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Applying Data Analysis Tools for IIoT Systems
The digital transformation is upon us, and companies are, in growing numbers, turning to…
3 Ways to Leverage Digital Technology for Effective Centerlining in Manufacturing
In today’s manufacturing landscape, accuracy is everything. It’s impossible to remain competitive with inconsistent…
IIoT: Industrial Internet of Things
IIoT stands for the Industrial Internet of Things and refers to a network of connected devices in the industrial sector. It is a subset of the Internet of Things (IoT). The defining characteristic of connected devices on IIoT networks is that they transfer data without human-to-human or human-to-computer interaction. The terms IIoT and IoT refer to proprietary, standalone networks, as well as broader, global networks.
MQTT Protocol
MQTT (Message Queueing Telemetry Transport) is a simple, lightweight message publishing and subscribing network protocol. It is the standard protocol for Internet of Things (IoT) and Industry 4.0 messaging.
It is lightweight, low bandwidth, and functions well in high latency and unreliable environments, making it ideal in production environments. Devices send data (publish) to an MQTT Broker with a topic and a data payload, and devices can subscribe to that topic and subtopics and receive updates containing that data from the broker when the data changes. Topics can be defined to use several levels of depth and devices can subscribe to topics using wildcards allowing for dynamic changes when required.
Zero-Trust Data Security
Zero-Trust is a security concept and cybersecurity framework allowing an organization to aggressively defend itself, its data, and user permissions using an advanced system of automated security protocols. Zero-Trust is centered on the belief that organizations should not automatically trust anything inside or outside their perimeters and instead must verify anything and everything trying to connect to their systems before granting access.
Data Correlation
The EDM Correlation data analysis tool is designed to help users perform root cause analysis across multiple devices or systems. It compares the activity of one system over a given period with the activity of multiple other systems and identifies the most highly related data points. This allows EDM to create an intuitive visualization of related events across an entire network of mixed technology enabling root cause analysis to be performed more efficiently than ever before.
Use Cases
What’s Really Happening Inside Your Unisys AB Suite Transactions? Now You Can See.
If your organization runs a mission-critical application on Unisys ClearPath MCP with Agile Business…
Real-Time Predictive Maintenance in Manufacturing: How IoT Sensors Reduce Downtime
In manufacturing, system downtime, even in short bursts can tank your profits. An unexpected…
Monitoring Legacy Mainframes: Why Visibility Into Older Systems Still Matters
In many organizations, legacy mainframes remain the backbone of critical business operations, handling everything…
When to Use Predictive vs. Real-Time Alerting in Enterprise IT Monitoring
Enterprise IT teams don’t have to choose between real-time and predictive alerting; the strongest…
How to Create a Unified Dashboard for IT and OT System Health
Modern industrial operations run on two parallel worlds: Information Technology (IT) and Operational Technology…
What Metrics Should You Monitor in ftScalable Storage Systems?
For organizations running mission-critical workloads on Stratus ftServer environments, the ftScalable storage array is…
eBooks
5 Reasons Why Smart Manufacturers Should Implement Industry 4.0 Analytics
This guide demonstrates how modern manufacturers can unlock the full value of their machine data to achieve the productivity, quality and efficiency gains promised by Industry 4.0.
5 Stages of Success with Manufacturing Analytics
This guide will document the steps modern manufacturers have taken on their way to implementing their IIoT strategy, considering the advantages of an industrial analytics platform and ultimately making steady progress on their digital manufacturing journey.
Capacity Planning: 6 Steps to Automating IT Resource Management
This guide details the six steps proactive IT operations teams can take to automate capacity planning, reduce over-provisioning expenses and forecast capacity constraints in advance.
5 Steps for Automating Root Cause Analysis
This guide details the five steps proactive IT operations teams take to leverage anomaly detection and event correlation to reduce mean time to resolution.