Industry 4.0 - How to Scale IIoT Solutions with Amazon Web Services

Industrial sites are an untapped well of data—this data securely stored in on-premises devices and equipment such as in proprietary historians. Imagine being able to access this data and improve your production process with real-time data straight from your industrial site!

The amalgamation of AWS and IIoT allows you to build secure, cost-effective, and efficient Industrial IoT (IIoT) solutions. By giving you real-time streaming updates from your industrial sites worldwide, you gain access to both data assets and machine assets.

This article will go over the numerous benefits and hurdles of Industrial IoT (IIoT) enabled predictive maintenance. We will also take a look at how AWS and partner solutions for IIoT-enabled predictive maintenance can lead to more valuable business outcomes for the industry.

What is Industrial IoT?

IIoT can be defined as a network of intelligent devices connected to systems that monitor, gather, move and analyze data. The basic structure of an Industrial IoT ecosystem is made up of:

A collection of interconnected devices that can identify, communicate and retain information
A competent public and private data communications infrastructure
Analytics that can be converted into business information
Data storage space for the data that is generated by the IIoT devices. IIoT devices generate a large amount of data that needs to be stored in a scalable infrastructure.

IoT and IIoT have various technologies in common; they fundamentally differ in terms of functionality. They share the same cloud platforms, sensors, connectivity, machine-to-machine communications, and data analytics, but each of these components are used differently. Unlike the user-centric nature of IoT applications, IIoT applications are centered around increasing production efficiency and improving health or safety conditions.

How to Scale IIoT?

Any new and progressive technological advancement like IIoT is constantly questioned in terms of scalability since it is a crucial aspect that determines the applications of this technology. The aspects of scalability in IIoT that need to be talked about are:

Features for scalability: Scalability is driven by smaller and more specialized processes which collectively make up a more extensivesystem. Features of scalability such as business, marketing, hardware, software, and network need to be considered extensively.
Techniques for scalability: Each device or even a system is scalable in various ways. A well-framed procedure needs to be created to facilitate scalability. Creating a plan for scale during live production use is an essential plan for DevOps.
Research challenges and issues: The fast-paced advancement and progress we witness today come with their own set of disadvantages, such as research challenges and problems while working your way towards scalability.

How to Scale AWS with IIoT

It has already been established that using AWS with IIoT can assist industrial companies in overcoming challenges and attaining business goals. Let’s take a look at how you can use AWS with IIoT.

AWS IIoT makes it easy to reach, manage, and update devices of any type. Devices ranging from the smallest microcontrollers to the most potent gateway devices can be at the tip of your fingertips. Simple sensors that can overlook processes and track key performance indicators can be deployed without changing or replacing existing hardware. This makes integrating existing legacy equipment on the manufacturing floor, such as Programmable Logic Controllers (PLC) and Supervisory Control and Data Acquisition (SCADA) systems, more straightforward than ever.
The built-in device authentication and authorization protect your data and devices that AWS IIoT provides. It will also allow you to audit security policies related to your devices, monitor your device fleet for suspicious activity, and receive warnings when things don’t function properly. This gives you the flexibility to put corrective measures, such as powering off devices into action.
The devices connected to your servers can operate with intermittent Internet connectivity to avoid data loss during unexpected downtimes.
"Plug and play" capabilities let you scale your IoT applications to a large number of devices. With AWS IIoT, you are given the freedom to organize device inventory as per your requirement, keep an eye on your fleet of devices, and manage various devices across many locations from where you’re standing.

Advantages of Scaling IIoT with AWS

Asset Condition Monitoring: The real-time status of your machines and equipment is tracked to understand how it performs in the field thoroughly. Data such as temperature, vibration, and error codes need to be checked regularly to ensure optimal equipment usage. This is difficult to capture manually since it requires technicians to be physically present at the site. With AWS IIoT, you can keep an eye on all IoT data and monitor performance, which in turn increases your visibility.
Predictive Maintenance: Predictive maintenance analytics inform you about the state of industrial equipment, allowing you to identify possible breakdowns before they even happen. An organization that uses predictive maintenance analytics can make equipment survive longer, increase worker safety, and enhance the supply chain. For more details see our journal entry on predictive maintenance.
Predictive quality: As analytics extract actionable insights from industrial data sources and human observations, you can make an informed decision regarding the next step you will take to improve the quality of the factory output. Using AWS IIoT, industrial manufacturers can produce predictive quality models that help them manufacture higher quality products.

Once your devices are securely on-boarded, AWS IIoT allows you to run analytics on IIoT data. AWS IIoT collects, processes, and understands IIoT data quickly and easily so you can make better insights. The AWS IIoT services can be integrated with various Amazon services like the Amazon SageMaker and Amazon QuickSight so you can build machine learning models for your Industrial IoT Data.

It is important to remember that scaling your IoT devices using AWS brings in a boatload of advantages, but it is still in the beginning phases of the transition. Many industrial companies are bridging IoT initiatives with their business, but few have advanced deployments required to reap all the benefits.

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