What is the IIoT? A definitive guide to the Industrial Internet of Things
The Industrial Internet of Things (IIoT) refers to all the devices used in manufacturing that are connected to wireless networks, gathering and sharing data. This includes most of the ubiquitous industrial technology we think of today such as machines in factories, engines in airplanes, and robotics. IIoT enables industries to use the data gathered and shared by these devices to be more efficient and reliable in their operations. To employ IIoT in your business and improve your processes, you need to understand the role it plays in manufacturing. This guide covers what IIoT is, why it’s important, and what to consider when investing in an IIoT platform. In this article, we will also reference a user study that involved 50 one-hour in-depth phone interviews with senior management, operations execs, and manufacturing engineers. This study was carried out to identify the current state of IIoT in manufacturing, challenges, solutions, and recommendations.
What does the Industrial Internet of Things (IIoT) mean?
The Industrial Internet of Things is derived from the popular term Internet of Things (IoT), and describes the use of IoT in industrial sectors and applications. IoT refers to the billions of devices around the world that are connected to the internet, collecting and sharing data. IIoT goes beyond the physical devices usually associated with IoT. What makes it distinct is the convergence of information technology (IT) and operational technology (OT). OT includes industrial control systems (ICSs), for example, human machine interfaces (HMIs), supervisory control and data acquisition (SCADA) systems, and distributed control systems (DCSs). IIoT platforms use big data and analytics to transform production processes. Having a dashboard that provides a strategic overview of the devices, machinery, and robotics used on the factory floor helps reduce downtime, monitor machine health, improve efficiency, and inform decision making.
The Industrial Internet of Things helps businesses achieve what is considered to be a Smart Factory. Smart Factory is a concept used to express a highly connected plant floor with the end goal of full digitalization in manufacturing. According to our user study, Smart Factory was the preferred umbrella term for the PLEX IIoT platform. It also describes a manufacturing process that uses the highly digitalized IT and OT to collect and share data. An example of an IT function that helps businesses achieve Smart Factory goals is machine automation. Machine Automation is designed to control the work of machines, with built-in computers that improve the quality of products and services, increases productivity, and allows plant-floor workers to concentrate on less menial tasks.
Why is the Industrial Internet of Things (IIoT) important?
The importance of IIoT over the last few years has increased due to its ability to help manufacturers overcome common challenges with production and plant throughput. In our study, we asked respondents what their biggest challenges were; the most common responses included labor shortage, COVID-19, asset downtime, training new staff, and poor forecasting. Using IIoT platforms to provide extremely detailed data in real-time can help companies better understand their current manufacturing processes and make improvements in line with the information provided.
The core benefits of using IIoT technology in manufacturing include:
Increased Efficiency - Use of IIoT platforms allows manufacturers to automate and optimize their operations. Robotics and automated technology work more efficiently and accurately. This increased efficiency supports manufacturers looking to reduce their labor force, reduce overhead costs, and streamline their functions.
No Risk of Human Error - IIoT technology helps reduce errors associated with manual labor. This can also go beyond operational and manufacturing errors, protecting manufacturer’s data. Control of computing is handed over to AI and machine learning-enabled programs which reduces the risk of data breaches caused by human error.
Predictive Maintenance - Machine downtime is the biggest risk to manufacturing operations. IIoT technology uses data to monitor machinery performance and function and schedule downtime for fixes before they become serious issues, saving both money and time.
Improved Safety - The purpose of an IIoT platform is to connect manufacturing operations so machines, sensors and people all work as one. This smart manufacturing process also works to monitor workplace and employee safety. If an accident occurs or there is a potentially dangerous fault, everyone in the facility can be alerted, operations will stop, and leadership teams can intervene.
Reduced Operating Costs - The insights provided by IIoT can help manufacturers make smart operational decisions that increase profitability. IIoT solutions provide the tools necessary to increase efficiency, reduce errors, provide predictive maintenance, and improve quality control, this all reduces operational overhead costs.
In our user study, we provided respondents with examples on how the Plex IIoT solution is applied within manufacturing environments. Our solution features a dashboard where users can monitor machine health in real-time, including machine uptime, current state, part, and job. The dashboard also includes contextualized machine data, providing current and historic values such as job number, part number, and workcenter status. Plex’s comprehensive solution provides alerts and historical analysis, meaning users can gain visibility into live historical sensor data for machine health and get maintenance alerts across a wide set of equipment. They can also use this information to track Overall Equipment Effectiveness (OEE) and reduce costly downtime.
After we showed our IIoT solution to respondents, survey results highlighted a real need for this technology. We asked them to rate their interest and how important they felt our solution was for their business from a scale of 1-7 (1 low – 7 high). On average, companies rated the solution as 6 for interest and 6 for importance.
How is IIoT Used in Manufacturing?
The industries currently using the IIoT are mainly manufacturing, retail, utilities, and transportation. Utilities can use IIoT platforms to reduce the costs of sending staff to check on remote installations by making them self-monitoring. They can also install IoT sensors in their equipment to monitor vibrations, temperature, and moisture in real-time. The IIoT in retail helps create faster, more efficient logistics and supply chains, so businesses can detect bottlenecks, improve customer experience, and better collaborate with new partners. Transportation and auto manufacturers can improve the performance of their vehicles using the IIoT and Smart Factory technology. IIoT can also be used in the automotive industry to reduce environmental emissions, helping them meet sustainability objectives.
IIIoT technology has become a critical part of digital transformation and manufacturers across a range of industries can accomplish many things using the technology. Some use cases include:
- Asset Tracking and Monitoring – Track and monitor machine health to reduce production disruption due to surprise outages and machine failures.
- Automation of manual processes – Automate data capture and processes to reduce human error and add increased levels of control, speed, and accuracy.
- Real-time manufacturing intelligence – Connect to machines to track real-time operational KPIs and gain accurate visibility of operational metrics to improve production and reduce downtime.
- Predictive maintenance – Mitigate unplanned downtime by reducing the time is takes to diagnose machine health events and improving historical data traceability.
- IT/OT Connectivity – Combine OT data from the plant floor with IT data from your software systems to create a closed loop system that drives informed decision making.
The IoT World Forum Reference Model and how it relates to manufacturing
The IoT World Forum Reference Model was introduced in 2014 and breaks down the vast IoT concept into seven functional levels, from physical devices and controllers at Level 1 to collaboration and processes at Level 7 (Jim Green, CTO Cisco Data Analytics Business Group).
So how can it be applied to IIoT in manufacturing? Let’s break it down (click layers to see more):
What are the security considerations and challenges in adopting the Industrial Internet of Things?
While IIoT platforms can revolutionize operations, maintaining security for a digitalized Smart Factory can be a challenge. Integrating operational technology to the internet sees the introduction of more intelligent and automated machinery. This in turn invites a range of new challenges that require a deeper understanding of the nuances of IIoT. Three core areas need to be focused on when adopting a new solution: availability, scalability, and security. Many businesses may already be familiar with availability and scalability when it comes to industrial operations, but security is a potential hurdle when integrating with an IIoT platform. For example, many businesses still use legacy systems and processes that have been in operation for decades, which complicates the adoption of new technologies.
Another potential challenge is the acquisition of new smart devices that gives rise to security vulnerabilities and accountability. Businesses adopting IIoT are responsible for the security of setting up and connecting the new devices and should be able to ensure the security of the users and provide the necessary response when issues arise. Using an increased number of smart devices in business operations creates an increased risk of data breaches, for example, hackers gaining access to these connected systems. This type of major breach can lead to a shutdown of operations, and the necessary cybersecurity steps must be taken to protect against incidents such as these.
Finally, businesses should also be made aware of the inherent risks that come with using data. IIoT platforms can use large amounts of data to inform business decisions and help streamline certain processes, but it is essential that personal information is kept separate from general log data. User data should be processed in accordance with privacy regulations, such as the European Union General Data Protection Regulation (GDPR). All personally identifiable information (PII) should be kept in a protected, encrypted database. Businesses looking to adopt IIoT as a solution should be aware of the following risks:
- Software vulnerabilities that can be exploited by hackers
- Publicly searchable internet-connected devices
- Threat from hackers, targeted attacks, and data breaches
- System manipulation that can cause operational disruption and sabotage processes
- System malfunctions that can cause faults in devices, damage to facilities, and injury to workers
The more connected devices adopted by a company, the more security risks. Considering all the potential risks during integration is essential.
How do you implement IIoT and overcome security risks?
We have discussed the potential security risks of IIoT, but what can businesses do to successfully implement IIoT and mitigate these risks? Having a security operations center (SOC) is vital for monitoring and defending against the risks we listed above. This allows industries to oversee, encounter, and respond to a high number of security alerts. A SOC team detects security issues or anomalous activity and immediately addresses issues before they cause any damages. Businesses may want to take this a step further and hire a dedicated security team for tackling security issues specific to an operations technology environment. Hiring a specialist team who understands the threats of adopting IIoT offers business the best possible protection from security risks. Having full stack protection built into different layers of IIoT implementations, such as device, the network, and the cloud, should be a security objective. This allows industries and manufacturers to securely conduct their operations.
The device layer incorporates the devices and applications that businesses use to implement IIoT solutions. These are supplied by manufacturers and service providers, and businesses should understand how their suppliers transmit and store data. By doing this, manufacturers and service providers can notify IIoT adopters of any security issues and how to handle the situation.
The network layer includes a gateway that gathers data from different connected devices. Businesses looking to implement an IIoT solution should have next-generation intrusion prevention systems (IPSs) monitoring and detecting potential cyberattacks. Control centers are kept in the gateway and used to issue commands to connected devices. This is where organizations should look to implement their security systems.
The cloud layer is where organizations should implement security that runs server-based protection to mitigate the risk of hackers accessing servers and sensitive data. Implementing IIoT systems correctly and overcoming security risks requires connected threat defense from the gateway to the endpoint, that can provide:
- Regular monitoring and detection
- Threat visibility and anomaly detection
- Prevention of threats and attacks between IT and OT
- Secure data transfers
- Next generation intrusion prevention systems
- Server and application protection across the data center and the cloud
Manufacturers who are aware of the risks and are willing to invest in the integration and security of new IIoT systems are the ones most likely to see a successful implementation of this technology.
What does the Industrial Internet of Things (IIoT) mean for MES?
There is no doubt that IIoT is having a big influence on manufacturing, spurring initiatives, pilots, and studies around the world. This has led to concerns that IIoT could replace existing manufacturing execution systems. It’s important that industries understand that the IIoT complements MES, rather than replacing it. In many cases, IIoT can expand the capabilities of an MES, using smart devices and cloud-based systems to reduce downtime, increase overall equipment effectiveness (OEE), and satisfy a greater need for return on assets. An IIoT solution should be seen as technological progress, and introducing smart sensors, actuators, and more reliable cloud infrastructure will only improve the performance of MES. It's important businesses realize that they can use this technology to complement their current MES software, and not see it as a replacement. Here are some examples of how industries can look to integrate the IIoT with MES:
- Move MES away from being a standalone application, integrating many technologies.
- Combine process, operational, and machine-level data through highly visual dashboards
- Capture data to understand machine trends over time and get early notifications of imperfect machine conditions
IIoT platforms can extend the value of MES, so industries need to be open minded when it comes to integrating new technologies within their business.
This article provides deeper insights into IIoT and why it is important for businesses. Using Plex IIoT can help you reduce costs, increase profitability, drive revenue, and more. You can learn more about Plex solutions and leverage the full benefits of analytics coupled with IIoT here.
IIoT with Plex Smart Manufacturing
The Plex Smart Manufacturing Platform with IIoT, delivers world-class security, high availability and scale powered by the Plex Cloud Infrastructure. In an industry where every moment counts, you can trust the Plex Cloud Infrastructure to prevent unplanned downtimes, automate workarounds, and decrease performance inefficiencies.
We understand IIoT technology because we’ve been doing it for years. We help manufacturers connect to machines through off-the-shelf hardware, contextualize OT data from the plant floor, and use that data to drive rapid decision making. Here are some of our powerful IIoT products:
- Plex Production Monitoring – Provides seamless connectivity to machines on the plant floor, delivering transparent, real-time operational KPIs and dashboards to drive continuous improvements.
- Plex Asset Performance Management (APM) – Combines process, operational, and machine-level data through highly visual dashboards to proactively monitor machine and plant health to ensure optimal uptime, throughput, and maintenance needs.
- Plex MES Automation & Orchestration – Connects your Plex MES to the plant edge to control information flow, processes, and workcenter setup adding efficiency, saving costs, and eliminating manual errors.
An IIoT Example
To better understand the IoT World Forum Reference Model and the way this technology can be applied to a manufacturing plant, we have put together an IIoT use case.
Let’s say you are a manufacturer of metal automotive parts. Here’s how information might flow in your plant.
Layer 1: Physical devices and Controllers
For this example, let’s use your welding stations that are equipped with sensors and actuators.
Layer 2: Connectivity
Here is where OPC UA—an open-source information exchange standard— collects and aggregates data from multiple welding stations, allowing for industrial communication between the sensors and actuators within the stations, between different welding stations, and from your welding stations to your IT systems. This layer includes all the network connectivity to bring data from distributed devices / controllers to central Edge device(s).
Layer 3: Edge Computing
Your welding station data is then pre-processed, transformed, and used for local analytics and actions. This may include data compression, analysis, triggering low-latency controls, and packaging transmission to the cloud.
Layer 4: Data Accumulation
The data from layer 3 is ingested and stored in a cloud-based databases. The data could be stored for the short-term use or accumulated in long term storage infrastructure.
Layer 5: Data Abstraction
The data that is stored in layer 4 can be accessed anytime, from anywhere, using any device. The platform automatically monitors the data for anomalies and alerts users of any machine anomalies. This layer often adds additional data context and data processing / analytics.
Layer 6: Application
Your data is used in applications that can provide Pareto and asset availability analysis so that your maintenance personnel can prioritize asset maintenance on the plant floor.
Layer 7: Collaboration & Processes
Finally, your data can be used to automate work orders into your computerized maintenance management system (CMMS) and contextualize process data from machines with production data from your manufacturing execution system (MES), aggregating data from multiple systems.