Smart devices make the difference when determining shutdown causes

Succeeding generations of technicians, and technologies, change plant-floor diagnostics.


Figure 1: When connected to a smart device, a smartphone becomes a diagnostic tool for the plant floor. Courtesy: LittelfuseA process shuts down unexpectedly. A plant technician is called to find and fix the problem. No one witnessed exactly what happened. The technician must therefore systematically inspect the equipment involved. He or she might restart the process, hoping to make it repeat the fault condition. However, numerous components are involved. Applying diagnostic tools to any one of them is time-consuming, and the technician typically can focus on only one process component at a time.

Today's Industrial Internet of Things (IIoT), including wireless smart devices, can help rectify the situation. The technologies involved do so by giving technicians quick access to the right information. They can quickly determine which equipment was not involved, reducing troubleshooting time. In addition, smart, connected devices deliver real-time information during a process restart. These valuable diagnostics were virtually unavailable or financially impractical on factory floors until recently.

What makes this an urgent topic is that maintenance budgets are under pressure even as population demographics indicate our most experienced and skilled technicians and engineers are near retirement or already retired. Those taking their places may know the latest software tools, but how good is their understanding when it comes to the best way to diagnose a failed or failing motor or pump?

In these circumstances, wireless and other IIoT technologies can deliver real support to troubleshooting efforts, matching emerging technologies with a new generation of technicians.

Purpose of convergence

It has been widely remarked that operations technology and information technology (IT) are converging. Tools being used on plant floors today reflect that. For traditional operations people—many of whom have been around for as many as 30 years-the primary tools are the voltmeter, ammeter and oscilloscope. These individuals have the skills and qualifications to enter a "live" panel and work in it safely.

Those from an IT background, on the other hand, have a modus operandi that tends more to plugging in an Ethernet cable and going back to the office, or using a smartphone, to view the relevant data. They're probably not very comfortable getting into live equipment, nor do they have the experience with the tools that the previous generations used regularly. Yet trends indicate that these are the people who will be handling maintenance duties in the future.

Although wireless monitoring is useful, it's most useful when integrated into an asset-management system. However, at the same time, tethering a smart device to the asset-management system can be a challenge, because locating data for a given component or sensor requires going to a dedicated terminal. For troubleshooting, it's better to have access to the asset-management data from the plant floor, without recourse to a dedicated workstation being necessary.

An example of a smart device that can prove very useful, if not tethered to the asset-management system workstation, is a motor-protection relay. A motor-protection relay monitors for multiple faults, including overloads, underloads, undercurrent, current imbalance, phase loss, phase reversal, overvoltage, undervoltage, voltage imbalance, rapid cycling/jog, contactor failure, zero-sequence ground fault and motor overtemperature. Most motor-protection relays have a networking connection that allows their use with Modbus, DeviceNet, Profibus, Ethernet or some other network standard.

Even short-range wireless connectivity allows a plant-floor technician access to all appropriate data, including the fault history, for example, from the motor-protection relay. Technicians also have access via a smartphone application to all associated information in the cloud, including manuals, datasheets and the like.

Data needs context

Like IIoT itself, "Big Data" is useful as a concept because it reflects the growing power of information technology in industrial-operations environments. As a term having a certain currency, it is part of the realization that a lot of the process data we already have in hand or which we can easily acquire will now cost-effectively be put to good use.

Data, however, is of little use to a factory-floor technician unless it's properly filtered and context provided. In today's world, a technician might spend hours or days sifting through normal readings to find anomalies. This wastes time and is a negative incentive for any technician who wants to be productive. The service person needs data pertaining to the exception, not the rule.

As an example, let's say in the past there was a power problem. To address the situation the first step was that someone from a utility company hooked a logging meter up to the power system. Once a minute, it printed out a set of voltages. The utility company left it logging for days. Eventually, a representative would say, "Well, everything looks good to us; here's a stack of paper that we just printed out; we didn't see anything wrong there."

All the stack of paper proves is there were many long hours of normal operation. The one or two bad readings in that paper stack that it would be useful to know of, may take some time to uncover.

Storing data in the cloud may be more convenient and promise better productivity, but digital records are often just as poorly utilized as that stack of paper. We should be very specific about what we store and not just store everything we can, even if we have the room to do it and it's not expensive. There must be a purpose behind all of it, and we must be able to use it quickly and easily, to our advantage. 

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