Artificial Intelligence

Robust, comprehensive solution for predictive maintenance

Robust, comprehensive solution for predictive maintenance

Robust, comprehensive solution for predictive maintenance

Siemens is integrating a new functionality with generative artificial intelligence (AI) into its predictive maintenance solution – Senseye Predictive Maintenance. This makes predictive maintenance more interactive and intuitive. With the new version of Senseye Predictive Maintenance, Siemens expands proven machine learning methods with generative AI and makes human-machine interaction and predictive maintenance faster and more efficient.

Combining generative AI and machine learning

Senseye Predictive Maintenance uses artificial intelligence and machine learning to automatically generate models for the behavior of machines and maintenance workers. This focuses the user's attention and expertise on the most important points. Building on this proven foundation, generative AI functionality is now being introduced to help customers leverage existing knowledge across machines and systems and select the right course of action to increase the efficiency of maintenance staff.

Machine and maintenance data is currently evaluated by algorithms that are automatically trained using machine learning. On this basis, the platform generates notifications for the user in static, self-contained cases. Senseye Predictive Maintenance's new conversational user interface offers a high level of flexibility and collaboration with little configuration effort. This enables a direct dialogue between the user, AI and maintenance experts: This interaction simplifies the decision-making process, making it more efficient and effective.

One of Senseye Predictive Maintenance's customers that will utilize the new generative AI functionality is BlueScope, an Australian steel manufacturer. “Senseye Predictive Maintenance is more than just a tool, it is a catalyst for change in our company. Siemens' innovative generative AI functionality will support our efforts to increase knowledge sharing between our global teams and further advance our ambitious digital transformation strategy," said Colin Robertson, Digital Transformation Manager, BlueScope.

From predictive maintenance to prescriptive maintenance

The generative AI scans and groups the recorded cases in the app, regardless of language. This allows her to specifically search for similar past cases and solutions to provide context for current problems. It is also possible to process data from various maintenance programs. To ensure the security of customer data, all information is processed in a private cloud environment. In order for generative AI to transform data into actionable insights, data quality is only of limited importance. With little configuration effort, brief maintenance logs and notes on previous cases can also be taken into account to expand the knowledge of maintenance employees. By better contextualizing the available information, the app is able to not only detect anomalies in the production process, but also proactively derive a suitable maintenance strategy (so-called prescriptive maintenance). The new generative AI functionality in the Senseye Predictive Maintenance software-as-a-service (SaaS) solution will be available to all Senseye users starting this spring. The combination of generative AI and machine learning creates a robust, comprehensive predictive maintenance solution.

Drive productivity and digital transformation

For Siemens, integrating generative AI into predictive maintenance is not just about improving the technology, but also about achieving tangible benefits for users. Faster, easier maintenance decisions increase productivity, promote sustainability and accelerate digital transformation across the organization. The new generative AI functionality is also an effective approach to combating the shortage of skilled workers in the maintenance sector: due to the upcoming generational change in the maintenance sector, important expert knowledge is being lost. Generative AI captures and archives this expert knowledge and makes it available to less experienced employees. This allows tasks to be completed more efficiently and effectively.

“By leveraging machine learning, generative AI and human knowledge, we are taking Senseye Predictive Maintenance to the next level. The new functionality makes predictive maintenance more dialog-oriented and intuitive. This helps our customers to streamline maintenance processes, increase productivity and optimize resources: an important milestone in counteracting the shortage of skilled workers and supporting the digital transformation of our customers", summarizes Margherita Adragna, CEO, Customer Services for Digital Industries, Siemens AG.