Almost everyone today is intimately familiar with some form of human-machine interface (HMI). We use them to send messages and watch videos (smartphones and tablets), create documents and drawings (laptop computers) and find our way around (GPS systems). HMIs are even appearing on coffeemakers, large appliances and other consumer goods.
In the world of industrial automation, applying HMIs to control and monitor machines, processes and even smart buildings has been a common practice for many years. These industrial HMIs, sometimes called operator interface terminals (OITs), are good at what they do but have traditionally required significant engineering effort for development, deployment and maintenance. They also typically include many proprietary elements and require ongoing expenditures for software and licensing.
Closely related to HMIs, and in fact often overlapping with them, are supervisory control and data acquisition (SCADA) systems. SCADA systems typically cover a much wider physical area, such as multiple pumping stations remote from a central facility, while HMIs are usually local to the processes for which they provide visualization. SCADA systems offer a wider reach for initiating control and monitoring, and usually include database capabilities for logging data points and facilitating analysis. But like HMIs, they are also usually proprietary, and expensive to support over time.
Today, automation engineers are increasingly taking advantage of available “smart” systems in the field, including Internet of Things (IoT) devices. These devices have lots of useful data to offer and frequently need monitoring, and are sometimes used as inputs to real-time control systems. But the traditional methods of connecting these remote devices through standard industrial systems is difficult and costly.
However, a next generation of HMI and SCADA hardware and software addresses these and other challenges. By using the latest commercial and open-source technologies, these products free users to focus on connecting with smart systems, getting data, transforming it into actionable information, and visualizing it when and where we want.
The Case for Connectivity
Outfitting processes and equipment with electrical and digital instruments is a standard practice with a well-developed history. A wide range of sensors, analyzers, controllers and other components are available to support these automation systems, but many of these established products require relatively expensive engineering and installation for deployment.
With the digitization of everything, easy availability of Ethernet and wireless networks (Wi-Fi), and energy-efficient designs—an entirely new class of IoT instrumentation has become available to address these deployment issues. These devices can economically be installed out at the “edge” of processes and facilities.
Larger equipment also comes standard as “smart.” Systems distributed throughout company sites—such as air handlers, power distribution equipment, and packaged skids for water handling and compressed air—all offer extensive operational and power usage data collected with smart devices.
In fact, edge-located IoT devices (Figure 1) and intelligent equipment are now the norm. Even if direct command and control is not warranted, substantial value can be gained by gathering the available data so it can be analyzed to reveal energy usage, perform condition monitoring, and help discover other trends. When problems are discovered early and addressed before escalation, money can be saved and downtime avoided.
Figure 1, Wireless Sensors, courtesy of Emerson: Field-located smart sensors, such as this wireless tank level instrument, are the norm now, offering data when end users make connections.
Issues with Classic Connectivity Methods
Although it’s desirable to tap into these smart devices, it’s not always easy or cost-effective. The “classic” approach involves several steps and linkages to make edge data available up to the cloud (Figure 2, top diagram). Not only are these connections difficult to configure initially, but they are also challenging to maintain over time, with required maintenance beginning at the periphery and progressing inward.
First, the field device is likely wired or networked to a local programmable logic controller (PLC), since this is often the nearest programmable system to the edge component. The PLC requires some device-specific communication driver or instructions to obtain the data, which may involve choosing the desired points and mapping them in a spreadsheet-like format.
Next, the PLC data is networked up to a PC-based HMI or SCADA system, with either approach requiring configuration of data tags, drivers and polling rate assignments. In turn, the HMI or SCADA needs additional configuration or programing steps to transport the data into a cloud-based database, where it can be made more widely available.
All these tasks are feasible and commonly employed, but they have many downsides. Typical PLCs and communications drivers may be proprietary, requiring costly configuration software and licenses. Even with the right hardware and software in hand, designers require specialized knowledge of devices, programming and networking. Certainly, the last networking link from the project site to the cloud demands dedicated attention to go through firewalls and maintain security.
Figure 2, Flattening the Architecture: The diagram at the top shows the traditional and overly complex methods often used for linking sensors to the cloud. The bottom diagram depicts the use of next generation hardware and software to significantly simplify these steps.
Hardware First
A better approach circumvents many of these issues by leveraging commercially-based and open-source hardware and software to achieve streamlined but effective high-performance connectivity (Figure 2, bottom diagram). Specialized elements are superseded with simple, standard building blocks far more easily managed, but still capable of implementing cloud-based IoT smart systems.
Where classic data handling solutions demand hardware-intensive layers of PLCs, servers and PCs networked together, newer platforms are streamlined with the proper amount of connectivity and processing power. A fundamental building block for this next-generation solution is an industrially hardened component combining connectivity and computing power, optimized for data handling tasks and HMI/SCADA visualization.
An edge-located component of this type is not exactly a PLC, or a PC or an HMI—but includes some of the capabilities found in each of these components. It is built upon commercial technologies to offer a superior price/performance ratio, but fortified with features for reliable operation in harsh environments.
This type of edge component can function directly as an industrial controller, or inputs can be added to it for monitoring legacy systems. Where more advanced networkable devices are available, such as packaged equipment controls or IoT devices, the edge component can act as a robust gateway.
As many or as few edge components as necessary may be installed to gather data from other smart equipment, depending on the logistics of the sites. Each edge component acts as a bridge to connect other intelligent devices up to the cloud. Working together, these edge components form the backbone of a new architecture for HMI and SCADA.
Software Technology Enables Advancements
Hardware alone in the form of an edge component isn’t enough to power next-generation HMI and SCADA connectivity to IoT devices, as numerous open-source and built-in software technologies are also required to deliver modern HMI and SCADA systems. Here is a list of key features needed for an effective edge component, followed by an explanation as to the role of each.
- Linux operating system
- Native OIT/HMI options (onboard display and off-board via HDMI)
- Extensible to mobile and web-based HMIs, scalable for any device
- Built-in OPC UA drivers for popular PLCs
- Improved licensing (affordable, server-based, no tag limits, no client licenses)
- MQTT/Sparkplug for secure, outbound, IT-friendly communications
- Node-RED to deliver integrated cloud connectivity and data flow engine
Microsoft Windows is the most popular and familiar PC operating system (OS), and many HMI and SCADA platforms run on Windows. As the leading alternative open-source OS, however, Linux cost-effectively provides stability and security without demanding excess computing resources. It is already heavily used in IoT and other smart devices, making it a natural fit for edge processing.
While there are many data handling use cases for edge components to be “headless,” without any sort of display, if an edge component can offer a local display̶—and the ability to drive an even larger HDMI monitor—it is more useful for local operator interactions, and easier for designers to configure. Equally important is the ability to extend the HMI out to web-based and mobile HMIs, making the interaction experience scalable and seamless from any authorized user’s device.
Built-in OPC UA drivers facilitate native communications between the edge component and almost any popular PLC, and they can be combined with a reasonably priced software environment without costly and awkward tag limits and client licenses.
No edge component discussion would be complete without a mention of enabling technologies targeted at securely moving data. An open-source protocol called message queuing telemetry transport (MQTT) is specifically tailored to be robust and streamlined, even over less capable networks. More importantly, MQTT can initiate outbound communications, thus operating seamlessly over typical business IT systems, thus avoiding complex and hard-to-maintain network configurations. This is particularly important since it helps operations personnel to concentrate on their own processes, without having to rely on IT personnel. MQTT is often combined with a common industry specification called Sparkplug to efficiently deliver industrial-type messaging.
A browser-based tool called Node-RED provides a visual configuration interface to define data from sources and route it to destinations (like a cloud-based database) over various communication paths. Industry-standard Transport Layer Security (TLS) ensures all communications are secured with banking-level encryption. Once the data is in the cloud, one can extend their HMI and SCADA systems to anywhere worldwide with an internet connection.
All these acronyms add up to open-source, built-in software options geared exactly for helping you securely move data from the edge up to the cloud, while avoiding the expense, complications and pitfalls of traditional methods.
Conclusion
Next-generation HMI and SCADA technologies are available now to help you meet your automation goals. One example of an edge programmable industrial controller (EPIC) component of this type is Opto’s 22 groov EPIC (Figure 3).
Source: https://www.automation.com/the-next-generation-of-hmi-and-scada
