Siemens Senseye Predictive Maintenance

Siemens has launched the latest version of Senseye Predictive Maintenance. Utilising big data and AI technology, the app has transitioned from a custom-built tool to what Siemens says is a streamlined, user-friendly platform that can be easily tailored to the specific requirements of the user.

The app offers a cloud-based platform designed to support large-scale asset monitoring. By utilising custom AI algorithms, the platform is designed to identify both existing and potential issues, empowering maintainers to prevent malfunctions and unplanned downtime.

Accessible through any web browser on any device, the platform allows inspections to be conducted at any time and from anywhere, resulting in time savings and promoting a proactive maintenance approach. Its integration into real-world workflows is said to enable users to make informed decisions and optimise their operations.

The product takes an asset-agnostic approach by automatically constructing models. This should streamline the work of maintenance teams, reduce the likelihood of unexpected outages, eliminate manual inspections, minimise the need for excess spare parts and prevent unnecessary over-maintenance.

The latest version features a list-based interface with a split-pane design, side menu and collapsible panes, and a single-page design that consolidates all charts in one place for quick reference. Customisable layout options provide improved support for different screen sizes, and embedded widgets offer instant overviews of asset performance and team productivity. Enhanced reporting capabilities allow users to search, configure and export asset performance data.