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Description
APM Health, a component of GE Digital's asset performance management suite, oversees data for a wide range of assets and systems, thereby establishing a thorough and validated data repository that offers a unified perspective on anticipated performance across asset, plant, and enterprise levels. By addressing the issues of data inconsistency and delay linked to industrial asset management, APM Health grants users a real-time insight into asset health and condition, issues early warnings about possible failures, and identifies areas of elevated risk. The health manager utilizes the gathered data to assess and communicate the asset's current health within its operational framework. It employs anomaly detection through the calculation of various metrics and the implementation of rule-based exceptions. Furthermore, the health manager facilitates both continuous monitoring of asset health through data oversight and discrete or periodic assessments via rounds and calibration management, ensuring a comprehensive approach to asset reliability. This dual monitoring capability enhances the overall effectiveness of asset management strategies, allowing for timely interventions and informed decision-making.
Description
Analyze and utilize your data at the Edge to transform Big Data into manageable, pertinent insights. Gather sensor information from all your equipment and establish connections with various devices like sensors, PLCs, DCS, MES, or historians. Implement condition monitoring for assets located remotely, aligning with Industry 4.0 standards for effective data collection and integration. Merge real-time streaming data with enterprise data for seamless data flows, and utilize your preferred Cloud Provider or your own data center for data storage solutions. Leverage Crosser Edge's MLOps capabilities to bring, manage, and deploy your custom machine learning models, with the Crosser Edge Node supporting any machine learning framework. Access a centralized library for your trained models hosted in Crosser Cloud, and streamline your data pipeline using a user-friendly drag-and-drop interface. Easily deploy machine learning models to multiple Edge Nodes with a single operation, fostering self-service innovation through Crosser Flow Studio. Take advantage of an extensive library of pre-built modules to facilitate collaboration among teams across different locations, effectively reducing reliance on individual team members and enhancing organizational efficiency. With these capabilities, your workflow will promote collaboration and innovation like never before.
API Access
Has API
API Access
Has API
Integrations
Advantech WebAccess/CNC
Azure Stream Analytics
Barracuda PST Enterprise
Google Cloud Platform
Microsoft Azure
Integrations
Advantech WebAccess/CNC
Azure Stream Analytics
Barracuda PST Enterprise
Google Cloud Platform
Microsoft Azure
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
GE Digital
Country
United States
Website
www.ge.com/digital/applications/asset-performance-management/apm-health
Vendor Details
Company Name
Crosser Technologies
Founded
2016
Country
Sweden
Website
www.crosser.io
Product Features
Product Features
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization
IoT Analytics
Activity Dashboard
Activity Tracking
Analytics
Asset Tracking
Data Collection
Data Synchronization
Data Visualization
ETL
Multiple Data Sources
Performance Analysis
Real-Time Analytics
Real-Time Data
Real-Time Monitoring
Status Tracking