According to IoT Analytics, the industrial sector is expected to increase IoT spending to $310 billion by 2023. At the same time, Impact claims that ‘36% of companies are considering new business directions as a result of their IoT initiatives.’ Thus, industrial IoT can open many use cases and allow organizations to operationalize actions depending on the IoT technologies in real-time.
The IIoT involves internet-connected machines and advanced analytics platforms to process the data produced by them. Adopting industrial IoT has increased in the last several years due to massive computing power, new trends in data-processing technologies, and emerging algorithms regarding machine learning (ML) and natural-language processing. IIoT has created a new arena for businesses to address a long-standing challenge of connecting different devices and using the collected data for efficiently influencing decision-making processes.
So what makes the industrial IoT different from the conventional one? How can your company use it, and what IIoT platform to choose? Read in our blog post.
The Internet of Things (IoT) represents the networking of devices. Such devices communicate independently through the Internet or cellular networks and conduct different tasks. Thus, the conventional IoT covers daily machines, including vehicles, household appliances, consumer electronics, etc.
The particular devices collect data regarding their application, their environment, and the environment of their users. Besides, the IoT requires these devices to have a clear identity, maintain communication with one another, and perform commands. With conventional IoT, you can automate applications and carry out tasks with no outside intervention.
What about the industrial IoT, it simply serves as the industrial form of the conventional one. Compared to IoT, IIoT concentrates on implementing IoT technologies in manufacturing and industrial environments rather than representing customer-oriented concepts. The main goals of the IIoT are reducing production costs, improving operational efficiency, ensuring faster processes, and enabling the adoption of new business models. When you use the IIoT properly, it makes a positive impact on a company's growth, competitiveness, and further viability.
Therefore, the IIoT connects learnable machines, sensor technologies, automation technologies, and big data existing separately in an industrial environment. That creates close networking of the digital mechanical devices, which promotes significant changes in the global industry. The IIoT concept can bring promising approaches like the ability to provide sustainable improvement of a company's manufacturing process. Finally, that helps fulfill client wishes on time and results in higher customer satisfaction.
Although the industrial IoT and Industry 4.0 serve as separate concepts, they should be considered as one piece when providing greater efficiency into operational processes due to more automation. For example, Industry 4.0 cannot exist without IIoT, and IIoT cannot be efficient without the bigger-picture concept of Industry 4.0. Thus, let’s learn more about their specific characteristics.
The industrial IoT will almost usually represent the facility’s equipment exclusively. And in many cases, IIoT means a technology implementation that can refer to existing or new devices, wireless equipment, etc. On the contrary, Industry 4.0 considers IIoT in a much larger context that involves analysis, action, and even long-term sustainability for manufacturing processes.
Industry 4.0 serves more like a philosophy influenced by technologies like IIoT, maintains a broader scope, and provides a bigger-picture vision.
However, IIoT and Industry 4.0 have some critical common features:
Ultimately, businesses implement IIoT and Industry 4.0 for improving operational performance, and these categories help remain competitive in the industry today.
Nowadays, even though many IIoT projects remain at the initial phases, the entire IIoT continues to demonstrate prosperity and versatility due to successful deployments in different organizations. Here we will go over five specific IIoT applications that can drive further IIoT implementation in manufacturing.
Fleet management. For businesses that rely on transportation and logistics, the appropriate fleet management allows removing or minimizing the risks related to vehicle investment. That increases efficiency and productivity and at the same time reduces transportation and staff costs. Companies can also collect real-time traffic data and implement specific algorithms for delivering more packages more effectively, with less dependence on drivers and vehicles.
Asset tracking. Business operations require a company to track the location of its assets and goods securely. Thanks to IoT-enabled asset tracking sensors, you can maintain remote real-time tracking of equipment and fleets. That allows reducing risks, saving money, and preventing theft. Using sensors can also improve manufacturing management and cut down the operational costs of your business. Lastly, after applying tags and sensors for monitoring facilities, it becomes clear for organizations how to optimize their space usage.
Smart factory. A smart factory requires integrating machines, employees, and Big Data into one digitally connected ecosystem. That provides an opportunity not only to curate and analyze data but learn from experience as well. Smart factories can interpret and gain insights from data sets for forecasting trends and events, which helps apply smart manufactured workflows or automated processes. Also, they undergo continuous procedural enhancements to self-correct and self-optimize.
Predictive maintenance. Your company can implement predictive maintenance technologies for tracking the working processes of machinery and obtain visibility through all operations. Modem manufacturers use a detailed overview for predicting system failures or equipment degradation, which leads to reduced operational and maintenance costs. Besides, due to emerging advances in machine learning, the IIoT applications with complex algorithms allow companies to make predictions depending on new data with no human intervention.
Connected vehicles. The computer-enhanced vehicles help automate numerous driving tasks, even including driving themselves. One of the top advantages of using self-driving cars is accident avoidance, as the vehicle can respond to different obstacles on the road faster than a human. Another advantage is that using computers to operate vehicles is more economical than hiring and training staff. Meanwhile, all necessary data can be obtained via cameras, radars, or lasers. But the ultimate goal of connected vehicles is to reduce the overall number of cars.
Today, experts believe that businesses searching for an IIoT platform should have more time to explore due to the developing capabilities of IIoT to get value from data, reduce costs, improve performance, or propose new action plans. With many options for industrial companies, here we created a list of several IIoT platforms to simplify your task of choosing an appropriate one.
Amazon Web Services. AWS offers an assortment of IIoT services that include everything from connecting and managing gadgets to analytics and computing. What about the computer side, AWS supports a specific real-time operating system called FreeRTOS, which is critical for microcontroller gadgets. Besides, the platform provides its own device programming, AWS IoT Greengrass, to bring AWS abilities for computing, analyzing, managing, and storing to edge devices and enable further local real-time processing.
Azure IoT. Microsoft provides manufacturing units with a helpful ability to collect large amounts of data from industrial machines effortlessly. That allows processing it on edge for real-time alarms and then passing it to the cloud for a thorough analysis in PowerBI. Azure IoT enables manufacturing companies to prepare for actions rapidly compared to past projects when they had to assemble the entire thing with no preparation.
Oracle IoT Cloud. Companies using Oracle IoT Cloud can be satisfied with its technical features and high ability to manage data from manufacturing sensors. The platform provides proper integration with a current manufacturing execution system, which drives companies to improve the entire performance.
IBM Watson IoT. IBM’s platform is considered a fully managed, cloud-hosted service, which provides organizations with abilities to connect, register, and control devices and further data visualizing and storing. Watson IoT highlights analytics and APIs to enable real-time data analysis from different machines and frameworks. The platform’s security and management features allow companies to manage applications and devices that rely on use patterns and anomaly detection.
IDC states that 58% of manufacturers consider IoT ‘a strategic necessity for digitally transforming industrial operations.’ Therefore, the IIoT allows transforming traditional, linear manufacturing supply chains and making dynamic, interconnected systems. After all, modern IIoT technologies change the ways of creating and delivering products, which promotes manufacturing efficiency, ensures better safety for employees, and, in several cases, saves millions of dollars.
Are you already using the IIoT? What operations or tasks does it help you to deal with? Or how do you benefit from implementing such a technology? Share with us in the comments below.
Over the past several years, AgileVision has helped many businesses to implement new industrial IoT solutions or improve the existing ones. Are you considering the increase in efficiency or need some advice on how to start using IIoT in your company?