TABLE OF CONTENTS1. Introduction 2. Introduction 2. AWS Industry 4.0 Partner for Industries AWS Industry 4.05. Conclusion6. About CloudThat7. Frequently Asked Questions Introduction:
The 4th Industrial Revolution (or Industry 4.0) is a stage in humanity’s evolution of production processes. There have been three previous Industrial Revolutions. The first was in 18th-century Britain, with mechanization. The Second Industrial Revolution was a period of improved manufacturing techniques and assembly lines. It occurred in the early 20th century. The Third Industrial Revolution was born in 1960s with the introduction of digital technology. Industry 4.0 was born in 2010 as computers became more powerful and the internet became increasingly interconnected.
Industry 4.0 includes many pillars such as Big Data, Autonomous Robots and Augmented Reality, Cybersecurity, but the most popular ones are AI, IoT & Cloud.
Industry 4.0 uses IoT sensors in conjunction with the AI to improve predictive maintenance and continuous machine health monitoring. Moreover, customized dashboards can be used to remotely monitor the machinery by an expert with minimal human interaction.
It is possible to compare the production, maintenance downtime, and cost of operations of globally distributed industries by comparing them from one location.
Data from manufacturing facilities can also be used to increase production. These data can be gathered by sensors that redirect to IoT gateways’ analyzing tools.
There are many intelligent sensors. The most commonly used sensors are the level sensors and electric flow sensors.
Industry 4.0 is incomplete without intelligent sensors. Industry 4.0 environments must include the modern web-of-things (IIoT), and distributed computing. They are often referred to as IIoT sensors.

The following is the foundation for industry 4.0: IoT Sensors continuously gather data from machines and store it either on Cloud storage or on-premises storage. You can also create dashboards using the data for visual monitoring with domain expertise or predictive analysis.
2. Industry 4.0 with AWS (Amazon Web Services).

Industrial Sensors & SCADA/HDA (Supervisory control and data acquisition/Historical Data Access) collects the industrial data for monitoring purposes.
AWS IoT greengrass, an extension to AWS IoT core provides local commuting and helps to make decisions when it is not connected to Cloud.
AWS IoT core can receive data directly from either Greengrass devices or partner edge devices. What data can we save in logs to S3?
SageMaker and AWS Machine Learning Services can be used to train the model in Predictive Maintenance.
QuickSight, an AWS Analytics Service, can be used to create dashboards and publish reports on collected data.
Industry professionals must be able to receive alerts about safety and production issues at any time. AWS SNS (Simple Notification Service), allows this via email or SMS.
3. Industries using AWS as an industry 4.0 partner
A case study demonstrates how AWS can help improve efficiency at automobile giants.
“Volkswagen Group uses AWS IoT and ML to power its Industrial Cloud. This connects data from more than 120 manufacturing plants to improve production flexibility and efficiency, as well as vehicle quality.
Refer to – Volkswagen Group Innovator (amazon.com).
Another case study demonstrates how Georgia-Pacific optimizes processes and saves millions of dollars each year by using AWS.
“We use AWS data-analysis technology to predict