All You Need to Know About the Internet of Things (IoT) in Industrial Applications
Written by Richard Seeley
Published: July 25, 2022
IIoT is the industrial-strength version of the Internet of Things (IoT) powering a new industrial revolution, sometimes referred to as Industry 4.0. Industrial Internet of Things applications run everywhere from factory floors to remote energy exploration sites.
Artificial Intelligence comes into play in remote monitoring systems where IoT sensors on machinery inside factories and out in the field, feed data such as temperatures, vibration, and other readouts of operating conditions to Industrial AI applications. In such an IIoT application, AI can detect even minor anomalies and make adjustments or alert technicians of potential maintenance needs to avoid stoppages in production.
What began with placing sensors on machinery for remote monitoring via the internet and cloud computing has evolved into IIoT or Industry 4.0. “The proliferation of sensors in manufacturing environments provides a phenomenal amount of valuable data,” according to Modernizing the Manufacturing Industry with MQTT a HiveMQ white paper. “Advances in cloud computing make it possible to integrate machine learning, artificial intelligence, and advanced analytics to quickly respond to the changing dynamics on the factory floor.”
Beyond IoT sensors located on traditional factory equipment, Smart Machines, including robots capable of performing tasks once done by humans, have industrial applications not only in manufacturing but also in medicine where the technology can help medical doctors with patient diagnoses.
Advanced Data Analytics Systems
The Industry 4.0 revolution is made possible by increasingly sophisticated analytics systems capable of analyzing and acting on data collected from IoT devices using not only AI but also Machine Learning, and a host of smart technologies.
“Advanced Analytics is the autonomous or semi-autonomous examination of data or content using sophisticated techniques and tools, typically beyond those of traditional business intelligence (BI), to discover deeper insights, make predictions, or generate recommendations. Advanced analytic techniques include those such as data/text mining, machine learning, pattern matching, forecasting, visualization, semantic analysis, sentiment analysis, network and cluster analysis, multivariate statistics, graph analysis, simulation, complex event processing, neural networks,” according to Gartner’s definition of the technology.
What are the Benefits of IoT in Industrial Applications?
Many of the benefits of Industrial IoT are hallmarks of what manufacturing operations have been striving for since Henry Ford started running Model T’s down an assembly line, including increased efficiency and reduced costs. Machines that can alert technicians to maintenance issues so they can be addressed before a problem slows or stops production are going to increase efficiency.
A major benefit of Industrial IoT is enhanced reliability and quality, as Daimler AG, the German automotive manufacturer known for its premium brand Mercedes-Benz Cars, Daimler Trucks, and Daimler Buses has found with its Industrial IoT application that relies on HiveMQ.
As part of its manufacturing process, Daimler must test the 70-100 electronic control units (ECUs) in every vehicle. These are controls for critical functions including brakes, lights, locks, and the entertainment system. To ensure the highest quality and reliability the famed car maker created a Vehicle Diagnostics System (VDS) to coordinate the production process of commissioning and testing all the control units that are added to a car. Daimler uses HiveMQ as the core infrastructure service for VDS to manage the information flow between the test devices on the factory floor and the server-side enterprise IT systems. The reliability of that system is as dependable as the vehicles Daimler manufactures.
“We have been running the VDS using HiveMQ for 4 years and the HiveMQ broker has not gone down. It is rock solid, completely reliable,” says Marius Hertfelder, VDS Operations. “When we do have to restart the broker, it is a very fast process so our downtime is minimal. This is very important since we can’t stop the factory assembly line.”
To find out more about this Industrial IoT application read the HiveMQ case study, Daimler Relies Upon HiveMQ During Automotive Manufacturing.
How Do IoT Devices Work in Industrial Areas?
Advance manufacturing leveraging Internet of Things technologies in general and Industrial Internet of Things technologies are being deployed to provide connectivity via standard MQTT (Message Queue Telemetry Transport) especially among once discrete processes on a factory floor, for example. This provides organizations with productivity gains, as well as improvements in reliability and quality by orchestrating the various processes that go into making products.
Modernizing the Smart Manufacturing Industry with MQTT, a HiveMQ white paper explains:
Measuring and increasing overall equipment effectiveness (OEE) is a central element of the process:
- Increase the availability of equipment by avoiding unplanned downtime
- Ability to analyze everything and continuously increase the quality of production
- Fine-tune the performance of machines and processes
In a factory deploying Industrial IoT, the white paper details four distinct areas where processes are evolving:
- Automation area: Factory machines, sensors, and gateways. Data needs to be able to flow between the machines and the sensors and gateways. The gateways are typically used to communicate with other areas in the factory architecture.
- Manufacturing area: Systems used to control the factory equipment such as SCADA (supervisory control and data acquisition) and MES (manufacturing execution systems).
- Factory area: Systems used to manage the entire factory such as PLM (product lifecycle management) and OEE systems.
- Cloud: Connectivity to the enterprise IT systems of the organization that allows for deeper integration between the OT (operational technology) and IT systems.
Remote control IoT devices allow factory managers and technicians to monitor machinery and systems to troubleshoot potential problems and enhance manufacturing processes.
What Are the Security Concerns for IoT Devices?
Data moving within an industrial complex via MQTT requires the same security defenses as any other business system, such as financial transactions or medical patient information. The HiveMQ MQTT Security Fundamentals Overview recommends securing IoT data devices and securing IoT systems from hacking attacks and malware at three critical levels:
One way to provide a secure and trustworthy connection is to use a physically secure network or VPN for all communication between clients and brokers. This solution is suitable for gateway applications where the gateway is connected to devices on the one hand and with the broker over VPN on the other side.
When confidentiality is the primary goal, TLS/SSL is commonly used for transport encryption. This method is a secure and proven way to make sure that data can’t be read during transmission and provides client-certificate authentication to verify the identity of both sides.
On the transport level, communication is encrypted and identities are authenticated. The MQTT protocol provides a client identifier and username/password credentials to authenticate devices on the application level. These properties are provided by the protocol itself. Authorization or control of what each device is allowed to do is defined by the specific broker implementation. Additionally, it is possible to use payload encryption on the application level to secure the transmitted information (without the need for full-fledged transport encryption).
The Future of IoT and AI Technology Integration
In the Wikipedia definition of the Fourth Industrial Revolution we learn the term had been showing up in scientific papers and then in 2015 it was “popularized” by Klaus Schwab, the World Economic Forum Founder and Executive Chairman. He asserted that Industry 4.0 technologies were going beyond traditional efficiency improvements and creating significant changes in how industries worked. As discussed in this article, IIoT, AI, Cloud Computing, Smart Machines, and other leading-edge technologies are creating a fundamental shift globally.
Industry 4.0 is just beginning. Gartner reports Smart Machine implementation only became widespread in 2021. The Fourth Industrial Revolution with IIoT, including what is being called “large-scale machine-to-machine communication (M2M),” promises to bring further innovations to industries including manufacturing, automotive, and transportation.