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6 October, 2022

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AI-based edge app could raise drives availabilities by 30%

11 May, 2022

At the 2022 Hannover Fair, Siemens will unveil an AI-based edge app that detects problems in drive systems before they can affect production. The app will allow users to avoid unplanned downtime and to schedule maintenance times in good time, raising plant availability by up to 30%. Siemens says that by scheduling maintenance and servicing activities based on actual demand, companies will be able to boost their productivity by up to 10%.

The Predictive Service Analyzer will detect early signs of anomalies, such as bearing damage, imbalance and misalignment, that could indicate mechanical damage in motors, as well as critical operating conditions of frequency converters. The app will assess the severity of the defect and estimate the expected remaining runtime, thus predicting potential future failures.

The analyser is particularly suitable for applications with constant movements, such as pumps, fans, and compressors, or with motors that do not require speed control. Compared to Siemens’ earlier MindSphere Predictive Service Assistant app, the new edge app's analysis evaluates high data volumes in near real time. It also provides secure data handling and cuts costs for cloud data transfers. Together, the two apps can pre-process data which can then be used by the MindSphere app to provide further insights and recommendations for action.

The new app is part of Siemens’ Predictive Services for Drive Systems – a standardised extension to local service contracts. It can be used for more efficient maintenance of Sinamics frequency converters and Simotics motors. Users are said to benefit from higher productivity and reduced unplanned downtime. It also gives them transparency on spare parts and maintenance activities to minimise risks through simple weak-point analysis.

Siemens says that its new AI-based edge app will be able to improve motor and drive availabilities by up to 30%.

Different predictive services are available tailored to the needs of specific industries.

Siemens:  Twitter  LinkedIn   Facebook




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