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ease
features
design
support

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Description

Determining whether a machine is operational is relatively straightforward, but forecasting its potential failures over the coming days, weeks, or even months is considerably more complex. Envision a scenario where one of your industrial assets could inform you about an impending issue twelve months in advance, specifying not only the exact nature of the problem but also its underlying causes. With such foresight, you can strategically plan repairs or replacements well ahead of time, thereby significantly cutting costs by utilizing the ANNEA automated predictive maintenance platform. ANNEA stands out as the premier next-generation platform for condition-based predictive and prescriptive maintenance tailored for your machinery. Our innovative end-to-end solutions allow us to develop digital twins for each component of your machines, leveraging advanced artificial intelligence, physical modeling, and normal behavior modeling to enhance performance and reliability. This approach not only improves operational efficiency but also empowers you to make data-driven decisions for long-term asset management.

Description

Identify patterns in operational data that can forecast deterioration and potential failures long before they occur. By employing accurate failure pattern recognition, you can reduce the frequent occurrence of false positives typically associated with traditional model-based approaches. Utilizing low-touch machine learning, you can swiftly distinguish between normal and abnormal behaviors, ensuring equipment protection starts within weeks rather than extending into months. The integration of Aspen Mtell with Aspen Cloud Connect™ provides connectivity to devices that support OPC UA. This method of recognizing operational patterns not only serves as an initial defense against asset decline but also enhances existing maintenance strategies through the deployment of AI-driven agents across various sites or throughout the entire organization. By focusing on precise failure pattern recognition, the challenge of high false positive rates in model-based solutions is effectively mitigated. Moreover, the rapid identification of operational behaviors facilitates timely equipment protection, ensuring that organizations can respond proactively to potential issues as they arise.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

SAP Store

Integrations

SAP Store

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

ANNEA

Founded

2019

Country

Germany

Website

annea.ai

Vendor Details

Company Name

Aspen Technology

Founded

1981

Country

United States

Website

www.aspentech.com/en/products/apm/aspen-mtell

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

Preventive Maintenance

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

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