Google has partnered with Siemens to combine deep domain expertise in manufacturing with artificial intelligence (AI). The partnership aims to provide manufacturing with a way to deploy AI at the edge on manufacturing production lines in a way that can scale globally.
In a video showcasing how AI could be deployed on a production line, Axel Lorenz, vice-president of control and factory automation at Siemens Digital Industries, discussed AI-powered vision, based on a camera and a model trained by Google Cloud. Such a system could be used for inspection on the production line to help its workers ensure the packaging of industrial PCs is correct.
According to Google, while AI projects have been deployed by many companies in “islands” across the plant floor, manufacturers have struggled to implement AI at scale across their global operations.
Google claims its approach can operate across many different manufacturing companies by offering the ability to deploy AI on a global scale.
Dominik Wee, managing director of manufacturing and industrial at Google Cloud, said: “Siemens is a leader in advancing industrial automation and software, and Google Cloud is a leader in data analytics and AI/ML. This cooperation will combine the best of both worlds and bring AI/ML to the manufacturing industry at scale. By simplifying the deployment of AI in industrial use cases, we’re helping employees augment their critical work on the shop floor.”
Data drives today’s industrial processes, but many manufacturers continue to use legacy software and multiple systems to analyse plant information, which is resource-intensive and requires frequent manual updates to ensure accuracy.
Through the partnership, Siemens intends to integrate Google Cloud’s data cloud and artificial intelligence/machine learning (AI/ML) technologies with its factory automation system to help manufacturers innovate for the future.
In a blog post describing a vision for AI-powered factory automation, Rainer Brehm, CEO of factory automation at Siemens, predicted how manufacturers looking to make what people want will endeavour to build products that can be customised. This, he said, would require a shift in production from planned-out, overarching processes customary today to flexible, modular production.
“This new approach to manufacturing will use smart transport and handling systems, and the optimal path will be envisaged, simulated and implemented in real time. It will make it possible to change over production to an entirely new product overnight without wasting valuable time on engineering and commissioning a new production line,” Brehm wrote in the blog post.
Brehm said that autonomous production needs AI, edge and cloud computing, and blockchain. “These and other technologies are enabling the autonomous factory in ways that would not have been thinkable five years ago. Even today, they offer companies ways to imbue machines with intelligence – to make them capable of processing and analysing data and using it to make decisions independently.”
Google’s partnership with Siemens, one of the world’s largest manufacturers, follows on from Microsoft’s acquisition of Nuance earlier in April. Both are examples of public cloud providers growing domain expertise in AI. While Microsoft spent $19bn acquiring Nuance to bolster healthcare AI, the Siemens and Google partnership is wholly focused on filling a gap in manufacturing to provide AI at the so-called industrial edge.
