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Description
Anticipate machine malfunctions before they arise by utilizing machine learning (ML) and taking proactive measures. Within minutes, you can initiate equipment monitoring through a straightforward installation, coupled with automated and secure analysis via the comprehensive Amazon Monitron system. The accuracy of this system improves over time, as it incorporates technician insights provided through mobile and web applications. Serving as a complete solution, Amazon Monitron leverages machine learning to identify irregularities in industrial machinery, facilitating predictive maintenance. By implementing this easy-to-install hardware and harnessing the capabilities of ML, you can significantly lower expensive repair costs and minimize equipment downtime in your factory. With the help of predictive maintenance powered by machine learning, you can effectively reduce unexpected equipment failures. Amazon Monitron analyzes temperature and vibration data to forecast potential equipment failures before they occur. Assess the initial investment needed to launch this system against the potential savings it can generate in the long run. In addition, investing in such a system can lead to enhanced operational efficiency and greater peace of mind regarding equipment reliability.
Description
Amazon SageMaker Model Monitor enables users to choose which data to observe and assess without any coding requirements. It provides a selection of data types, including prediction outputs, while also capturing relevant metadata such as timestamps, model identifiers, and endpoints, allowing for comprehensive analysis of model predictions in relation to this metadata. Users can adjust the data capture sampling rate as a percentage of total traffic, particularly beneficial for high-volume real-time predictions, with all captured data securely stored in their designated Amazon S3 bucket. Additionally, the data can be encrypted, and users have the ability to set up fine-grained security measures, establish data retention guidelines, and implement access control protocols to ensure secure data handling. Amazon SageMaker Model Monitor also includes built-in analytical capabilities, utilizing statistical rules to identify shifts in data and variations in model performance. Moreover, users have the flexibility to create custom rules and define specific thresholds for each of those rules, enhancing the monitoring process further. This level of customization allows for a tailored monitoring experience that can adapt to varying project requirements and objectives.
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
Country
United States
Website
aws.amazon.com/monitron/
Vendor Details
Company Name
Amazon
Founded
2006
Country
United States
Website
aws.amazon.com/sagemaker/model-monitor/
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Preventive Maintenance
Condition Monitoring
Inspection Management
Maintenance Scheduling
Mobile Access
Predictive Maintenance
Purchasing
Reminders
To-Do List
Vendor Management
Work Order Management
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization