Google Cloud And Siemens To Cooperate On AI-Based Solutions In Manufacturing

By combining Google Cloud’s data cloud and AI/ML capabilities with Siemens’ Digital Industries Factory Automation portfolio, manufacturers will be able to harmonize their factory data, run cloud-based AI/ML models on top of that data, and deploy algorithms at the network edge.

Recently, Google and Siemens announced a new cooperation to optimise factory processes and improve productivity on the shop floor. The new cooperation aims to enable the scaled deployment of AI-based solutions for industrial manufacturing.

Siemens intends to integrate Google Cloud’s leading data cloud and artificial intelligence and machine learning (AI/ML) technologies with its factory automation solutions to help manufacturers innovate for the future.  

Deploying AI to the shop floor and integrating it into automation and the network is a complex task, requiring highly specialised 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.

By combining Google Cloud’s data cloud and AI/ML capabilities with Siemens’ Digital Industries Factory Automation portfolio, manufacturers will be able to harmonise their factory data, run cloud-based AI/ML models on top of that data, and deploy algorithms at the network edge. This enables applications such as visual inspection of products or predicting the wear-and-tear of machines on the assembly line.

Axel Lorenz, VP of Control at Factory Automation of Siemens Digital Industries said, “The potential for artificial intelligence to radically transform the plant floor is far from being exhausted. Many manufacturers are still stuck in AI ‘pilot projects’ today – we want to change that.” Lorenz added, “Combining AI/ML technology from Google Cloud with Siemens’ solutions for Industrial Edge and industrial operation will be a game-changer for the manufacturing industry.”

Dominik Wee, Managing Director Manufacturing and Industrial at Google Cloud commenting on the same 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.”

More Great AIM Stories

Ambika Choudhury
A Technical Journalist who loves writing about Machine Learning and Artificial Intelligence. A lover of music, writing and learning something out of the box.

More Stories

OUR UPCOMING EVENTS

8th April | In-person Conference | Hotel Radisson Blue, Bangalore

Organized by Analytics India Magazine

View Event >>

30th Apr | Virtual conference

Organized by Analytics India Magazine

View Event >>

MORE FROM AIM
Yugesh Verma
A beginner’s guide to Spatio-Temporal graph neural networks

Spatio-temporal graphs are made of static structures and time-varying features, and such information in a graph requires a neural network that can deal with time-varying features of the graph. Neural networks which are developed to deal with time-varying features of the graph can be considered as Spatio-temporal graph neural networks. 

Yugesh Verma
How is Boolean algebra used in Machine learning?

Machine learning model with Boolean algebra starts with the data with a target variable and input or learner variables and using the set of rules it generates output value by considering a given configuration of input samples.

3 Ways to Join our Community

Discord Server

Stay Connected with a larger ecosystem of data science and ML Professionals

Telegram Channel

Discover special offers, top stories, upcoming events, and more.

Subscribe to our newsletter

Get the latest updates from AIM