs and time by helping to reduce the risk associated with discovering problems late in the production cycle where yield and profitability are most likely to decrease.