Subscribe to our Newsletter!
By subscribing to our newsletter, you agree with our privacy terms
Home > IoT > IIoT > IIoT – A comprehensive guide
October 19, 2022
With the rise of inflation and competition in the market, many enterprises are going through a digital transformation in order to stay competitive in today’s market.
For such companies, the Industrial Internet of Things, or IIoT, is indispensable as it helps create intelligent factories and a higher market share. Most enterprises have already implemented connectivity solutions to save money and provide more optimized operations.
But what is IIoT exactly? How does the concept help digital transformation to increase business and generate higher operational performance? Is it inevitable now? How can manufacturers utilize these things to achieve their business objectives?
You will get answers to these questions and more below. This comprehensive guide will also discuss common risks and advantages attached to IIoT.
IIoT is defined as the use of IoT in the industrial field. It connects machines and data management in smart factories to improve productivity and quality. In simple words, it refers to IoT used in the industrial world.
IIoT collects data from sensors, actuators, intelligent equipment, and systems. It delivers critical, live insights to end users, operators, and industrial managers. Once the data is collected, it is analyzed and configured in a cloud server.
Live insights can help find descriptive and predictive solutions in robotics and other advanced applications. It can even force machines to make semi-autonomous or even autonomous decisions. As a result, the equipment becomes more optimized and less prone to human error. Not only this, real-time or live insights also help improve worker safety, reduce costs, and enhance quality.
IIoT uses AI and other machine learning software to connect platforms and devices. It creates a more agile cybersystem that works efficiently and improves its capability.
Statistics depict that by 2025, over 30 billion devices will be connected to IoT worldwide. The manufacturing industry will play a big part in creating these devices and business models to increase profitability. This also indicates an increasing transformation for the Fourth Industrial Revolution that is upon us.
With machines’ laboring, processing, and maintenance, manufacturing is an ideal industry to use machines’ data. Data is always valuable, and business intelligence programs and algorithms can be manipulated to get insights from it. Plus, data is not only about the numbers but also what these numbers can do with insights.
With IIoT, happens on the factory floor with individual machines and in production cycles becomes more visible. Automated processes and predictive maintenance are just the start of what can be done with the data.
The future of IIoT will be about the sensors that analyze and transmit data. It will also include:
So, in terms of importance, IIoT should be seen as enabling modifications to the building processes that the consumer values most. Being quick to market, custom production, and more manageable customization levels, IIoT has a bright future.
IIoT is a network of smart devices connected to systems that monitor, collect, control, exchange, and analyze data. Simply put, it is a network of physical objects that collects and exchanges data to monitor and control industrial processes.
In the IIoT infrastructure, the data is collected through sensors, actuators, and intelligent nodes. This data is then controlled by the IoT interface and intelligence gates. Later, the information is transferred to the IoT platform and local server for data processing, analysis, solutions, and automated database process.
IIoT utilizes advanced machines and live analytics to use the data that “dumb” old devices generate in the industrial field. This information can later be used for predictive maintenance and maximum efficiency in business processes.
The philosophy behind IIoT is that advanced machines are better than human beings at capturing and analyzing data in real time. They are also better at delivering critical information and are used to drive business decisions more effectively and accurately.
IoT should not be confused with IIoT.
IoT is a wireless or wired transmission to control, link, and send services to communication devices in an area or business. Smart cars, home appliances, or thermostats are linked to the internet. IoT generally gathers and transfers data.
On the other hand, IIoT is a cluster of automation systems, sensors, analytics platforms, and equipment communication. It is used to manage and improve working within an industrial world.
In IIoT, data gathering enables the user to enjoy a customized experience. Internet connectivity is a digital instrument that manages an ecosystem created to improve working within the manufacturing industry.
Every industry eventually has to drive its stakeholders to move towards newer technologies. This move helps decrease costs and increases efficiency. It is the same in manufacturing as well.
Manufacturers are generally risk averse. It makes it harder to convince them to leap into the era of cognitive IoT-centric manufacturing. However, as the first firm leaps, others more easily follow.
IIoT has a significant role in the manufacturing industry. Various machines have embedded sensors that optimize most of the industry’s operations. For example, if a system breaks down, the connected sensors locate the issue and trigger a message to the manufacturer.
Below are some critical market pressures that are driving manufacturers toward IIoT:
1. Cost reduction in production
2. Faster time to market
3. Exponential revenue growth
4. Last-minute changes to orders
5. Bulk production of individually configured products
IIoT solutions are best designed for manufacturers so that they can start using existing data better. They do so by assembling and improving production data on the spot. Generally, this creates numerous use cases, like predicting trends based on analyzing past data.
The IIoT-connected machines capture and communicate data more accurately and consistently than ever. This enables organizations to break open data silos and access information at every level.
With IIoT, operators, engineers, and supervisors can get visibility into production. Engineers can take cues from the operators, process, and machine data to achieve continuous efficiency and improvement on the plant floor. Additionally, management can make informed business decisions backed by data.
Below are some advantages a manufacturer can have by using an effective IIoT solution.
Humans are slow and prone to making mistakes when interacting with equipment. However, with IIoT, this is not the case. Live data is collected and analyzed, and manufacturers make decisions guided by data.
These advanced analytics are also helpful in spotting trends that are not otherwise highlighted. Also, with IIoT solutions, a manufacturer can optimize its production process and enterprise performance.
Advanced analytics can also help with capacity utilization and labor. These optimizations best serve the overall performance of an organization.
Today, inventory management has become more costly than ever. With rising inflation and inventory-keeping costs, manufacturers look for a solution to minimize this cost.
For this, IIoT solutions are recommended as they further extend the gathering of data on the production floor. The IIoT system takes data from enterprises via the devices used for conveyance.
Finished goods are then monitored, and their availability is included in the analysis on the platform. Here, the goods are sent to finance software for precise management of inventory.
Many manufacturers use quality testing programs for inspecting, auditing, and preventing. The slightest variation in the manufacturing process can increase the scrap rate. This mostly happens in industries where automotive, aerospace, and medical parts are customized to exact tolerances. It can also cause a security lapse if the user passes the domain inspection.
However, if IIoT devices are used, there is less of a chance of this happening.
This precise measurement cuts the temperature, weights, and other such information using IIoT devices. It also enables operators to check and make adjustments before production units are out of order because of certain parameters. As a result, this saves time, labor, cost, material, and equipment deterioration.
Data can also be collected for motor frequency. It helps manufacturers to design machine learning programs to highlight failures that can lead to major losses. With IIoT devices, multiple adjustments are designed to be performed semi-autonomously or autonomously by the machine.
IIoT systems help reduce the costs of manufacturing companies. The systems’ ability to find and correct errors saves material, cost, and downtime. They are also helpful when analyzing data, which enables them to spot trends humans can make. The analytical strength renders decreased operational costs and process optimization.
In addition, connected devices also yield insights that enable enterprises to design predictive maintenance programs to prolong equipment lifespan, lower downtime, and minimize the price of additional parts.
Cost reduction is the critical driver for manufacturers to adopt IIoT. With sensor-focused machines autonomously gathering and analyzing data on machine health and performance, companies can use it to reduce maintenance, operation costs, and repairs.
89 percent of failures are random and thus very difficult to avoid with only planned preservation. The obvious downside is that the over-maintenance of assets can be costly and disruptive to a stable system.
However, using IoT for maintenance can optimize asset availability, decrease costs and increase productivity. Predictive maintenance is also valuable for asset organizations as it identifies future tools’ degradation or loss before they occur.
Company equipment is the most expensive for industrial companies. With IIoT, predictive maintenance suggestions, real-time analysis, and secondary tools, manufacturing enterprises can design strategies for managing asset health in a single enterprise or factory.
New machine data programs can best monitor equipment statistics to spot machine health, equipment life issues, and other variables. They can also suggest courses of action or remedies in order to keep assets in working order.
Several changes in a product enable it to gain popularity in the market quickly. The changes can include individually customized assets and niche markets, whether online or in store. Talking about the products you buy that are accessible to the people enables you to personalize certain aspects such as clothes, shoes, food, vehicles, furniture, etc. It has never been so easy to sit in your room and order a pizza, with a choice of everything from the sauce to the type of crust and cheese.
This customization gives you a sense that this is different for you, even if other people can get it. The creation process at the back needs an uplift in variety and design without any increase in cost.
So, with the use of IIoT, the extracted data from machines and systems is translated into the required context to figure out production schedules, quality, and price to enable effective decisions. Additionally, live visibility enables for a more efficient and fluid supply chain so that your ordered product comes out perfect every time.
There are a number of risks and issues attached to IIoT. The major ones include security, cost, and experience. Below, we will discuss these challenges and risks in detail.
The price of implementing new IIoT technology is high. Like other industries, manufacturing also needs to use the latest technology in traditional IT. In the past, the infrastructure, maintenance, and training were considerable. But today, simultaneously obsoleting old systems and getting new systems up and running is daunting.
There is also a lot of confusion regarding the rate of interest (ROI). Even if prospects are correct, the advantages of IIoT will overshadow the cost. However, with connection devices’ rapid growth and software development, investment costs will fall sharply in the future.
IIIoT is a new technology. Hence, there are not enough professionals who understand the changing landscape of Industry 4.0 and offer perfect IoT development.
Also, there is a shortage of training and experience for professionals to help companies deploy IoT efficiently.
Also, the manufacturers and IT staff usually deal with IIoT with more caution, as it requires extensive training. Staff also hesitate because they have to undergo rigorous training and experience. They also need advanced analytics and digital tools for their work, adding more costs for the manufacturing company.
However, this risk can be minimized as there are platforms that can increase the variety of the current IT structure. These platforms can communicate with current cabling and old hardware while giving new connectivity like cellular or Wi-Fi to increase the influence of the network.
Security is the primary concern for all IIoT adopters. Security issues can occur due to unsecure web interfaces, mobile interfaces, weak encryption, and network services. The security worries are justifiable, as almost half of the important infrastructure operations work with old software.
IIoT security has both good and bad sides. The good side is that IIoT has cloud security. It means the service and security providers who provide these platforms have improved their security over recent years. The bad side, however, is that security issues still occur due to the companies’ weak or common passwords, for example. But they do not occur because of the cloud provider’s service.
It means that security may have been a priority but maintenance and access handling depends solely on guidelines followed by enterprises. These companies usually handle security with an in-house system which is not as safe as it should be.
Most manufacturing companies use a proprietary, hybrid system with various hardware and software solutions. This lack of standardization is a hurdle to successfully adopting IIoT. It often leads to an increase in the costs of purchasing and setting up software solutions for the company.
This lack of standardization has led to a boom in the industrial sector’s requirement for IoT app development solutions. So, it has become a massive challenge for manufacturing companies and needs to be addressed.
Numerous industries use IIoT devices and technology. Some of the most common industries are listed below.
The automotive industry is an industry that rapidly embraced the fourth industrial revolution. This industry combines IIoT with other latest technologies like robotics into innovative, intelligent factory environments.
Today, the automotive industry indulges in software. IIoT has created an environment of manufacturing and production directly attached to sales, supply chain, marketing, and financing. It yields a full picture of manufacturing conditions while getting connectivity data and linking them together to increase value.
This industry has vast resources stretching far beyond the point of production. The IIoT capability to deploy deep analytics to analyze energy consumption and predict trends results in better production and energy management.
Digital tools that enable electric utilities to visualize their network in terms of performance and health have been game changers.
CNC machines are usually discrete manufacturers that produce unique items. There are some faults related to installation time, process optimization, settings, labor training, and more.
Big data insights and IIoT applications can make a huge difference in the probability of CNC machines. A CNC machining company can find ways to reduce costs and maximize capacity. They analyze data from sensors, frequency data, retrofitted devices, and other such input.
It can maximize capacity through better processes, predictive maintenance, and improving tool life.
After reading all the benefits and risks attached to IIoT, you might be wondering about the future of IIoT in the manufacturing industry. If yes, keep reading.
Although IIoT has gained notable advances in research, customer experience, and production, technological achievements are still on the horizon. Small businesses and global enterprises enjoy the opportunities for better internet communication and low cost management.
Companies that deal with product development are seeing more benefits when using IoT devices. IIoT is helping to lower operational costs and improve performance within the production process.
Similarly, IIoT is developing trends across connected utilities. As IoT as a service, it enables third-party providers to deal with all IIoT devices with reference of facility. The most compelling prospect of IIoT is the combination of edge and cloud computing. It is evolving so that facilities will collect statistics from any source, no matter how it is connected, in one location.
So, all in all, IIoT is the most promising technological trend today. However, multiple enterprises are still hesitant about it or are in the initial stage of accepting and adopting.
This tells us that the future of IIoT is not bleak. In the future, there will be more security, increased connectivity, and reduced deployment costs. IIoT is expected to grow by 16.7% from now until 2027 and hit an overall market share of $264 billion.
With more software solutions and device manufacturers emerging, adoption costs of IIoT will automatically fall. However, as enterprises realize that high productivity optimization, the cost and profitability can quickly turn with companies seeking a competitive advantage.
There is no denying that the future of IIoT and IoT is bright across industries. Although there are several barriers to adoption, it does not mean that IIoT is not worth the risk.
To keep up with technological advancements, every manufacturer will have to turn toward it sooner or later. So, contact us today if you are looking for an IIoT development service or want a company to take care of your IIoT process.
September 08, 2023
August 10, 2023
July 10, 2023
June 23, 2023
May 31, 2023
May 11, 2023
May 09, 2023
April 26, 2023
Previous
Startup brings Machine Learning to sensors
Next
IoT boosts cargo and vehicle tracking in Brazil
