Manufacturing AUTOMATION

Siemens-Voltaiq collaboration aims to optimize battery manufacturing

January 31, 2024
By Manufacturing AUTOMATION

Siemens Digital Industries Software is collaborating with Voltaiq to accelerate battery manufacturing, by combining their strengths to reportedly offer enhanced capabilities for battery manufacturing-focused companies.

According to a Siemens press statement, this collaboration aims to bring together the capabilities of both Siemens’ Insights Hub and Voltaiq’s Enterprise Battery Intelligence (EBI). Customers can gain access to enhanced 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 organizations, contributing to a new era in battery manufacturing,” says Raymond Kok, senior vice-president and managing director of cloud and edge foundational services at Siemens Digital Industries CTO.

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


Siemens’ Insights Hub’s industrial IoT solutions combined with Voltaiq’s suite of battery-specific monitoring, visualization and advanced analytics capabilities will reportedly provide customers with a seamless end-to-end solution for managing and optimizing battery cell manufacturing. Siemens shares that 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.

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