factory ai

The companies join forces to create industrial applications, optimize processes, improve productivity and help manufacturers innovate using AI.

factory ai
Engineer control welding heavy automation with smart connection new technology in the future.

Google Cloud and German industrial giant Siemens announced Monday a new partnership to optimize factory processes and improve factory-floor productivity. As part of the agreement, Siemens will integrate Google Cloud’s data cloud, artificial intelligence, and machine learning (AI/ML) technologies into its factory automation offerings.

“We offer several off-the-shelf AI products ranging from Vision AI to Dialogflow, to Recommendations AI that will serve as building blocks for new joint solutions with Siemens,” said Dominik Wee, managing director of manufacturing and industrial at Google Cloud. “These solutions will address common factory automation use cases, such as quality control, energy efficiency, and more. Ultimately, this collaboration is about providing a unique, end-to-end offering to unlock the value for manufacturing companies through the convergence of IT and OT [operating technology].”

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Combining Google Cloud’s data cloud and AI/ML capabilities with the Siemens Digital Industries Factory Automation portfolio is intended to help manufacturers harmonize data from multiple, heterogeneous systems and vendors and run cloud-based AI/ML models that data and deploy algorithms at the network edge. These capabilities will enable manufacturers to deploy applications such as predictive maintenance and allow machines to conduct visual product inspections.

Data drives today’s industrial processes, but many manufacturers continue to use legacy software and multiple systems to analyze plant information, which is resource-intensive and requires frequent manual updates to ensure accuracy. Besides, 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.

Deploying AI to the shop floor and integrating it into automation and the network is a complex task, requiring highly specialized expertise and innovative products such as Siemens Industrial Edge.

The goal of the cooperation between Google Cloud and Siemens is to make the deployment of AI in connection with the Industrial Edge—and its management at scale—easier, empowering employees as they work on the plant floor, automating mundane tasks, and improving overall quality.

SEE: 5 Internet of Things (IoT) innovations (free PDF) (TechRepublic)

“The potential for artificial intelligence to radically transform the plant floor is far from being exhausted,” Axel Lorenz, Siemens’ vice president of Control at Factory Automation, said in a statement. “Many manufacturers are still stuck in AI ‘pilot projects’ today. We want to change that.”

According to Wee, the manufacturing industry has not benefited from the cloud and AI technology to the same extent as other verticals. According to Google research, three-fourths of surveyed manufacturers (76%) revealed that the pandemic increased the use of digital enablers and disruptive technologies such as cloud, AI, data analytics, robotics, 3D printing/additive manufacturing, Internet of Things, and augmented or virtual reality.

“We want to accelerate the adoption of AI for manufacturers,” said Wee. “By tightly integrating the two companies’ technology stacks, deploying AI at scale will become much easier, empowering employees as they work on the plant floor, automating mundane tasks and helping prevent mistakes before they become more serious issues.”

Disclaimer: I am the author at PLM ECOSYSTEM, focusing on developing digital-thread platforms with capabilities across CAD, CAM, CAE, PLM, ERP, and IT systems to manage the product data lifecycle and connect various industry networks. My opinions may be biased. Articles and thoughts on PLMES represent solely the author's views and not necessarily those of the company. Reviews and mentions do not imply endorsement or recommendations for purchase.

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