Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
In an interconnected process industry where historical data is scarce, the unpredictability of failures is a constant challenge. Our comprehensive monitoring solution identifies quality concerns, equipment malfunctions, deviations in operational modes, and irregular process behaviors. Rather than sifting through countless false alarms, we streamline this to deliver a maximum of five meaningful alerts daily. This allows for advance notifications of potential failures, ranging from a week to just 24 hours before they occur, eliminating unexpected disruptions during off-hours. Emphasizing proactive and planned maintenance not only enhances operational efficiency but also reduces costs. The unique demands of industrial assets necessitate an innovative approach; we seamlessly integrate your team's expertise with advanced machine learning technologies to create a tailored predictive monitoring system. With your existing sensors and data, implementation is swift; it only takes two weeks for a process engineer to outline the plant's structure and behavior, after which the software will be fully operational, paving the way for improved reliability and performance. This rapid deployment ensures that your operations will benefit quickly from enhanced monitoring capabilities.
API Access
Has API
API Access
Has API
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
PreCognize
Country
United States
Website
www.precog.co
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
Maintenance Management
Asset Tracking
Billing & Invoicing
Calibration Management
Dispatch Management
Inventory Control
Inventory Management
Key & Lock Management
Mobile Access
Planning Calendar
Predictive Maintenance
Preventive Maintenance
Purchasing
Scheduling
Service History Tracking
Technician 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