In the modern world and our day-to-day lives, we keep on hearing the word IIoT and how much of a big thing it is. Today, in this very article, we are going to talk about how industrial use of the Internet of Things is transforming the productivity of automation networks.
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What Is the Industrial Internet Of Things (IIoT)?
In the past decade, the industrial Internet of Things (IIoT) is everywhere. It’s like air, everyone has something to say about it, but not many know what exactly it is. To define what IIoT is, we are going to share some real-life examples to make it clear to you how it gets implemented and how it is helping the industry.
See, the Industrial Internet of Things (IIoT) is an industrial framework in which a large number of automated machines or devices are connected and work in a synchronized way with the help of software tools.
Automation Network In Industries
Automation, as from the word, makes it clear, creating something that works by itself on the given set of requirements. Most of the machines that you see in industries are taking help from automation to make the manufacturing task efficient and less time-consuming. Network automation helps in different processes and machinery to help replace human errors.
Automation in the industry was introduced to increase the productivity of manufacturing as machines can efficiently work 24 hours without taking any breaks and rest. But now, as we move to the next date, automation is trying to increase the quality of manufacturing. Right now, in the automobile industry, most of the manufacturers are using robots instead of humans to install pistons in the engine. As a result, the error rate has gone down to 0.000001% from 1–1.5%.
Example 1 — Siemens smart factories using cloud-based IoT system
Siemens is a leading multinational conglomerate company located in Germany. The company desired to create fully automated internet-based smart factories that allow factory managers to collect the data from different machines automatically and analyze it to make the production smooth and more optimized. It works on the same process that BMW is using for building cars with the help of automated machines.
Siemens created an operating system. They named it Mindsphere. This cloud-based IoT system collects the data from all different machines and devices present in the factory and then analyzes it with rich analytics to provide the optimal result from each machine.
Read About: IoT Consulting Services: Everything You Need To Know
Example 2 — Airbus’s digital manufacturing
Airbus recently launched digital manufacturing. Each manager and employee has their tablet or smart glasses to freely access the task and communicate with each other and the infrastructure. The employee analyzes the data and sends the required information to the robotic machine, which then inputs the data and completes its task.
Advantages Of Using IIoT With Your Automation Network
There are several IoT implementations that can help you increase the productivity of the industry. IoT can help you in harnessing the power of smart manufacturing. In addition to this, with the help of IoT, you can easily communicate with your fellow employees and machines and give them the required instructions.
Data Analytics and Management
- IoT can analyze the data from multiple sensors in a much shorter time and inefficient way than a human can do.
- As a result, you get a better understanding of how your machines are performing under the given load.
- Further, IoT can help you detect the problems and issues that may arise in your machines before time, which can cause manufacturing a halt.
- Energy is a significant concern for industrialists. Also, bills can be massive, and there’s no way you can know every detail of how much each machine has consumed.
- IoT can help you reduce data loss as it stores the data and analyzes it right down to each device.
Check Your Machines
- Your manager can easily track the machine that is not performing at its optimal level and is consuming more electricity than required to fulfill; it’s a task.
- Likewise, real-time data can give you some fascinating insights, such as you can measure the off-hour consumption of the machine. And how you can use it more productively.
- Besides, you can use IoT services to benchmark your similar machines and equipment to find which one of them is performing better in the given circumstances and how to make other machines work on the same level.
Reliability and Productivity
- Without reliable production, you are surely getting yourself in significant loss even before putting up an industry. IoT can quickly point you to the machine, which can cause downtime.
- Lastly, the essential aspect of expanding your industry is to improve the quality of the product you are manufacturing.
- According to one of the reports from IDC, an increase in the quality of the product helps you in reducing waste, while lowering the cost and increasing customer satisfaction.
Things To Keep In Mind Before Applying IIoT
See, setting up an industry is a daunting task; it requires a lot of capital and labor hours. If you are thinking about starting from scratch, we would wholeheartedly say you should implement IoT and automate your assembly line. But if you currently have some ongoing production that gets done mostly by human employees or workers. Then you need to give yourself some time to think seriously.
This is because switching from the human production line to a fully automated one, which takes the assistance of robots, requires an initial investment. On the other hand, you need to train your employees to handle these new complex and self-working machines.
To Conclude
The future of the industrial Internet of Things is as bright as the sunny sky in mid-summer. More and more machines are being introduced, which can take the benefit of communicating with its operator and other machines to provide higher productivity.
Besides, you will be reducing the halt time of your production line while lowering the need for human interference in the production process. As a result, your production line will have fewer human errors with a greater productivity rate and higher product quality.
About HashStudioz Expertise in Internet of Things (IoT) Solutions
Industrial IoT Solutions help organizations boost operational efficiency and transform their business need to differentiators. SMART, CONNECTED and SECURE.
We at HashStudioz design application programs and interfaces that are used to provide internet to computing devices. In (IoT) Internet of Things offering, we work on Big Data Technologies, machine learning, predictive analytics, Factory Automation, Process Automation, Smart Lock Systems, Smart Security Systems, Remote Control Systems, Smart Things, Automatic Car Tracking Adapters, etc to name a few. Contact us to know more.
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FAQs
What is the IIoT mainly focused on?
The Industrial Internet of Things (IIoT) has a multi-faceted focus, but its core areas of attention can be summarized into three key objectives:
- Enhancing Efficiency and Productivity
- Ensuring Safety and Security
- Optimizing energy use
- Resource management
- Real-time monitoring
- Optimizing production lines
What is the difference between IoT and IIoT?
IoT Primarily focuses on consumer convenience and improving personal lifestyles. Think smart homes, wearables, and connected appliances.
IIoT Targets industrial applications aimed at enhancing efficiency, productivity, and safety in sectors like manufacturing, energy, and transportation.
What are the system components of IIoT?
An IIoT system, like any complex network, is made up of several key components working together to collect, analyze, and utilize data from industrial environments. Here are the main building blocks:
- Sensors and Devices
- Connectivity
- Gateways
- Data Platform
- Applications
What is the key technology of IIoT?
While multiple technologies contribute significantly to IIoT, there isn’t a single “key” technology. The power of IIoT lies in the synergy of several key technologies working together to unlock the value of industrial data. Here are some of the most important
- Cloud Computing
- Artificial Intelligence (AI) and Machine Learning (ML)
- Big Data Analytics
- Edge Computing
- Cyber Security
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