Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Senseye PdM employs advanced proprietary machine learning techniques to anticipate potential asset failures before they occur. By automatically evaluating the performance of your machinery, Senseye can accurately forecast when maintenance should be performed. This allows maintenance teams to prioritize their efforts on the assets that require the most urgent care. With an easy-to-implement solution, organizations can reduce maintenance expenses while enhancing the accuracy of downtime predictions. Designed for scalability, Senseye PdM can accommodate any number of connected machines, whether large or small. The automated condition monitoring provides insights that emphasize only the most pertinent information. Users gain an understanding of how long their machinery is expected to operate before maintenance is necessary. The platform allows for the seamless analysis of tens of thousands of assets, providing a clear and ongoing indication of which machines need attention. Furthermore, Senseye ensures that industrial companies experience significant reductions in machine downtime, ultimately leading to enhanced operational efficiency and productivity.
Description
A comprehensive solution for monitoring and predictive analysis can enhance equipment condition tracking and streamline maintenance and repair processes. This involves utilizing predictive analysis to ensure production process quality and assess potential risks of exceeding maximum permissible loads through detailed unit operation evaluations. By implementing predictive analysis of unit conditions, emergency shutdowns can be effectively minimized. Furthermore, evaluating the quality of repair work by comparing equipment performance before and after servicing is critical for continuous improvement. The integration of automatic controls for manual repair and maintenance tasks enables efficiency and accuracy in operations. Additionally, predictive analysis aids in strategic maintenance and repair decisions while facilitating informed purchases of new equipment based on intelligent load balancing of current assets. Spare parts and consumables can also be optimized through intelligent failure predictions, reinforcing a proactive approach to equipment management. Overall, this solution supports a robust framework for enhancing operational reliability and efficiency.
API Access
Has API
API Access
Has API
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
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
Senseye
Founded
2014
Country
United Kingdom
Website
senseye.io
Vendor Details
Company Name
Ctrl2GO Global
Country
Russia
Website
ctrl2go.solutions/en/solutions/smart-maintenance/
Product Features
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization
OEE
Benchmarking
Cost Tracking
Downtime Tracking
Historical Reporting
Performance Metrics
Quality Control
Real Time Reporting
Root Cause Analysis
Trend Analysis
Work Order Management
Preventive Maintenance
Condition Monitoring
Inspection Management
Maintenance Scheduling
Mobile Access
Predictive Maintenance
Purchasing
Reminders
To-Do List
Vendor Management
Work Order Management
Product Features
EAM
CMMS
Energy Management
Equipment Management
Facility Management
IT Asset Management
Inventory Management
Maintenance Management
Parts Management
Preventive Maintenance Scheduling
Software License Management
Warranty Management
Work Order Management
Preventive Maintenance
Condition Monitoring
Inspection Management
Maintenance Scheduling
Mobile Access
Predictive Maintenance
Purchasing
Reminders
To-Do List
Vendor Management
Work Order Management