The Industrial Internet of Things (IIoT) is a variant of the Internet of Things (IoT) designed to handle the needs of more important industries. The only difference between the two is that IoT is primarily intended for consumer use, while Industrial IoT is primarily intended for industrial purposes, such as manufacturing and large-scale management systems.
"Today, we can analyze the state of our plants in real time, which allows us to respond faster to opportunities that arise in the marketplace and helps improve product quality and asset availability," says G Conary, senior vice president.
There's a lot of truth to this: in less than 20 years of history, the IIoT has been an interconnected instrumentation system used in applications and industries around the world, and is proving to be a great example of the evolution of the IoT and basic control systems.
What is the Industrial Internet of Things?
As we have already mentioned, the Industrial Internet of Things (IIoT) is a subtype of the Internet of Things (IoT). But to better understand IIoT, let's start with the general concept of IoT.
IoT is a system of corresponding computing devices, machines, objects, and people that can transmit data over a network without the need for direct interaction or an HMI (Human Machine Interface). The IoT usually focuses on consumer technologies such as wearable technology, telephony, television, home appliances and automation (often referred to as "smart home technology").
So how does this translate to the Industrial Internet of Things?
IIoT refers to the networking of interconnected sensors and instruments in industrial applications of computers. This sector is responsible for data collection, exchange and analysis in automation, factories, healthcare, machinery, transportation and urban planning. Hence the name: the system is most commonly used in industrial environments.
Impressively, by 2030, IIoT is expected to add $15.7 trillion to global gross domestic product (GDP) from AI alone. That's because major companies and industries will increasingly use AI software - thanks to systems like IIoT.
How IIoT Systems Work
IIoT systems have a specific architecture that is directly related to how they operate. The operation is divided into three layers, which are:
- Application layer: user interfaces, such as screens and tablets;
- Network layer: communication protocols such as WiFi and cloud computing; applications and software that convert data into information
- Sensing layer: hardware, including CPS, machines and sensors
These internal systems communicate with each other when commands are issued. This simple architecture is the brains behind IoT and IIoT technologies, and can offer a plethora of advantages and benefits to manufacturing.
Benefits of using Industrial Internet of Things
Like IoT, IIoT is very helpful in saving time, saving money, and increasing productivity. Without this system and evolving elements such as artificial intelligence, manufacturing plants would not be able to meet the needs of consumers everywhere.
Benefit #1: Extended Connectivity
Thanks to its extensive network, applications can share information with users, customers, and other systems in seconds. This extended connectivity within the industrial workplace allows businesses and companies to make better decisions.
Benefit #2: Cost Savings
With communications better than ever, the IIoT can perform a variety of cost-saving methods by increasing production time, performing automated tasks, and performing necessary repairs and maintenance work to avoid any unexpected costs. Computers that can target and respond to internal system issues help save production time by eliminating the need for human operators.
Benefit #3: Efficient Manufacturing
Just-in-Time (JIT) manufacturing reduces response time between the customer and the organization, increases collaboration, provides information about delivery schedules, and tracks basic metrics such as throughput, output, and failure rates.
Benefit #4: Automated Maintenance
Predictive maintenance (PdM) predicts when a machine or system is likely to fail and when repairs may be needed. This prediction helps prevent unplanned maintenance checks and minimizes the cost of spare parts and the time spent repairing machines, so more time can be spent improving productivity and reducing unnecessary repair costs.