While the term IIOT or Industrial Internet of Things may sound like a very complicated technical terminology, it is simply an extension of what you have experienced in your daily life. The Internet of Things (IoT) is a system of interconnected objects that are connected to the Internet and can collect and transmit information over a wireless network without human intervention. You may not know how they are used in the commercial world, but I am sure you will come across them daily. Does it still look like something weird? Look at this example.
What is that device you wear in the morning when you go running? Your fitness group, right? The fitness bracelet you put on in the morning is an example of a device that uses the Internet of Things. First, it monitors your exercise, sleep patterns, and other things like your heart rate. Then, it uses the data to train algorithms and draw meaningful conclusions.
Another example is the voice assistant, which has gained popularity recently. It is compatible with other devices, such as your mobile phone or laptop, and collects and transmits data.
You may have already figured out the functionality of your home, but perhaps you’ve wondered how the Internet of Things can be used in industry. They probably don’t need voice assistants or fitness bands there.
IoT is much broader than a few common household appliances. They are just the tip of the iceberg. The Internet of Things is widely used in all areas: factories, government sectors, residential buildings, commercial properties, research and development centers, or manufacturing units. Everyone is slowly but surely moving to this new way of life.
The Industrial Internet of Things (IIoT) refers to the extension of the Internet of Things (IoT) for use in industrial areas and applications. It uses intelligent sensors and actuators to improve manufacturing and industrial processes. It is used in many industries worldwide to improve efficiency, processes, and safety. Let’s see how the implementation of IIoT in the industry is proving its worth:
Best Use of Resources
Particularly in production companies, it is about the optimal use of resources. Whether it is material, personnel, or machine time: Every manufacturer wants to maximize its productivity. Using IoT tools in their manufacturing processes helps optimize production processes, identify wasted resources and identify opportunities to improve production efficiency.
Cost reduction
In the past, when equipment stopped working or even broke down, it was time for maintenance and repair in most production units. Unfortunately, maintaining your machines to this endpoint increases costs rather than maintaining them properly. After all, it is more expensive to repair something when it is broken than to maintain it regularly.
The production process would also be interrupted in the event of failure of certain key equipment, leading to a reduction in output.
With IIOT solutions, companies can minimize this downtime by using predictive technology. These technologies make it possible to anticipate problems and solve them before paralyzing the production process. For example, the use of alarm and notification software helps to send advance notifications to interested parties when problems arise.
Improvement of safety at work
Working in factories or in dangerous workplaces requires extra safety. It is always best to closely monitor the functions performed to ensure compliance with the security protocol.
For example, IP cameras use thermal imaging to detect events, such as an employee not wearing a helmet, and send an alert.
The use of sensors by workers on hazardous equipment serves as a warning by detecting sounds, temperatures, or frequencies near certain equipment and issuing warnings.
Production automation
Industrial automation controls industrial processes and machines using logical programming commands and powerful hardware. This minimizes the need for human intervention in industrial plants.
This method is becoming increasingly popular in the processing industry and contributes to the efficiency of the production process.
Product quality and standardization
Manual quality control of every product and every standard is a time-consuming, labor-intensive, and expensive task. Although it takes time, its importance should not be underestimated. The quality of a company’s products is its main selling point and sets it apart from others. However, manual verification is always subject to errors and misunderstandings on the part of the verifier. IoT solutions are the answer to this problem.
IoT sensors can receive information about standard product specifications and quality, which can match the product under study. This would free up a large proportion of the staff assigned to this task for other production processes, thereby increasing productivity.
Storage and logistics
IIoT tools can be used to decide on the optimal inventory and storage requirements in terms of order frequency and inventory service levels. Moreover, different types of products require different storage conditions. Information on temperature, time, humidity, etc., can also be defined and standardized with IIOT tools.
Optimizing logistics by tracking downtime, volumes, routes, and locations in industries such as trucking and transportation are becoming increasingly popular. All this data can be tracked to create an optimal supply chain, reduce costs and maintain an efficient process.
IIOT is a promising tool that is changing the way industries work worldwide. These tools have a significant impact on the efficiency and safety of production processes in all industries.
Frequently Asked Questions
How will the Industrial Internet of Things improve productivity?
A: IIoT improves productivity, efficiency, and decision making, reduces costs, and enables an organization to gain real-time insights and operational benefits. Some of these benefits: Reduces machine downtime.
Why is IIoT important?
A: IIoT is an important part of the fourth industrial revolution or Industry 4.0. IIoT offers the opportunity to harness the power of smart machines and real-time analytics to harness the data that machines in industrial environments have been producing for years.
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