Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
The surge in industrial data and processing at the edge is a direct result of the growing digitalization of distributed assets on the plant floor. As a leader in Industrial Transformation (IX), your goal is to minimize latency for intelligent applications operating outside while also enhancing data processing capabilities at the edge. Recognizing the importance of data security, quality, and lifecycle management for local workloads and governance, you aim to oversee industrial edge devices in a streamlined, scalable, and secure manner. This necessitates establishing a robust foundation for a long-term edge computing strategy that not only ensures the success of edge deployments but also enables operational technology (OT) personnel to efficiently manage devices from any location. Additionally, it is essential to facilitate the effective deployment of applications on these devices, all while reinforcing your overall security posture to safeguard against potential risks. Ultimately, your commitment to advancing edge technology will drive innovation and operational excellence within the industrial sector.
Description
Siemens Industrial Edge is a multi-purpose edge computing platform that helps manufacturers process industrial data closer to where production happens. It is designed to optimize factory operations by combining Siemens and partner technologies across hardware, software, apps, connectivity, and central device management. The platform makes it easier to connect shop floor assets, standardize data, and turn operational information into real-time insights. Industrial Edge supports scalable app and device management, allowing companies to roll out software across distributed factory environments with IT-like simplicity. It connects OT systems with cloud platforms, IIoT SaaS solutions, ERP, MES, SCADA, and MQTT environments to support stronger IT and OT convergence. Manufacturers can use it for OEE monitoring, production analytics, intelligent maintenance, predictive insights, and resource planning. The platform also supports software-defined automation through virtual PLC and HMI capabilities, helping companies move toward more flexible manufacturing systems. AI models can be deployed on the shop floor for defect detection, monitoring, process optimization, and throughput improvement. With secure infrastructure, ecosystem offerings, and centralized management, Siemens Industrial Edge helps industrial organizations reduce complexity while making faster and smarter operational decisions.
API Access
Has API
API Access
Has API
Integrations
MSIGHTS
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
Rockwell Automation
Founded
1903
Country
United States
Website
www.rockwellautomation.com/en-us/products/software/factorytalk/factorytalk-edge.html
Vendor Details
Company Name
Siemens
Founded
1847
Country
Germany
Website
www.siemens.com/en-us/products/industrial-edge/
Product Features
Industrial IoT
Condition Monitoring
Data Visualization
Factory Data Analytics
Machine Learning
Machine Workflow Creation
Predictive Maintenance
Production Line / Factory Insights
Real-Time Monitoring
Reporting / Analytics
Smart Alerts / Notifications
Product Features
Industrial IoT
Condition Monitoring
Data Visualization
Factory Data Analytics
Machine Learning
Machine Workflow Creation
Predictive Maintenance
Production Line / Factory Insights
Real-Time Monitoring
Reporting / Analytics
Smart Alerts / Notifications
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization