Siemens / Senseye

Andrea Gillhuber,

New Generative AI functionality in Predictive Maintenance

Siemens is releasing a new generative artificial intelligence (AI) functionality into its predictive maintenance solution - Senseye Predictive Maintenance. Using a conversational user interface, manufacturers can take proactive actions easily, saving both time and resources.

© Siemens

Through this new release of Senseye Predictive Maintenance with generative AI functionality, Siemens will make human-machine interactions and predictive maintenance faster and more efficient by enhancing proven machine learning capabilities with generative AI.

Senseye Predictive Maintenance uses artificial intelligence and machine learning to automatically generate machine and maintenance worker behavior models to direct users' attention and expertise to where it's needed most. Building on this proven foundation, now a generative AI functionality is being introduced that will help customers bring existing knowledge from all of their machines and systems out and select the right course of action to help boost efficiency of maintenance workers.

Currently, machine and maintenance data are analyzed by machine learning algorithms, and the platform presents notifications to users within static, self-contained cases. With little configuration, the conversational user interface (UI) in Senseye Predictive Maintenance will bring a new level of flexibility and collaboration to the table. It facilitates a conversation between the user, AI, and maintenance experts: This interactive dialogue streamlines the decision-making process, making it more efficient and effective

Advertisement

From predictive maintenance to prescriptive maintenance

In the app, generative AI can scan and group cases, even in multiple languages, and seek similar past cases and their solutions to provide context for current issues. It's also capable of processing data from different maintenance software. For added security, all information is processed within a private cloud environment, safeguarded against external access. Additionally, this data will not be used to train any external generative AI. Data doesn't need to be high-quality for the generative AI to turn it into actionable insights: With little to configure, it also factors in concise maintenance protocols and notes on previous cases to help increase internal customer knowledge. By better contextualizing information at hand, the app is able to derive a prescriptive maintenance strategy.

The new generative AI functionality in the Software-as-a-Service (SaaS) solution Senseye Predictive Maintenance will be available starting this spring for all Senseye users. The combination of generative AI and machine learning creates a robust, comprehensive predictive maintenance solution that leverages the strengths of both.

  • Xing Icon
  • LinkedIn Icon
Advertisement
Advertisement

You might also be interested in

Advertisement
Advertisement
Advertisement

Siemens

Edge rack server in robust

The trend towards hyper-convergent infrastructures is not stopping at the manufacturing and automation industry. Siemens has now launched the first edge rack server in robust industrial PC quality. How is the inner workings of the server designed?

read more...
Advertisement

Siemens

For personal use

Siemens operates vertical farming for its own use at its site in Frankfurt. Siemens technology is used here. What works here on a small scale is also a future field for agriculture in general.

read more...
Advertisement
Advertisement
Advertisement

In focus: Agriculture

The e-paper of issue 05/2024

Strategies for the future are one of the topics covered in the current issue of Computer&Automation. Read about the reforms that associations are demanding from politicians, the opportunities offered by technologies such as ChatGPT and SPE and...

read more...
Subscribe to our newsletter
Advertisement
Back to home