Siemens Brings Google Cloud’s AI-based Solutions Aboard its Industrial Edge Digital Enterprise
Siemens and Google Cloud joined forces in order to bring together a wealth of knowledge for the improvement of scalable AI deployment in manufacturing.
The combination of Siemens industrial expertise and Google’s Cloud and AI know-how set the stage for a unique opportunity to make AI a bigger part of industrial manufacturing’s future.
Collaboration Between Siemens and Google Cloud
Google Cloud has experience in more than 200 countries helping to digitally transform businesses. The company helps give companies a foundation for the future by leveraging its knowledge of efficient business operation, which can cut down on waste and save resources. Google Cloud has become an industry leader that many companies trust as a partner to solve critical business problems.
Video used courtesy of Google Cloud
Siemens has over 170 years as a global technology giant. It has stood at the cutting edge of power distribution, intelligent infrastructure, and manufacturing for a long time. As a leader in digitalization and automation, Siemens remains a leader in helping customers achieve greater flexibility and efficiency.
Partnering AI, ML, and Industrial Processes
Many manufacturers still use legacy software and multiple systems to carry out processes that would be more efficient when combined in a cloud setting. Most of the current AI in today’s manufacturing plants is isolated to specific tasks and operations. When traditionally isolated AI technology is linked together across the board, entire processes become more efficient.
Siemens’ Digital Enterprise for Industrial Edge plans to use Google Cloud’s technology. Image used courtesy of Siemens
The process of introducing AI and ML to the plant floor is a very complex task that requires highly specialized knowledge and expertise, like that of the Siemens Industrial Edge. The partnership will allow for a smoother transition into the future of AI in a plant setting. This helps to allow for easy integration into the new technology among plant workers, helping to automate mundane tasks and bring the standard of quality up.
Quality control constitutes a large expense in most manufacturing processes and Siemens hopes to improve the quality control process through ML and AI. The improvement may help to lower costs and inefficiencies for manufacturers while improving work standards.
The Change from Pilot to Practical AI
Most plants and manufacturing processes are stuck in the “Pilot” phase of AI and ML integration. With the industrial backing of Siemens and the Cloud/AI experience of Google, AI can become a practical solution to many industrial automation problems. Efficiency may increase because plants can be connected on a global scale, helping to determine and predict part wear and other unavoidable inefficiencies in manufacturing.
Quality control can also improve with the help of AI and ML. Worker job satisfaction could increase as more mundane tasks are replaced with AI and automation. The partnership between Siemens and Google will be a large step into the future of industrial AI and ML as a standard for industrial automation.