IoT and Edge Computing Part Three: Converging traditional Operational Technology with IoT to drive automation

June 15, 2021, by Sean King

Apps for Engineering

IT / OT Convergence through IoT

The fusion of Operational Technology and Information Technology is often touted as the upcoming Fourth Industrial Revolution and is predicted to be the key driver of digital transformation in coming years for the manufacturing, logistics, utilities, building management, and other industrial sectors.

Operational technology (OT) is the term coined to describe the Industrial Control Systems that have been adopted in many industries to monitor and control industrial assets. For example, the oil & gas industry and water utilities have used Supervisory Control and Data Acquisition (SCADA) systems for years.

However, in many organizations these OT systems are aging, maintenance is time consuming, and they could be made more efficient if properly integrated with digital process management workflows. The challenge is that the specialization required to modernize in the short term prevents organizations from effectively future-proofing their operations for the long.

What modern IoT solutions offer is the chance to reimagine and modernize your OT systems, ensuring the same reliability, but with increased insight into real-time operations. Additionally, you'll reduce the ongoing costs and labor associated with maintaining the complex and rigid integrations required to run and update existing centralized or distributed relay-based control systems.

The ability to procure pre-configured controllers with internal processing power and built-in database and workflow integrations is a new and exciting complement to existing OT infrastructure that allows new capabilities to be added with much less effort and difficulty than ever before. For example, you can now easily configure dashboards to visualize real-time sensor data. When coupled with exiting SCADA systems you can analyze large quantities of data quickly and at scale, a major improvement if you are running a large physically distributed utility or manufacturing facility.

By embracing IIoT and edge computing, business analysts, operations managers, and IT professionals can now combine both the IT and OT aspects of their systems in one unified platform configured without code. This allows organizations to benefit from timely data-driven decisions and automated workflows without having to design and program the data collection and workflow aspects of a custom system.

Analysts, journalists and others agree that the convergence of Information Technology (IT) with Operational Technology (OT) is one of the key drivers of digital transformation. Yet many people are confused about the IIoT, and how to implement a successful adoption strategy. (source)

Driving automation with Edge Computing

Edge computing, moving data processing from data centers out to the edge, where your real-world data is being collected, offers even further benefits.

For example, reduced latency is a significant benefit of edge computing, allowing faster decision-making as organizations reduce the time spent transmitting and processing data. Edge devices, such as controllers with built-in processing power, allow organizations to aggregate and action data at the source instead of at a remote central database. Therefore, your workflows aren't delayed by latency issues when a large volume of data is transferred from the collection point back to your processing center. This will streamline your business processes, allow automated responsive action to happen faster, and greatly reduce the likelihood of a catastrophic event.

Smart controllers also drive efficiency and preventative maintenance by speeding up the human elements of a business process. For example, in a wastewater facility, a controller connected to a tower light can create a clear signal to laboratory technicians that immediate action is required the second a sample falls out of temperature range or a piece of crucial equipment fails.

The ability to trigger instant notifications and interact with physical assets helps organizations create more predictive and preventative maintenance workflows. For example, at a manufacturing facility, an organization may have previously assigned employees to routinely monitor the performance and calibration of machinery to ensure it meets safety and performance expectations. If during a routine inspection, a piece of equipment is found to be out of calibration, an employee can act to shut down production and then request maintenance.

This standard process is now obsolete because it cannot prevent machinery from running in an unsafe or damaging way for a prolonged period before the fault is discovered manually.

By implanting an IoT solution a sensor can collect calibration data many times a minute. As soon a machine falls out of an acceptable range, an edge device automatically flags the error and creates a maintenance order in a workflow solution. This allows an employee to step in to perform an assessment quickly and take corrective action to prevent a serious malfunction, or accurately predict when a future maintenance cycle should be scheduled to optimize up time.

Prevention happens even faster when actions are automated, and the processing is performed at the edge where the machine is operating. When rapid cycle manufacturing equipment falls out of alignment milliseconds can make the difference between a quick repair and a costly replacement. In many environments, even marginal changes in temperature or vibrations can indicate potentially damaging issues, so latency concerns take on an even greater significance.

In these cases, an edge controller device can act where a simple IoT sensor cannot, shutting the asset off or activating a tower light to indicate potential issues. This is extremely useful for mitigating risk and preventing costly or dangerous errors in many industries.

The Flowfinity M1 Controller offers this important functionality, taking control of a physical asset while also instantly launching the appropriate workflow actions and recording data. This combination of Industrial IoT and edge computing functionality allows organizations to create an unprecedented level of automation to support a truly preventative maintenance process.

operational technology and IoT for automation

IoT Edge Computing savings and security

Edge-enabled IIoT can also provide a cost-effective solution to automating business processes long-term. Edge devices gather and action data constantly, going well beyond the ability of humans to make manual observations. These devices allow you to use high-volume, high-frequency data collection coupled with data visualization tools such as interactive dashboards to find new efficiencies in your workflows and make better business decisions faster.

There are also significant savings to be realized via reduced bandwidth costs. When organizations begin aggregating data at the source, it allows for more efficient use of IoT devices without paying the significant data transmission costs to wireless network carriers since there is no need to upload to a central database for processing.

Edge devices, like the Flowfinity M1 controller, can be deployed to essentially transcribe data between physical objects and digital workflows, storing data on the device and never losing data due to connectivity issues. This kind of edge deployment provides extra resiliency to your IT infrastructure.

Consider a laboratory setting, deploying sensors is an efficient way to monitor environmental factors such as temperature or humidity. Currently, a lab could deploy IoT sensors to take frequent readings and upload these to a central database. But if power or internet-connectivity fails, there is likely to be a hole in your data right at the critical time, and your alerts could fail, leading to a delayed or disrupted response.

However, a controller with a separate power source or battery could still trigger a notification, launch a workflow action, and continue to store readings on the device, providing redundancy against a loss of power or connectivity. This is another example of how Industrial IoT and edge computing can improve overall resiliency and safeguard your mission-critical materials.

IoT devices and edge computing controllers can now be combined with no-code configuration tools, offering a unique opportunity to create truly end-to-end workflow solutions. Taking data from the edge and tying it together into one unified, configurable workflow and data management platform.

To discuss your IIoT and edge computing strategy, contact our experts for a complimentary consultation.

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