Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
C3 AI® Sensor Health guarantees the efficient operation of IoT devices and their network infrastructure throughout both the installation and operational phases of these devices. It allows users to visualize the status of sensors, track deployment progress, and pinpoint geographic areas that may require attention, while also providing a prioritized list of sensors that have been flagged for health concerns. Users can uncover issues related to sensor deployment, determine the origins of malfunctions, streamline field service operations, and anticipate future deployment advancements. It is crucial to maintain accuracy, consistency, and up-to-date installation information across both source and cloud data systems. Additionally, the platform facilitates the monitoring and analysis of the physical integrity, functionality, and communication capabilities of sensor devices, which aids in improving field service and resolving issues effectively. Users can visualize planned sensor installations alongside actual deployment and provisioning advancements, along with tracking operational problems and trends related to devices, and prioritize service tasks accordingly. The system also generates comprehensive analyses and consolidates findings through both preformatted and customized reports, which cover aspects such as failure analysis and health assessments, thus providing valuable insights for decision-making. Overall, this robust solution enhances the management and performance of IoT ecosystems.
Description
The Failure Reporting, Analysis, and Corrective Action System (FRACAS) serves as a comprehensive feedback mechanism that facilitates collaboration between users and suppliers to gather, document, and evaluate failures related to both hardware and software systems. During the design evolution phase, corrective actions (CAR) are most effective, but as the design solidifies, implementing these actions becomes increasingly costly and constrained. The analysis conducted within this framework pinpoints necessary corrective measures that must be executed and verified to avert the recurrence of failures. By fostering reliability enhancements throughout the equipment's lifecycle, FRACAS can be applied during various testing phases, including in-house laboratory evaluations, field tests (whether alpha or beta), and production operations, enabling stakeholders to identify and address areas of concentrated issues within the equipment's design. This systematic approach not only enhances product reliability but also ensures a more efficient path to problem resolution.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
Google Cloud Platform
HPE Industrial IoT
JewelSuite
Microsoft 365
Integrations
Amazon Web Services (AWS)
Google Cloud Platform
HPE Industrial IoT
JewelSuite
Microsoft 365
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
C3 AI
Country
United States
Website
c3.ai/products/c3-sensor-health/
Vendor Details
Company Name
Qsoft
Website
www.qsoft.cc/qsoft_website/FRACAS.aspx
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
Product Features
CAPA
Audit Management
CAPA Planning
Change Management
Complaint Management
Incident Management
Nonconformance Tracking
Quality Control
Risk Management
Root Cause Analysis
Training Management