Examples of IIoT Applications
By shaping new concepts and business models, the IIoT is bringing more efficiency and capacity to automated systems. Take a look at some of the ways the IIoT is revolutionizing the manufacturing and automation sectors.
See our previous articles covering the IoT and cloud:
- Cloud Computing and the Industrial Internet of Things
- IoT Software Distribution Models: Cloud Based and On Premises
- Components of the Industrial Internet of Things
- Challenges and Best Practices Implementing Industrial IoT Solutions
Undoubtedly, the Industrial Internet of Things (IIoT) is revolutionizing the manufacturing and automation sectors. In addition to bringing more efficiency and capacity to automated systems, the IIoT is also paving the way for new concepts and business models. This article will review some of the business models that are gaining the most from introducing IIoT technologies.
Predictive maintenance is perhaps the most recognizable and tangible application of the IIoT that can be found today. The success of IIoT embedded in maintenance practices is thanks to the proven high rate of return on investment. Manufacturing businesses spend large amounts of money each year on preventive maintenance, and IIoT is crucial in reducing these expenditures.
Figure 1. The IIoT has helped make predictive maintenance possible with its IIoT-enabled sensors and the cloud. Image used courtesy of Canva
Historically, maintenance programs have relied on the preventive model. Preventive maintenance is based on a predetermined schedule of upkeep tasks on industrial equipment.
However, the biggest problem with working with a set maintenance schedule is that, in many cases, time does not necessarily correlate with wear and machine conditions.
Let’s take a simple hypothetical example. Suppose my manufacturing plant consists of ten assembly lines and I schedule maintenance on a rotation basis. What happens when one or two of my lines are not producing for a certain amount of time for other reasons? Let’s say demand was down for the products made on these lines, so they had to be shut down temporarily. Based on my schedule, I would still perform maintenance on those lines even when the machines were not used as much as on the other lines.
The answer to this problem is predictive maintenance. This method employs data analytics and algorithms to try to predict when failures will occur. Maintenance tasks can then be programmed using these predictions, thus directly addressing potential failures that preventive maintenance could have otherwise neglected.
But where is IIoT in all of this? The answer is that predictive maintenance requires large amounts of data from machines and processes, and IIoT is the key to gathering that data. IIoT-enabled sensors installed at strategic points provide input about circumstances and incidents that are not typically monitored by traditional control systems. Machine vibration, temperature, and humidity are examples of these incidents that, if left completely unchecked, are likely to cause unnecessary wear and damage to industrial equipment.
The data gathered by IIoT field devices is sent to the cloud where an application then processes it and produces meaningful reports and actionable information. There is also the possibility of implementing warnings and alarms based on historical data and trends.
Blockchain in Manufacturing
Blockchain is a concept that has become closely related to cryptocurrency in popular culture. However, cryptocurrency is just one real-world application of the blockchain fundamentals. Although it is not discussed as much, blockchain is also gaining popularity in manufacturing.
Figure 2. Blockchain keeps a permanent system of records that can be helpful in manufacturing, such as in the case of a product recall. Image used courtesy of Canva
So, what is blockchain, and how does it apply to manufacturing? In simple terms, a blockchain is a digital ledger that keeps the records of all the transactions performed on the blockchain entity. That entity can be cryptocurrency, but it can also be a manufactured product. The ability to record every single step of the production process, from raw material to finished goods, makes blockchain the ideal solution for traceability in the industry.
Why is traceability important?
As an example, think of a product recall. When no accurate information is available to limit the scope of the recall, companies err on the side of caution and recall many more products than were needed, thus incurring losses that sometimes cost hundreds of millions of dollars (not to mention the unnecessary inconvenience to the consumers who wouldn’t have actually been affected). Instead, traceability enabled by blockchain technology relies on highly accurate information from the production process to give the business a clear idea about the defect that caused the recall. With this information, the company can decide to limit the recall based on specific production dates and times, manufacturing lines, or locations. Again, the availability of the data needed from the process is provided by IIoT devices.
Transportation and Logistics
Transportation and logistics are not usually considered part of the control automation world, but in reality, they are right at the frontier of industrial automation. They are the last steps necessary to get products to the consumers.
Figure 3. In transportation and logistics, the IIoT is used with enabled devices to track and manage assets. Image used courtesy of Canva
Surprisingly, transportation was also among the first real-world applications of IIoT. As a result, the modern transportation industry employs a combination of dedicated IIoT-enabled devices and blockchain concepts to improve logistics management and traceability.
To provide a specific example, specialized IIoT devices are often installed on trucks and railcars to provide real-time information about the assets transported, geographic location, and even fuel efficiency and engine diagnostics. If this is a truck used for deliveries, this may also include real-time access to order and route changes to optimize delivery times for drivers to decrease overhead costs and provide better customer support.
The availability of this information in real-time makes it possible to make better decisions to optimize transport costs. It also improves decision-making in unexpected events, reducing delays and impacts.
The IIoT is projected to see huge growth over the next decade as more businesses integrate its technology and solutions into their practices. With evolving business models brought on by the IIoT, manufacturing and automation have and will continue to become increasingly efficient.