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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Utilize data gathered from current sensors to develop machine learning models tailored to your machinery. Ensure swift and accurate automatic monitoring of equipment that identifies problematic sensors. Speed up the resolution of issues with instant alerts and automatic responses when anomalies are identified. Enhance the effectiveness and precision of alerts by integrating trends in anomalies and user feedback. Amazon Lookout for Equipment serves as a machine learning monitoring solution for industrial machinery, identifying unusual operational behavior so you can respond proactively and prevent unexpected downtime. By automatically recognizing atypical equipment behavior, you can effectively avert unplanned interruptions. Lookout for Equipment systematically evaluates sensor data from your industrial systems to uncover abnormal machine activity. This capability enables you to swiftly identify equipment irregularities, diagnose concerns promptly, and take action to prevent unexpected downtime—all without needing prior machine learning expertise. Furthermore, consistent monitoring ensures that your models remain relevant and effective over time.

Description

FalconEAM, also known as Computerized Maintenance Management System (CMMS) Software, serves as a versatile, enterprise-level asset management solution that offers a comprehensive overview of an organization's asset infrastructure, including its availability, health, productivity, and the history of both periodic and preventive maintenance as well as maintenance strategies. By minimizing unexpected downtime, FalconEAM enhances asset performance and prolongs the operational lifespan of capital equipment, thereby boosting return on assets. Maintenance tasks, whether periodic, cyclic, or reactive, are efficiently scheduled and delegated to operators. The integration of Industrial IoT (Industry 4.0) sensors along with predictive analytics enables the system to issue alerts for preventive maintenance. Furthermore, it allows for the management of assets across various business units or sites while maintaining a unified view of the entire asset infrastructure within its operational framework. Additional features such as geo-tagging and regular audit updates ensure that asset availability is accurately validated at their designated locations, promoting a more organized and efficient management approach. Overall, FalconEAM stands out as a critical tool for organizations aiming to optimize their asset management practices.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon S3
Micromerce

Integrations

Amazon S3
Micromerce

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

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/lookout-for-equipment/

Vendor Details

Company Name

Inventrax

Country

India

Website

inventrax.com/enterprise-asset-management.aspx

Product Features

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

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