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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

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.

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

Screenshots View All

Screenshots View All

Integrations

PI Vision
SAP Store
dataPARC Historian

Integrations

PI Vision
SAP Store
dataPARC Historian

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

Aspen Technology

Founded

1981

Country

United States

Website

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

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

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