The Industrial Internet of Things is surpassing itself with added data sources, more detailed information and greater insights—if users are open-minded and flexible enough to try it. Read more of this series here.
Understandably, as IIoT became more familiar and accepted over the past few years, users started to shift their focus from its basic networking and communications needs to the data it can move and analyze.
For example, oil and gas midstream marketing and logistics provider ARB Midstream in Denver recently worked with system integrator INS Services in Richardson, Texas, to develop a SCADA system in just six months for a newly acquired, 900-mile, crude oil pipeline with 37 sites and 950,000 barrels of storage in Oklahoma and Texas. The pipeline’s assets included 35 RTUs and central gathering locations, 10,000 tags and 3,500 alarms, and required 12 overview screens and one per site for a total of 115.
“We wanted cloud computing, but we didn’t want to build a traditional infrastructure,” says Jerod Blocker, operational technology manager at ARB Midstream. “We chose to spend on software and edge computing, and we wanted a local OPC UA server that could leverage multiple protocols.”
MQTT pulls together
Consequently, INS and ARB built a web-based, cloud-hosted SCADA solution and software-defined, wide-area network (SD-WAN) with cloud-based reporting, management, visibility, control and communications with failover capabilities and store-and-forward technologies. It also included Ignition Pro software hosted on AWS, Moxa UC8100 computer with Ignition Edge MQTT, and Cradlepoint Netcloud Perimeter SD-WAN.
“ARB also asked us to look at replacing some older VSAT equipment and maybe even some older cellular equipment at some of their remote locations,” adds Dave Brewington, services manager at INS. “We also needed a secure, reliable and scalable network that would let ARB grow. NetCloud Perimeter let us to create an abstracted overlay network built on cellular technology, which allowed us to have fully secure, encrypted end-to-end communications between remote assets and the cloud.”
The overlay network uses the 172 IP address range on top of the SD-WAN’s IPv6, creating a large pool of IP addresses that won’t conflict with each other. It simplifies management of the network, and eliminates the need for users to memorize local IP addresses. The new network is also carrier-agnostic, enabling it to use a mixture of copper, fiber, cellular and satellite for connectivity, and select the best connection in each situation.
Mo Moore, software services manager at INS, adds the system integrator and ARB were impressed with MQTT’s performance. MQTT uses little bandwidth and reports by exception, which can be a big improvement over traditional polling. In fact, a weak cellular network related to ARB’s pipeline previously meant that basic communications were having trouble getting through. However, data from MQTT seamlessly and quickly reached its intended destinations.
“Retiring the VSAT devices and migrating to MQTT over cellular was a much better approach,” says Moore. “It helped ARB implement a secure, robust, cost-effective and scalable infrastructure. On the first day, we saw a 35% difference in data-plane utilization because we weren’t sending up tags that we didn’t need to send up. With Cirrus Link’s MQTT setup, the lightweight protocol gets the data to the cloud or control center, so it was a huge benefit.”
AWS keeps gaining ground
“IIoT is still defined by the Internet, data collection, edge computing, and store-and-forwarding information, but there’s more awareness of providing the infrastructure that operations technology (OT) applications can use to allow data to flow more freely and efficiently to the business level,” says Travis Cox, co-director of sales engineering at Inductive Automation. “We’ve seen a recent transition to companies using cloud-computing services, especially Amazon Web Services’ (AWS) IoT SiteWise for asset modeling or Microsoft’s Azure Digital Twin (ADT). These software tools let users inject operations data, store it against a model, and use it in context. This means having the types of devices, engineering units, operating ranges and other conditions where the data is produced, which is very important for understanding machine learning (ML) or artificial intelligence (AI).”
For instance, if a motor is important to a process, users can define and model it with Ignition or other software at the edge, and preserve it in the cloud, where it can be compared with an established model. Because this all happens in the same format, Cox explains that no traditional script or programming is needed, and no custom code or other laborious tasks are required.
“AWS and Azure know the value of this, but they just need some added software like Ignition to secure the data in the same way,” says Cox. “The critical piece is using open Sparkplug B for specifying the data payload and MQTT protocol to achieve that common format. This is what allows the notion of models, objects and metadata associated with process values to come across. Sparkplug is open, so any device that supports it can translate data to AWS, Azure or other cloud services. As a result, users who want to take data from PLCs and old, proprietary devices and map it to a model, they only need to do it once with Sparkplug. After that, every service above can access, use and republish the data for that device without added programming.”