Industrial Internet of Things (IIoT) Archives

IIoT Is More than a Buzzword

The Industrial Internet of Things (IIoT) has been evolving since it was coined several years ago, but its core meaning remains unchanged. Manufacturing and industrial processes are improved by using general Internet and intranet software, as well as smart sensors, actuators, and localized embedded controllers (also known as Edge Gateways). These technologies provide information beyond the control process itself, historically managed by embedded controllers like PLCs.

Also known as the industrial Internet, IIoT leverages advanced device and data technologies to create “smart machines.” These machines are capable of near real-time analytics, generating enhanced data that traditional “dumb machines” (which only have basic control functionality and feedback) cannot produce on their own or have not typically been generated. Smart sensors provide a means to communicate information beyond simple functionality, such as discrete detection or single-purpose “analog” values like object detection, distance, or temperature, for example. They include “smart” features like internal or even surface temperature, inclination, humidity, and even multi-axis vibration detection all in a single device. These sensors include photoelectric, proximity, digital position, and measurement indicators, radio frequency identification (RFID) systems, and even multi-functional condition monitoring sensors that can combine vibration with several other detection functions, such as temperature and humidity.

IIoT offers many new data gathering and analytics that perform in real-time or near real-time and can allow for the addition of the following to typical older automation:

- Condition monitoring
- Predictive maintenance
- Remote monitoring and control feedback
- Inventory management and supply chain management
- Energy management

Condition monitoring

With condition monitoring, operators can strategically place sensors around non-control locations, such as feed, conveyor, and pump motors, to constantly monitor motor and drive trains (couplers, motor mounts, etc.) for performance information. Adding pressure to oil, coolant, and air feed lines to monitor pressure and flow, will enhance monitoring capabilities, and placing temperature sensors around all critical areas of equipment and processes can allow for monitoring operational temperature levels. This information can be monitored and analyzed without encumbering or interfering with critical machine control or process functionality and can provide the information to develop predictive maintenance analytics to develop and provide more reliable and cost-effective maintenance programs.

Remote monitoring and control feedback

Remote monitoring and control feedback using these same discussed principles can be combined with condition monitoring and predictive maintenance to provide feedback from remote locations, such as pumps and motors and non-controlled devices, for performance feedback to machine controls. For example, if the condition monitoring detects excessive motor vibration, the machine controller can use the information to manage performance, minimize machine damage, and prevent catastrophic failure.

This information can be monitored and analyzed without encumbering or interfering with critical machine control or process functionality and can provide the information to develop predictive maintenance analytics to develop and provide more reliable and cost-effective maintenance programs.

Inventory and supply chain management

For inventory and supply chain management, smart sensors can collect and report inventory and logistics information using sensor-based feedback and cloud-based software. This information can be accessed securely in a shared format across multiple locations, facilitating efficient inventory and supply chain management processes. It also provides a simple and easy-to-digest format for quick information gathering and analytics of predictive inventory management and supply chain status compared to spreadsheet-like or text-based data graphical user interfaces, for example.

Energy management

For energy management, IIoT can optimize energy usage by monitoring and controlling energy-consuming processes and reducing costs and environmental impact. Smart sensors and process or condition monitoring systems make it possible to manage energy usage by tracking the process cycle and machine usage. This allows for automated control of energy distribution based on whether the equipment is in use, idle, or during off-shift times, leading to improved energy efficiency and cost control.

So as touched upon here, IIoT coupled with smart sensing technology can provide many new and innovative ways to monitor the manufacturing process and its critical support systems in many advantageous ways. IIoT can be deployed from the manufacturing process through to the logistics and even energy usage aspects to improve overall equipment effectiveness (OEE), reliability, and efficiency. Look at what your needs are and see what the newest IIoT innovations can do for your business today.

Edge Gateways To Support Real-Time Condition Monitoring Data

In my previous blog post from early summer, I talked about IO-Link sensors with condition monitoring features that work with PLCs. I covered how condition monitoring variables can be set up as alarms and how simple logic can be set up inside the sensor so it only sets off those alarms to the PLC in real time to alert operators when something is wrong. Many companies, however, take advantage of the IoT sensor data with the long-term goal of analyzing the environmental data conditions to predict maintenance needs in real-time versus relying on a schedule. Some even want to connect directly to their MES systems to inform maintenance personnel of daily maintenance orders, which requires a separate device, such as an IoT edge gateway.

Edge gateway benefits

The biggest benefit of an IoT edge gateway is the ability to process and store large amounts of data quickly, enabling real-time applications to use that data efficiently.

An IoT edge gateway typically sits at the end or edge of your network and gathers all the sensor data either directly from the sensors or from the PLC. Since there will be a large amount of data from all the sensors on the network, part of the edge gateway setup is to filter the relevant and important information and process this vast amount of data. The edge gateway must also handle the amount of data required reliably, and it must have low latency. These important factors are often associated with the gateway’s CPU and memory specifications.

After looking at the performance of the edge gateway, comes the ‘gateway’ aspect which provides a translation to different communications networks, whether local or cloud-based. There are the hardware specs of the gateway, whether it’s using serial, USB or Ethernet for that connection, as well as the environmental ratings on the gateway. Then, more importantly, is the software side of the edge gateway. There are cloud-based communications standards designed for different applications and for either private or public cloud networks.

Edge gateways support different communications protocols, such as HTTPS, MQTT, RESTful API, C/Python API. The gateway portion also helps in the conversion of those protocols and the ease of interoperability to different platforms, such as AWS, Azure, Ignition, and Wonderware. This provides data transparency so that all the data gathered can be used across the many different software platforms.

To get to the IoT end goal, an edge gateway is necessary and it’s important to choose the correct one.

Security in the World of the Industrial Internet of Things

The Industrial Internet of Things (IIoT) is becoming an indispensable part of the manufacturing industry, leading to real-time monitoring and an increase in overall equipment effectiveness (OEE) and productivity. Since the machines are being connected to the intranet and sometimes to the Internet for remote monitoring, this brings a set of challenges and security concerns for these now-connected devices.

What causes security to be so different between OT and IT?

Operational Technology (OT) manufacturing equipment is meant to run 24/7. So, if a bug is found that requires a machine to be shut down for an update, that stop causes a loss in productivity. So, manufacturers can’t rely on updating operational equipment as frequently as their Information Technology (IT) counterparts.

Additionally, the approach of security for OT machines has largely been “security through obscurity.” If, for example, a machine is not connected to the network, then the only way to access the hardware is to access it physically.

Another reason is that OT equipment can have a working lifetime that spans decades, compared to the typical 2-5-year service life of IT equipment. And when you add new technology, the old OT equipment becomes almost impossible to update to the latest security patches without the effort and expense of upgrading the hardware. Since OT equipment is in operation for such a long time, it makes sense that OT security focuses on keeping equipment working continuously as designed, where IT is more focused on keeping data available and protected.

These different purposes makes it hard to implement the IT standard on OT infrastructure. But that being said, according to Gartner’s 80/20 rule-of-thumb, 80 percent of security issues faced in the OT environment are the same faced by IT, while 20 percent are domain specific on critical assets, people, or environment. With so many security issues in common, and so many practical differences, what is the best approach?

The solution

The difference in operation philosophy and goals between IT and OT systems makes it necessary to consider IIoT security when implementing the systems carefully. Typical blanket IT security systems can’t be applied to OT systems, like PLCs or other control architecture, because these systems do not have built-in security features like firewalls.

We need the benefits of IIoT, but how do we overcome the security concerns?

The best solution practiced by the manufacturing industry is to separate these systems: The control side is left to the existing network infrastructure, and IT-focused work like monitoring is carried out on a newly added infrastructure.

The benefit of this method is that the control side is again secured by the method it was designed for – “security by obscurity” – and the new monitoring infrastructure can take advantage of the faster developments and updates of the IT lifecycle. This way, the operations and information technology operations don’t interfere with each other.

Maximize the Benefits of Open-Source Code in Manufacturing Software

The rise of many players in manufacturing automation, along with factories’ growing adoption of Industrial Internet of Things (IIoT) and automation solutions, present a suitable environment for open-source software. This software is a value-adding solution for manufacturers, regardless of their operation technology and management requirements, due to the customization, resiliency, scalability, accessibility, cost-effectiveness, and quality it allows.

Customization

Software developers who use open-source code provide software with a core code that establishes specific features and allows users to access it and make changes as necessary. The process is much like being able to complete an author’s writing prompt or change the end of a story. Unlike a closed system that locks users in, open-source allows them to adapt and modify the code to meet a particular need or application.

This add-on coding system provides endless customization. It enables communities (i.e., users) to add or remove features beneficial in an integration phase, such as features for user testing or to find the best solution for a machine.

Customization is also valuable regarding data visualizations; users can develop dashboards and visuals that best describe their operations. Suppose a sensor provides real-time condition monitoring data over a particular machine. In that case, it’s possible to customize the code supporting the software that gathers and processes the data for specific parameters or to calculate specific values.

Resiliency

Additionally, open-source code is resilient to change because it can be modified quickly. The ability to quickly add or remove features and adapt to cyber environments or specific applications also makes it volatile. Like exposure to pathogens can help strengthen an immune response to said pathogens, so can an open-source code be made stronger by its exposure to different environments and applications to be ready to face cybersecurity threats. Implementing an open code isn’t any less risky (cybersecurity-wise) than closed codes due to the testing and enhancements made by so many coders or programmers. However, it is up to the implementer to use the same rules that apply to other closed source software. The implementer must be aware of the code’s source and avoid code from non-reputable sources who could have modified it with negative intentions. Overall, the code is resilient, adaptable, and agile to adapt given a new environment.

Scalability

The add-on and customization aspects of open-source also allow the code to be highly scalable. This scalable implementation happens in two dimensions: adoption timeline and application-based. Both are important to guarantee user acceptance and that it meets the operation and application requirements. Regarding the adoption timeline, scalability allows modification of the software and code to meet users’ expectations. Open-sourced code enables the implementation of features for user testing and feedback. The ultimate solution will include multiple iterations to meet the users’ needs and fulfill operation expectations.

On the other hand, this code is scalable based on the application(s), such as working on different machines, multiples of the same machine with different purposes, or adding/dropping features for specific uses. Say, for example, there are three of the same machine (A, B, and C), but they are in different environments. Machine A is in an environment that is 28°F , B is at room temperature, and C is exposed to constant wash-down. In this case, the condition monitoring software defines the acceptable parameters for each scenario, avoiding false alarms from erroneous triggers. In this example, the base code is adapted to include specific features based on the application.

Accessibility

In general, cost-effective and high-quality open-source code is available online. There are additional resources such as free coding tutorials that don’t require any licenses as well. Moreover, when programmers update an open code, they must make the new version available again, ensuring that the code is accessible and up to date.

Cost-effectiveness and quality

Regarding cost-effectiveness, using community open-source code significantly reduces the cost of developing, integrating, and testing software built in-house. It also reduces the implementation time and makes for better production operations. Essentially, it is high-quality, reliable code created by trusted sources for multiple coders and users.

“The application drives the technology” mantra is at the heart of open-source software development—a model where source code is available for community members to use, modify, and share. IIoT enablers and providers in the manufacturing industry own a particular solution that is then available for manufacturers to adapt to their specific operational requirements. With the increasing adoption of data-collecting technologies, it is in manufacturers’ best interest to seek software providers who grant them the flexibility to adjust software solutions to meet their specific needs. Automation is a catalyst for data-driven operation and maintenance.