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What is Senseye PdM?

Senseye PdM utilizes cutting-edge proprietary machine learning approaches to predict asset failures before they happen. By continuously assessing the operational performance of machinery, Senseye is able to provide precise forecasts on when maintenance should be conducted. This capability enables maintenance teams to focus their resources on the most critical assets needing immediate attention. With a straightforward implementation process, organizations can lower their maintenance costs while improving the accuracy of their downtime forecasts. Built with scalability in mind, Senseye PdM can support any number of connected devices, regardless of size. The automated condition monitoring delivers insights that spotlight only the most crucial data. Users are informed about the expected operational lifespan of their machinery prior to the need for maintenance. Moreover, the platform facilitates the analysis of thousands of assets, offering clear and continuous updates on which machines require intervention. In addition to minimizing machine downtime, Senseye empowers industrial companies to enhance their operational efficiency and overall productivity. Thus, through its innovative approach, Senseye PdM not only optimizes maintenance strategies but also supports long-term asset management goals.

What is APM Health?

APM Health, which is part of GE Digital's asset performance management suite, manages data from a variety of assets and systems to create a comprehensive and validated data repository that provides a unified view of expected performance at the asset, plant, and enterprise levels. By tackling challenges related to data inconsistency and latency that typically hinder the management of industrial assets, APM Health delivers real-time insights into asset health, issues timely warnings for possible failures, and spots areas with elevated risks. The health manager leverages the collected data to evaluate and convey the current status of the asset in its operational context. It employs techniques for anomaly detection by scrutinizing metrics and implementing rule-based exceptions. Furthermore, the health manager ensures continuous monitoring of asset health through regular data surveillance, along with specific checks or scheduled assessments via rounds and calibration oversight. This comprehensive system ultimately enhances decision-making capabilities, bolstering operational efficiency, while also fostering a proactive approach to asset management that can lead to significant cost savings and improved reliability over time.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Free
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad

Supported Platforms

SaaS
Android
iPhone
iPad

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Online Training
On-Site Training

Company Facts

Organization Name

Senseye

Date Founded

2014

Company Location

United Kingdom

Company Website

senseye.io

Company Facts

Organization Name

GE Digital

Company Location

United States

Company Website

www.ge.com/digital/applications/asset-performance-management/apm-health

Categories and Features

Condition Monitoring

Not specified

IoT

Big Data Analytics
Data Management
Device Management
Performance Management
Visualization

Machine Monitoring

Not specified

OEE

Downtime Tracking
Historical Reporting
Real Time Reporting
Trend Analysis
Work Order Management

Preventive Maintenance

Condition Monitoring
Inspection Management
Maintenance Scheduling
Mobile Access
Predictive Maintenance
Purchasing
Reminders
To-Do List
Work Order Management

Categories and Features

Condition Monitoring

Not specified

Machine Monitoring

Not specified

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