Intelligent equipment developed by today’s OEM machine builders helps their end user customers be more efficient than ever. Using IoT technologies, these smart machines report back to their OEM makers with performance and diagnostic data to improve support.
Benson Hougland, Opto 22
Manufacturing companies consider many criteria when shopping for production machinery. The equipment needs to perform correctly, reach proper throughput, be easy to operate and function reliably. To achieve these goals, today’s OEM machine builders are employing advanced automation techniques and adding Internet of Things (IoT) technologies. In fact, because powerful control and visualization devices are now available, end users expect this type of advanced functionality and interfaces in all the equipment they purchase.
As it turns out, many existing industrial automation technologies can enable much deeper interactions between machine builders and their customers, fulfilling the promise of the IoT. Traditionally, OEMs might hear back from their customers only for replacement part orders, or perhaps a service call for repair or preventive maintenance. Today’s more sophisticated OEMs, on the other hand, can apply automation techniques so the machine can securely report back to the builder through the internet with extensive performance and diagnostic information. Enhanced machines of this type are often referred to as “smart” or “intelligent.”
With feedback from intelligent machines, equipment builders can more quickly and effectively support their customers. Furthermore, OEMs can use the information to pinpoint problem areas or identify operating trends. The data exchange thus benefits both OEMs and their end-user customers.
Today’s OEM machine builders are looking to “close the loop” by gathering information from machines they have deployed in the field at customer sites (Figure 1). But although a wealth of information is available, transporting it can be challenging. End user networks may be configured and secured in a way that restricts communications outside the plant walls. Fortunately, several standard technologies can overcome these difficulties, and do so with appropriate security.

Smart-enabled machines deployed at customer sites can not only produce parts and assemblies, but also provide a wealth of operational and performance data.
Let’s look at common challenges and solutions, starting with the types of machine data valuable to OEMs and end users alike.
Valuable data
OEM machinery provides immediate and tangible value when it runs well, produces efficiently, and rarely requires any attention. Many end users would not look far beyond these basics. Yet OEMs and their end user customers alike can find more value by delving into the extensive data many machines can provide, and analyzing these data to create actionable information.
Here are several categories of data that can inform machine builders:
–Equipment speed and production throughput
–Runtimes and cycle counts
–Uptime/downtime
–Energy usage
–Alarms
–Events
–Operator actions and responses
And here are some of the ways OEMs can use these data:
–Evaluate overall equipment effectiveness (OEE)
–Improve machine uptime
–Predict problems before they occur
–Help operators respond more quickly to problems
–Develop fixes to existing machines
–Engineer improvements to new machines
Fundamental metrics such as equipment operating speeds, production throughput, runtimes, and cycle counts are basic information required by most end users. Similarly, tracking uptime versus downtime can provide insight into how well the machine is running.
Knowing what constitutes “good” or “bad” values could be tough for end users to discern, even if they have several machines to compare. On the other hand, these data can take on new meaning for OEMs when it can be viewed in the context of many machines across a broader sample of deployments.
As experts in the design of their machines and their capabilities, OEMs are best positioned to critically review performance data (Figure 2). Through analysis, normal operating ranges can be determined, so it becomes far clearer when a machine is or is not operating at peak performance. With the right source data, it is possible to develop OEE measurements for comparing machines. OEE calculations quantify the availability of the machine, including when it is expected to run, the speed at which it operates, and the amount of quality output it produces.

Viewing operational data sourced from equipment installed at customers’ sites allows machine builders to respond more quickly to issues, and to predict problems before they occur.
Identifying the sources of downtime is always of interest to improve uptime. Downtime can be due to stoppages downstream, shortages upstream or on-machine problems. When OEMs can quantify the root causes of downtime, they can address any problems on the machine, or point end users to other in-plant problems.
Energy usage is typically considered from a cost-to-run perspective, but it can also be used to pinpoint failing bearings or other drive equipment problems. Similarly, high alarm counts indicate trouble areas for investigation. OEMs can use this type of data to predict problems before a complete breakdown occurs.
Any number of other machine-specific events can be monitored and acted upon in the same way. In fact, it is often instructive to monitor operator actions and how operators respond (or don’t) to problems. This provides OEMs with some insight into how the equipment is being used and often reveals areas for improvement.
Implemented properly, an entire OEM machine can become an IoT edge device of sorts. Short-term goals for obtaining and using data are simply to keep the end user’s machines running well. But the long game is for OEMs to keep learning from their machines. This can enable them to develop fixes for existing machines where necessary, and can also provide an experience base for building improvements into future machines.
But getting the data from OEM machines at customer sites can pose challenges.
Data connection challenges
It is already quite common for most manufacturing sites to maintain a high-speed internet connection and multiple Ethernet networks. Likewise, most modern IoT devices and intelligent machines either use networking elements or offer a network connection. For OEMs to access machine data and support their customers, intelligent equipment must take advantage of these on-site networks and the internet. However, making this connection can be challenging.
The most common issue is that most sites protect themselves behind a firewall, as they should for security reasons, which prevents devices outside the firewall from initiating communications. While this is the established method for preventing digital intrusion, it can also prevent outside OEMs from connecting to their machines. Compounding this issue, many customers prefer to keep their machinery isolated on a manufacturing network, separate from the business network, to ensure a higher level of security.
Another complication is when manufacturing facilities operate many identical machines, each of which is supplied from OEMs with a typical IP address. A common approach is to install these identically addressed machines behind network address translation (NAT) devices. Making use of NAT is an ideal solution for internal purposes, but this interposing layer further complicates the ability for an OEM to connect to their smart machines.
As long as customers are willing to connect intelligent equipment to an internet-capable network, there are ways to enable communications through firewalls and NAT devices. Dedicated virtual private networks (VPNs) are a primary way, but they require involving a site’s information technology (IT) personnel. Unfortunately, IT personnel typically have little familiarity with operations equipment, and configuring the desired communication paths can be tricky to set up, and cumbersome to maintain and troubleshoot. A different method is therefore required for OEMs to easily and reliably make the connection with their customers’ machines.
A better way to communicate
Over the years, industrial automation products and technologies have improved in performance, ease of use and capabilities. One important development is communication methods. While there are many mission-specific fieldbus protocols, we will take a closer look at how Ethernet connectivity and protocols have evolved to achieve remote connectivity.
Adoption of an open-source communication protocol called message queuing telemetry transport (MQTT) has been a key development. A related specification called Sparkplug defines an industrial-friendly data-messaging format. Combined, these technologies enable what is called publish-subscribe communications.
Instead of an outside entity (the OEM, for instance) attempting to poll customer machines for data following a request-response model, MQTT and Sparkplug enable a machine to establish an outbound publish-subscribe connection. Because it is outbound, this connection immediately overcomes the firewall and NAT challenges described earlier. The OEM machine develops the communication link to an outside “broker” with no IT involvement necessary.
MQTT is very lightweight and able to withstand slow network connections or interruptions. It also does not place heavy burdens on networks, ensuring there are no negative impacts on a customer’s site or operations. The data from any number of machines or user sites worldwide can be published to a centralized cloud location where the OEM can subscribe to access it as needed (Figure 3).

Outbound connections initiated by intelligent OEM machines overcome the complexity of network address translation and firewalls, allowing machines to report critical performance data to the builder.
Because these communications are outbound only, customers can leave all site-security systems in place. These internet communications can also take advantage of industry-standard Transport Layer Security (TLS) provisions, such as banking-grade authentication and data encryption. MQTT itself offers an additional layer of credential checking to ensure proper clients are connecting with the broker. Thus, there are many protections to safeguard sensitive data.
OEM machine builders can take advantage of commercial off-the-shelf (COTS) products that combine all these abilities and more. For instance, Opto 22’s groov EPIC (edge programmable industrial controller) includes the necessary data collection, storage, processing, and sharing features (Figure 4). It also contains a full-fledged controller and human machine interface (HMI). OEMs can economically layer the groov EPIC on top of existing automation to gain the new capabilities, or they can adopt it as an all-in-one solution.

An edge programmable industrial controller, such as this groov EPIC from Opto 22, can be used by machine builders to collect, process, store and share operating data—as well as directly controlling equipment.
There are many reasons for enabling smart machines to connect to their OEM makers. Not only can OEMs benefit from these communications, they can also better serve their end user customers who operate the equipment daily. Common technical and security challenges can readily be overcome using a new generation of COTS devices, open-source protocols and IoT technologies.
Opto 22
www.opto22.com
Filed Under: Design World articles, IoT • IIoT • internet of things • Industry 4.0, Networks • connectivity • fieldbuses