Should assets be monitored in-house or in the cloud?

It might seem like the internet has been around forever, but even many millennials can remember its infancy. Using internet technologies for industrial applications has been a more recent development, as it took time for users to be convinced of its value and suitability in manufacturing contexts, particularly in process industries. This historical digression reminds us that the tools offered by the Industrial Internet of Things (IIoT) are relatively new. Just a few years ago, any facility wanting to implement manufacturing asset condition and performance monitoring would have had to undertake those efforts internally or use specifically dedicated products.

The IIoT is indeed here, and the outlook is much different. More choices are available to support monitoring functions. Communication options have expanded, providing more opportunities for processing facilities wanting to implement such an asset monitoring program.

Start simple

Monitoring helps companies determine two things about an asset. First, its physical condition, so it is possible to know if it is running well or headed for a breakdown ─ hopefully before there is a failure that can interrupt production. Second, it can determine how an asset is performing and doing its job within the larger process. Both monitoring methods, used effectively, deliver financial returns to justify their cost.

Let’s look at a simple and straightforward example ─ pressure relief valves (PRVs) ─ to illustrate the differences between asset condition monitoring and performance monitoring. In most situations, PRVs (Figure 1) operate without anyone paying much attention. They open during an overpressure event and then reseal when the process returns to normal, but it isn’t unusual when they don’t reseal completely due to a worn seat, debris on the seat or other mechanical issue. Condition monitoring looks for valves leaking slowly without closing fully. Identifying which PRV has operated and for how long is critical to identify the root cause of a process mis-operation. The challenge is to pinpoint one or a few bad actors among thousands of PRVs in a timely manner because most of them discharge into an enclosed collection system, such as a flare.

Figure 2: An acoustic transmitter, such as Emerson’s Rosemount 708 Wireless Acoustic Transmitter, can listen for the characteristic sounds a PRV makes in various operational states. Courtesy: Emerson[/caption]

This is simple enough. The instrument creates data that shows what the PRV is doing and the network delivers it. But how does a company turn this data into information able to support decision making? The question has two possible answers:

• In-house project with on-premise data collection and analysis
• Cloud-based monitoring with subscription-based analysis.

Let’s examine these two approaches and determine if the situation must be one or the other.

Doing it in-house

Until recently, the in-house approach was really the only choice, and for many processing facilities, it is still preferred. The difference between today and even five years ago is the number of tools available to make such a program easier to deploy and use.

Traditionally, even if the wireless acoustic transmitters and supporting wireless networks were available, the plant would have to integrate this project into a larger historian platform where extensive interpretation is required, or, absent that, bring in a system integrator to create custom automation software to perform the data analysis and historization. Fortunately, there is a growing range of new options. Here’s a typical scenario:

Data from the acoustic transmitters is carried to the gateway where it can be differentiated from the process instrumentation data communicated on the same network. Therefore, data from the acoustic transmitters does not need to go to the process automation system, only the alerts, so it can be sent directly to the reliability and maintenance group, along with the environmental reporting group. Here software designed specifically to monitor PRVs collects the relevant data. The software can identify which valves are open due to an incident and which are fully closed.

Technicians see the data on a dedicated PRV condition/performance dashboard (Figure 3). If there is a problem, the software initiates notifications to technicians. Furthermore, once an event occurs, plant personnel can receive that alert immediately on their mobile device for prompt response. The software also interfaces with larger asset management and computerized maintenance management systems (CMMSs) that can issue work orders for repairs or replacement as appropriate.

All of this is supported and maintained in-house on the company’s servers, with data carried by internal networks and decisions made at the plant. Implementations like this can be approached incrementally, beginning small and scaling up as the ROI is proven. The supporting software platforms are flexible and easy to adjust as changes are needed. The most difficult challenge for most companies deciding to handle everything in-house is finding the internal personnel to support it, but this challenge is addressed to a large extent by the monitoring software’s ease of use.

These platforms are not maintenance-intensive, but key individuals must watch the larger picture and make decisions. A PRV application will likely not be a plant’s only monitoring project once it gets going. Many other classes of assets will likely undergo similar digital transformations. The support of these systems requires internal resources. In many cases, this can be personnel formerly tasked with monitoring these assets manually.

However, if this type of solution is not practical with existing personnel, it might make more sense to engage specialized outside help.

To connected services

Internet access adds new options for implementing a monitoring program. First and foremost, it is no longer necessary to do all the work in-house. Parts or all of it can be issued to subject-matter experts outside the organization on a subscription-based contract. Remaining with our PRV example, the same acoustic transmitters would be used, still communicating, but they might be owned and installed by the service provider.

The service provider uses specialists to perform the analytical services and deliver recommended actions, including recommending work orders for individual maintenance tasks. The provider even can staff technicians at the company’s site to carry out the hands-on service work.

While real-time information is available from the service provider to any authorized individuals within the company via mobile devices or a portal, there will also be periodic summary reports. Providers with extensive experience can offer observations on how the company is performing on a given metric compared with industry benchmarks. Since all the software and data storage are managed by the provider, there is no maintenance required by the end user, and the solution is scalable.

A process plant might begin a monitoring program as an in-house project. However, early successes frequently lead to a rapid increase in the number of monitored points, and the desire to expand into a wider range of areas so even greater returns can be realized. Leading assets typically monitored in process plants include:

• Heat exchangers
• Centrifugal pumps
• Cooling towers
• Steam traps.

As deployments grow, management will have to determine how it wants to apply in-house resources. At this point, many companies find it much easier to engage a service provider to move forward.

Best of both worlds

Projects may take advantage of both in-house and cloud-based methods (Figure 4). Once data is collected, it may go to analytics platforms at the company or a service provider. A company may determine that it wants some of the processing in-house but leave the more complex and specialized analysis and report generation to the service provider. In most cases, a company must decide what functions it can and should keep in-house based on asset criticality and availability of internal resources. Consulting with an established provider is a good first step if the end user doesn’t know where to start.

For example, a large gas turbine necessary to drive an entire facility will likely have locally supported monitoring for the sake of immediacy and quick response to incidents, while also using remote monitoring for asset optimization.

In-house driven projects are still a viable approach and the right choice for many companies thanks to the wide range of tools now available. However, adopting a cloud-based subscription service can often bring projects online faster and with fewer lessons learned the hard way. Fortunately, either is a viable choice today, or even a combination of both.

This article appears in the IIoT for Engineers supplement for Control Engineering and Plant Engineering. See other articles from the supplement below.

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