What is Industrial IoT (IIoT)?
The Industrial Internet of Things (IIoT) and the Future of Industry 4.0
With 5G, machine learning, artificial intelligence, and other new technologies available on the market to use today, we’re now beginning the fourth industrial revolution (commonly named Industry 4.0).
Industry 4.0 is a new era of the industrial revolution that focuses on connecting machines to databases, automating processes, machine learning, and real-time information. Previous industrial revolutions focused on removing manual labour and replacing it with steam/water-powered engines (Industry 1.0), electrical machinery and the mass production model (Industry 2.0), and computer-driven technologies (Industry 3.0). Today, Industry 4.0 focuses on interconnecting physical machines and databases using Industrial Internet of Things (IIoT) technologies allowing for a more detailed and extensive picture approach to manufacturing. Using Industrial IoT within a manufacturing setting will enable users to manage every production line area better with real-time data.
As Industry 4.0 continues to happen, IIoT will play a significant role within the business setting and significantly impact how businesses operate. We’ll see many organizations transform traditional manufacturing operations using IIoT to enhance production lines and increase profits.
What is Industrial IoT?
The Industrial Internet of Things (IIoT) is a collection of linked sensors, machines and devices connected to computers’ industrial applications. Organizations take advantage of superior data collection by connecting all these devices, sensors, computers, and machines. The collected data is then sent to a centralized cloud system, where it is exchanged with other devices and end-users to improve productivity and efficiency levels (Source: Science Direct).
The Industrial Internet of Things (IIoT) uses machine learning, big data, real-time analytics, and machine-to-machine communications (M2M) to help corporations and enterprises create better processes for industrial development. Machines using IIoT technologies are better at capturing/analyzing data in real-time and communicating important information than traditional human processes that are often slow with biases and errors.
IIoT vs IoT
Different but somewhat similar, IIoT extends from the Internet of Things (IoT) technologies. IIoT brings IoT technologies into the industrial sector – hence the added “I” at the beginning.
IIoT leverages IoT technologies in the business and industrial sectors. Like optimizing your home with smart lights, connected thermostats, and other smart home devices, the industrial sector also uses IoT technologies to make their processes, insights, and outputs “smart.”
Although both technologies use the same standard protocols, IIoT’s goals, applications, scalability, and technical details differ from IoT’s.
Compared to IoT’s focus on consumer convenience and daily household tasks, IIoT’s main priority is monitoring outputs. Industries using industrial internet of things technologies want to reach maximum efficiency, productivity, and optimization.
Scalability is an essential difference between IoT and IIoT. Industrial IoT is much more scalable than IoT, allowing thousands of new sensors to connect to various robots, machines, controllers, and other devices (Source: Kellton Tech). Full integration makes IIoT successful in data collection and analyzing exchanges between devices, machines, and humans. IoT, however, only connects to a limited number of devices and sometimes may only connect within a specific line of products.
Because of IIoT’s need to scale with the industry, it must be more technical and detailed than other IoT deployments. IIoT uses complex devices and systems to assist existing manufacturing, supply chain, and business models, meaning setup may need to be customized specifically to a business’ current operations. Although customizable to an extent, IoT isn’t as detailed and doesn’t require a complex setup to start. Most IoT devices are easy to install and operate over your home’s Wi-Fi.
If 5G is here, will we still need Wi-Fi?
How Industrial IoT Works
A standard IIoT system shares data between hundreds of thousands of devices and networks.
Within the system, there are four main parts:
- External devices that can communicate and store information about themselves, their productivity, and workload (these could include sensors, robots, remote devices, computers, driverless vehicles, controllers, and more)
- A data communications infrastructure that allows data to be transferred between devices and the cloud (can be public and/or private)
- A central cloud system that stores all the data generated by the various IIoT devices
- An Application Programming Interface (API) or other applications to create business information from raw data collected from IIoT devices
In a nutshell, external devices are the devices that do the work and record data on themselves. The communications infrastructure then collects the data from the devices, bringing them to other external devices and the cloud—the cloud stores all the raw data. A worker then uses an application to pull the relevant data needed.
Although laid out simply here, attaining this network can be a challenge. With so much data being transferred between devices, the cloud, and people, it can overload a network without the right equipment and communications layout. It’s also important to note that not every IIoT network looks the same. Businesses and organizations need customized networks based on their current goals, outputs, and product strategy.
With many different use cases, Industrial IoT’s benefits vary based on industry. Specific industries like the healthcare sector focus more on using IIoT’s benefits to monitor a patient’s health. In contrast, the construction industry uses the same technology to improve a building’s safety and security (Source: SSRN).
IIoT benefits often depend on what resources are currently in place at an organization and the organization’s primary objectives. Once these two are identified, it’s up to the organization to decide what benefits they want from IIoT and the engineers to build the system.
Industrial IoT’s benefits rely on the people creating the system and their available resources.
Common Industrial IoT Benefits
Although different organizations require different outcomes, there are expected IIoT benefits that spread across various industries, including:
- Increased Productivity and Efficiency
- Cost Savings
- Positive Working Conditions and Worker Safety
- Improved Agility
- Real-Time Monitoring
Increased Productivity and Efficiency
One of the primary benefits of IIoT is increasing productivity. IIoT increases productivity through optimizing and automating processes already set in place. Using a variety of intelligent sensors, devices, controllers, and more, organizations can build systems to automate and speed up current processes. Increased productivity is manufacturing’s focus – getting more products out onto the market faster.
Although investing in an IIoT system can be an expensive up-front cost, it pays off in the long run. Organizations that invest in IIoT systems can enhance productivity/efficiency, increase quality control, manage inventories easier, reduce labour costs and save on energy bills making IIoT a robust investment. Enlighted (a Silicon Valley-based company) claims to have reduced lighting bills by 60 to 70 percent and cooling bills by 20 to 30 percent by investing in an IIoT-based sensor system (Source: Technative).
Positive Working Conditions and Worker Safety
Worker safety has improved over the past few decades, but there’s always room to improve.
Each sector has its own safety needs, and it’s IIoT’s job to assist in improving them. Some sectors, such as mining, would benefit from remote access and control. Instead of sending humans down into dark and dangerous areas, machines go down to perform the job at hand. Other sectors use IIoT to detect changes in health. Military commanders could use IIoT devices to monitor the health of their combat professionals in the field, observing their body temperature, heart rate, and other indicators.
IIoT also helps worker safety by providing information from sensors, like air quality. IIoT devices can give insight into worker safety data to see any trends and identify actionable next steps (Source: ISHN).
Productivity and efficiency are essential in an organization, but agility is crucial, especially as changes emerge. Incorporating Industrial IoT into an organization along with big data, AI, and cyber manufacturing systems creates a flexible and scalable approach to improve agility.
IIoT’s ability to collect, organize, and even predict data quickly makes it agile. Data from IIoT devices are collected in real-time and organized so decision-makers can decide on an outcome right away. Using IIoT within a system also provides decision-makers with predictive analytics allowing them to see what may happen in the future based on past trends.
Real-time monitoring in an industrial setting allows management to see what is happening right now. Compared to traditional monitoring (where data on a single day is sometimes not seen for a few days or even weeks), real-time monitoring allows management to make quick changes. There’s no point in making decisions based on old data.
Monitoring efficacy in real-time with IIoT also allows managers to get a 360-degree view of how operations are running. Suppose a manager notices that a robot or controller isn’t operating correctly. In that case, they can not only send someone to fix the problem but also understand how that affects the operation chain as a whole.
Other benefits also include:
- Predictive Maintenance: Big data and AI can predict when devices need to be maintained.
- Quality Management: Having an IIoT setup improves product quality management.
- Supply Chain Management: With real-time and big data, managing supply chains is more straightforward.
- Zero Defects Manufacturing: Having robots and other devices on the production line reduces defects in manufacturing products.
With numerous benefits, there are also challenges with integrating IIoT.
Common Industrial IoT Challenges
- Data Integration Challenges
- Lack of Job Market Skill
- Little Standardization
- Connecting with Older Technologies
IIoT Data Integration Challenges
With massive sets of big and raw data being collected from thousands of sensors, combining all this data to create meaningful insights is a significant challenge for organizations. How can organizations collect, organize, and make decisions based on all this information?
Big data analytics projects typically use Extract, Transform, and Load (ETL) – a traditional IT methodology. When asked to provide data intelligence from multiple systems, data systems architects extract the data and place it into a familiar location, then transform the data by normalizing it and cleaning it. Finally, they load it into a common site for decision-makers, hence ETL.
Unfortunately, ETL often stumbles within the significant complexities of IIoT. Since the data collected from IIoT is massive, traditional systems like ETL cannot handle it well, and ETL’s manual processes and rigid architecture can’t keep up with IIoT’s speedy and customizable needs (Source: Industry IoT Consortium).
The reality is that IIoT requires automation and, in most cases, the application of AI to be fully optimized. AI will enable real-time alerts to the collected data and flag irregularities and potential issues as they arise.
IIoT Cybersecurity Challenges
The sheer volume of critical and sensitive data that Industrial IoT produces makes it a large target for incoming cyberattacks. If a cyberattack were successful on an IIoT setup, the damage could be catastrophic.
Take, for example, TSMC – the Taiwan Semiconductor Manufacturing Co in 2018. After a WannaCry malware variant entered the system and spread to machines on the production line, TSMC had to shut down three plant locations for three days. This incident was estimated to cost TSMC NT $5.2 billion.
An onsite operator forgot to scan a new piece of equipment before setting it up on the company’s intranet. As soon as the computer booted up, the virus began to do its damage (CommonWealth Magazine).
Since IIoT may have thousands of different sensors, machines and other equipment installed on the system, there are plenty of opportunities to attack. As we can see, it’s easy for an attacker to take advantage of a simple mistake, and attackers aren’t just external either. Inside jobs could easily happen, making securing an IIoT system even more of a challenge.
The best cybersecurity plan is a predictive one. While implementing IIoT, do so with security top of mind.
Lack of IIoT Skill in the Job Market
Just as IIoT is a leading competitive differentiator in the market, professionals who can help build IIoT systems are in significant demand. 94% of companies have at least one Industrial IoT project in mind (Source: Mordor Intelligence). However, there’s a lack of skilled workers currently available.
Building an IIoT system requires many different experts. Data scientists, cybersecurity specialists, industrial networkers, system designers, AI experts, cloud architects, robot designers/engineers, UX/UI specialists and maintenance workers are all needed to build an IIoT operation. Still, many of these job titles are scarce in today’s market.
“Engineering knowledge” is in high demand, especially for organizations interested in building IIoT systems.
Companies are looking to overcome this challenge in a few ways. One common tactic is looking to level up the skill base of staff through education and training.
Looking to improve your tech credentials? Build your skillset with CENGN Academy!
A new pair of wireless headphones need to be:
- Compatible with a modern smartphone, desktop, laptop, TVs, gaming consoles, and other devices
- Chargeable using a USB cord that connects to a computer and wall outlet
- Functional with various apps (whether on the phone or through a website)
As new technologies come into the world, they need to connect with the current ecosystem of today’s technologies to function correctly. Unfortunately, standardizing IIoT is unforeseen.
Companies buying into IIoT today risk building up an operational IIoT setup that may not be compatible with future technologies.
Take, for example, Apple. If you own a MacBook, integrating it with your iPhone 13 to work together is easy. Each system runs on Apple’s iOS operating system, and both devices were designed to work together.
However, if you want to integrate your MacBook with a phone that runs on Android’s operating system, it will be challenging. If you’re lucky, you might find an app or converter that will allow cross-integration.
This Apple example is what might happen with IIoT devices. In the years to come, organizations may not have the opportunity to buy different pieces of their IIoT system from other companies. If they want an Industrial IoT setup, they’ll have to buy all the devices, robots, operating systems, and cloud setup from a single company.
But there’s also another situation that could happen.
If the marketplace allows integration across various brands and devices, we might see a similar dynamic in IIoT as today’s smart home IoT devices and their cross-integration.
Buyers have lots of options to choose from to customize their smart home. Although buyers must choose between having a Google Home or Amazon Alexa as their central smart home hub, most other brands provide cross-functionality. They can operate together (buying a lightbulb from one brand and a doorbell camera from another will work on your smart home setup regardless of the two brands).
As Industrial IoT continues to mature, we can assume organizations will eventually realize the exact requirements for integration. Unfortunately, for now, it’s not possible to see if integration and cross-functionality will work with IIoT devices in the long run. This leaves organizations at risk if they buy into IIoT as early adopters.
Connecting to Older Technologies
Integrating older technologies with newer ones comes at a challenge. Have you ever tried to set up a VHS player with a smart TV? It’s impossible unless you have an RCA to HDMI converter.
Well, the same goes for connecting older machines to an IIoT setup. According to the International Data Corporation (IDC), almost 85% of installed devices and sensors in working condition can’t connect to the internet (Source: SSRN). On average, industrial equipment is usually 20 to 25 years old, but some equipment is much older, going up to 50 years (Source: HPE).
So, how do organizations connect their older machines and equipment to today’s IIoT setup?
If they can’t fork over billions of dollars to enhance their manufacturing equipment, a few options include:
- Smart Sensors: Can be deployed on older types of equipment to track real-time analytics, whether it be environmental conditions, manufacturing progress, or more
- Retrofit Kits for Older Machines: Whether designed for specific machinery or a broad range of machines, retrofit kits are available on the market that enables older equipment to connect with IIoT sensors and setups so users can manage production and track analytics
- Edge Gateways and New Legacy Capabilities: Using edge hardware, these gateways are installed on the factory floor and supplied with industrial and IT interfaces. These gateways perform various functions, such as translating protocols and connecting equipment across the factory floor to databases and applications.
- Video Cameras: Installing video cameras on the production line and connecting the cameras with IIoT infrastructure to detect anomalies is also another way around connecting older equipment
IoT and IIoT Projects at CENGN
Focused on driving global technology innovation within Canada, CENGN allows small and medium-sized Canadian businesses to test and validate their promising technologies on an enterprise-grade testbed, removing production barriers to commercialization and speeding-up market growth. CENGN works with various tech solutions, such as cybersecurity, network applications, artificial intelligence, IoT, etc.
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