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What is aspenONE Asset Performance Management (APM)?

Stay ahead of potential failures by receiving timely alerts weeks or even months in advance through the use of real-time data and predictive analytics. Adopt a comprehensive strategy that incorporates prescriptive maintenance, root cause analysis, and RAM analysis to address issues at multiple tiers, such as equipment, processes, and systems. Seamlessly deploy automated Asset Performance Management solutions using advanced machine learning methods that require minimal intervention, allowing for the anticipation of asset failures and the reduction of downtime throughout the entire facility, across different systems, or across various locations. This forward-thinking approach not only improves operational effectiveness but also leads to a substantial increase in overall productivity, fostering a culture of continuous improvement within the organization. By leveraging these advanced techniques, companies can ensure sustained performance and reliability in their operations.

What is Senseye PdM?

Senseye PdM utilizes cutting-edge proprietary machine learning approaches to predict asset failures before they happen. By continuously assessing the operational performance of machinery, Senseye is able to provide precise forecasts on when maintenance should be conducted. This capability enables maintenance teams to focus their resources on the most critical assets needing immediate attention. With a straightforward implementation process, organizations can lower their maintenance costs while improving the accuracy of their downtime forecasts. Built with scalability in mind, Senseye PdM can support any number of connected devices, regardless of size. The automated condition monitoring delivers insights that spotlight only the most crucial data. Users are informed about the expected operational lifespan of their machinery prior to the need for maintenance. Moreover, the platform facilitates the analysis of thousands of assets, offering clear and continuous updates on which machines require intervention. In addition to minimizing machine downtime, Senseye empowers industrial companies to enhance their operational efficiency and overall productivity. Thus, through its innovative approach, Senseye PdM not only optimizes maintenance strategies but also supports long-term asset management goals.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Aspen Technology

Date Founded

1981

Company Location

United States

Company Website

www.aspentech.com/en/products/apm/asset-performance-management

Company Facts

Organization Name

Senseye

Date Founded

2014

Company Location

United Kingdom

Company Website

senseye.io

Categories and Features

IoT

Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization

OEE

Benchmarking
Cost Tracking
Downtime Tracking
Historical Reporting
Performance Metrics
Quality Control
Real Time Reporting
Root Cause Analysis
Trend Analysis
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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