Siemens brings generative AI to predictive maintenance

Siemens has introduced generative AI functionality to its Senseye Predictive Maintenance to make predictive maintenance conversational and transition it to prescriptive maintenance.

The new generative AI functionality with a conversational user interface is aimed to bring a conversational element to predictive maintenance and make it more intuitive and effective, Siemens has stated in a statement.

Senseye Predictive Maintenance already uses AI and machine learning to automatically generate machine and maintenance worker behaviour models to direct users’ attention and expertise to where it’s needed most.

Machine and maintenance data are analysed by machine learning algorithms, and the platform presents notifications to users within static, self-contained cases.

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With the generative AI functionality, users will be able to introduce knowledge from other machines and systems through conversation facilitated between the user, AI and maintenance experts.

This interactive dialogue should streamline the decision-making process, making it faster and more efficient.

“By harnessing the power of machine learning, generative AI and human insights, we’re taking Senseye Predictive Maintenance to the next level,” comments Margherita Adragna, CEO, Customer Services for Digital Industries at Siemens AG.

“The new functionality makes predictive maintenance more conversational and intuitive – helping our customers to streamline maintenance processes, enhance productivity and optimise resources. This marks an important milestone in countering skill shortage and supporting our customer’s digital transformation.”

Siemens describes the introduction of generative AI as enabling a shift from predictive maintenance to prescriptive maintenance.

In the app, generative AI can scan and group cases 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 security, the information is processed within a private cloud environment and will be safeguarded against external access. Additionally, the 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, Siemens notes: With little to configure, it also factors in concise maintenance protocols and notes on previous cases to help increase internal customer knowledge.

Thus by better contextualising the information at hand, the app can derive a prescriptive maintenance strategy.

Siemens reports that the new generative AI functionality in Senseye Predictive Maintenance will be available starting this spring for all Senseye users.