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New Terms of Use
The Subscription Term will automatically renew for successive Subscription Terms unless either party notifies the other at least 60 days prior to the end of the then-current Subscription Term that it has elected not to renew. Any renewed Subscription Term will be the same length as the preceding term or 12 months, whichever is greater. The fees for any renewed Subscription Term will be the same as those in effect at the end of the preceding Subscription Term, unless Siemens notifies Customer about different future fees at least 90 days prior to the end of the then-current Subscription Term.
The UCA (or any successor terms) available at Universal Customer Agreement (UCA) in the version that is current 60 days prior to the end of the then-current Subscription Term will apply for the following Subscription Term. However, if your subscription is governed by a master agreement that you have executed with Siemens, then that master agreement will continue to apply for any following Subscription Term, and auto-renewal terms for the subscription specified in that master agreement will prevail.
In all cases, instead of any previous versions of Supplemental Terms, the applicable Supplemental Terms available at Supplemental Terms in the version that is current 60 days prior to the end of the then-current Subscription Term will apply for the following Subscription Term.
Additional terms and conditions agreed upon in the initial order form (including product-specific terms), as well as agreed payment terms, will remain in effect for any following Subscription Term.
The Anomaly Detection can be extended by the Notifier App to send Anomaly-Notifications to smartphones or tablets.
In this case an additional license of the Notifier is required.
Additional Requirements
Hardware Demands
Industrial Edge Management License
Industrial Edge Devices in Industry Mall
Hardware Requirements
Anomaly Detection Basis runs on IPC227E (IPC427E is recommended)
Anomaly Detection Extension (DTA) Deep Time Analysis requires at least an IPC427E
Anomaly Detection
Provided by SIEMENS
AI to observe deviations in production processes/machines executed as Live Anomaly Detection in near real-time.
Early detection of abnormal behavior, signs of damage or vulnerabilities in production processes before they affect the entire production.
Use of AI methods with little effort (no tedious labeling required).
Unwanted abnormalities or changes can be quickly detected, for example, to avoid plant shutdown.
Easy selection and access to time series data through simple selection.
AI/Analytics methods run close to the data source (low latency, no unnecessary transport times/costs).
Clarity thanks to visualization of anomalies both time-related and asset-related.
Flexibility thanks to universal AI methods, adaptability due to easy data selection and data transformation.
The included machine learning (ML) methods use evidence from numerous metrics/sensors as multi-dimensional time series.
The user is quickly and clearly informed by the Live Anomaly Detection and its visualization.
The intuitive UI guides users from their raw data to a finished analysis model, which is executed as Live Detection on the Edge device (close to the data source).
Extension through the Notifier for Industrial Edge, for direct notification of anomalies on smartphones or tablets.
Entitlement
A subscription for this Industrial Edge App entitles to create one (1) single instance of this Industrial Edge App on an Industrial Edge Device.
Volume Discounts: For bulk purchases and quantities over 100, you may please contact your Sales representative.
| Minimum Quantity | Maximum Quantity | Discount per Quantity | Subscription Term |
|---|---|---|---|
| 0 | To 24 | Yearly | |
| 25 | To 49 | 5.00% | Yearly |
| 50 | To 99 | 10.00% | Yearly |
| 100 | To Max | 10.00% | Yearly |
Total: USD $1,452.00
Added to cart
Special features and essential highlights of Anomaly Detection for Industrial Edge.
By using artificial intelligence (AI) and especially machine learning (ML), Anomaly Detection enables pattern recognition in multi-dimensional time series to detect deviations even in a complex structure where linear methods (linear regression) fail.
The analytics are performed as Edge Computing completely on the Industrial Edge device, which makes it possible to signal in extremely short-term reaction the corresponding deviations.
Benefits
Anomaly detection enables abnormal structures in the production process to be identified at an early stage. Automatic, universal machine learning strategies are used. These are based on the historical data (no labeling required).
The user (operator) has the ability to immediately react to a peculiarity or abnormal situation, for example, in order to permanently ensure product quality or to avoid plant shutdown at an early stage.
The AI works around the clock and performs fully automated causal (temporal) as well as structural analysis of the interrelationships of all time series data. There is also the advantage of integration with automation using the Industrial Edge Management System.
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