Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
The Cherrywork® Predictive Asset Maintenance Application is designed to lower, streamline, and enhance the costs associated with asset lifecycles at every stage, from initial investment planning and network configuration to procurement, installation, operational management, and eventual disposal or replacement. This innovative tool plays a crucial role in identifying unforeseen equipment failures that could jeopardize customer satisfaction and overall reliability. Clients have an expectation for advance notice regarding planned outages, allowing them to manage their consumption effectively. By leveraging this application, users can proactively maintain their assets, thereby avoiding potential penalties. It harnesses historical data from a variety of sources to create precise and verifiable predictive models, enabling the generation of forecasts and risk assessments. Additionally, the application combines data from online monitoring systems, weather forecasts, and various non-operational information such as operational guidelines, equipment specifications, and industry standards, providing a comprehensive approach to asset maintenance. Ultimately, this integration of diverse data sources enhances decision-making and operational efficiency.
Description
The analysis of data from diverse IoT sources, such as sensors and devices, facilitates predictive and prescriptive insights that empower users to address potential anomalies in real time. Concentio® IoT Doctor effectively processes data from various IoT endpoints, notifying users of any faulty incoming data to ensure that issues are resolved before the data is utilized for further analytical purposes. Additionally, the Concentio® Production Line Fault Prediction tool leverages AI to conduct predictive assessments of production line components by analyzing IoT data, videos, and images. Meanwhile, Concentio® Optimal Asset Management scrutinizes incoming information from a network of utility service assets, allowing users to schedule timely maintenance and ultimately reduce capital expenditures by informing strategic asset replacement decisions. This comprehensive approach not only enhances operational efficiency but also significantly contributes to improved asset longevity and performance.
API Access
Has API
API Access
Has API
Integrations
SAP Analytics Cloud
SAP Extension Suite
SAP Integration Suite
SAP Store
Integrations
SAP Analytics Cloud
SAP Extension Suite
SAP Integration Suite
SAP Store
Pricing Details
$30,000 one-time payment
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
Incture Technologies
Founded
2006
Country
India
Website
store.sap.com/dcp/en/product/display-0000053552_live_v1/Cherrywork%C2%AE%20Predictive%20Asset%20Maintenance
Vendor Details
Company Name
Scry AI
Founded
2014
Country
United States
Website
scryai.com
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
IoT Analytics
Activity Dashboard
Activity Tracking
Analytics
Asset Tracking
Data Collection
Data Synchronization
Data Visualization
ETL
Multiple Data Sources
Performance Analysis
Real-Time Analytics
Real-Time Data
Real-Time Monitoring
Status Tracking
Preventive Maintenance
Condition Monitoring
Inspection Management
Maintenance Scheduling
Mobile Access
Predictive Maintenance
Purchasing
Reminders
To-Do List
Vendor Management
Work Order Management