An adage attributed to marketing pioneer John Wanamaker goes like this: “Half of the money I spend on advertising is wasted. The trouble is, I don’t know which half.” Maintenance managers in many process manufacturing facilities may feel something similar.

When maintenance actions are not driven by equipment-condition data, time and resources can be wasted performing unnecessary actions on equipment that is performing well. At the same time, assets that need attention do not receive it, causing production outages.

Failures of critical production equipment during operation can cause major disruptions and even safety incidents. The financial impact of such situations can drag down profitability by reducing income while simultaneously increasing costs related to unplanned repairs or premature replacement. Even the aftereffects rob productivity: Maintenance and reliability staff spend time investigating such incidents to determine the root causes.

Various traditional solutions are offered for this conundrum. One approach suggests simply accepting the situation as an unavoidable reality and mitigating the effects by installing lots of redundant equipment. When Pump A goes out, switch to Pump B. This works to some extent, but it is costly in equipment and creates extra work for the maintenance staff.

An alternative approach suggests performing a prescribed maintenance routine. Continuing the pump example, under this approach, a plant would service Pump A every six months, replacing all of the potentially troublesome parts whether they need it or not. This approach can consume a lot of resources. Worse, unless the maintenance intervals are well understood and planned effectively, Pump A might break down three weeks ahead of the scheduled maintenance interval. This would force the technicians to deal with an unscheduled outage — and possibly delay other scheduled maintenance actions. The disruptions ripple out from there.

Eventually, maintenance and reliability managers ask, “How do we know what equipment needs maintenance before it breaks down and has a serious effect on production?”


FIGURE 2. This diagram shows how the eight sources of production losses interact to reduce profitability from a facility by slowing down effective output. OEE is a key method to quantify these losses.

Techniques for Evaluating Condition

A range of diagnostic equipment exists to help maintenance staff evaluate the condition of manufacturing assets. Want to know how the bearings are in Pump A? An old-timer technician would listen using the screwdriver-handle-to-the-ear technique. Most people able to do that with any skill probably retired long ago, however. Fortunately, modern electronic probes can capture more sounds and analyze them over time to detect changes. In the hands of a well-trained technician (figure 1), these devices can provide highly insightful information. The facility must have the well-trained technician, however. Also, he or she must have the right diagnostic device — and the time needed to get to Pump A often enough to make a difference.

Of course, pumps are just one of the many assets in a typical process plant. Evaluating a valve actuator requires different skills and equipment than a compressor. Sufficient personnel are not always available in many facilities.

Many field devices such as transmitters for process instruments (pressure, flow, level, temperature, etc.) and smart valve controllers have sophisticated internal diagnostic capabilities. These diagnostic results can be sent to a host system in a wired environment using HART or a fieldbus such as Foundation Fieldbus or Profibus. In wireless environments, ISA100.11a can carry diagnostic and other data. The problem is that few companies monitor such devices continuously to capture the information.

Survey results vary, but most suggest that the number of plants using intelligent device data continuously is well below half at best. Some of this relates to legacy environments where I/O supporting automation host systems do not have the necessary capability to capture and convey the data. Supplemental systems added to existing environments tend to be cumbersome and complex to administer.

Even in environments where the infrastructure is up to date, there may not be a platform to capture, historicize and analyze the information. Without this, it is merely data, unusable as a means to inform decision-making. There is an enormous gap between raw diagnostic data and an informed, well-functioning maintenance program.

Valves chart

FIGURE 3. Valves from a variety of suppliers can be monitored with a resource-management system.

What Can Effective Maintenance Accomplish?

The challenge facing maintenance and reliability managers is — first and foremost — production losses: those things able to keep the plant from achieving the highest possible output. Eight causes of such losses are:

  • Planned shutdowns, where production is intentionally halted for various reasons.
  • Production adjustments, which also are intentional.
  • Equipment failures, which cause sudden loss of function.
  • Process failures, which stop production.
  • Out-of-specification startup conditions, which can prevent production from achieving full output.
  • Minor interruptions, which may be planned or unplanned.
  • Defective product, which wastes production time and resources making something inferior.
  • Rework, which is redundant effort to bring a defective product to a sellable level.

For any plant, it can be a telling exercise to examine a block of time and see how each of the above causes has impacted production.

Maintenance — no matter how effective — cannot address all eight of these issues directly. At the same time, degrading performance or unpredictable breakdowns may contribute to all, in one way or another.

Maintenance efforts can have the greatest effects on four causes — equipment failures, process failures, startup conditions and minor interruptions — but improvements may be seen in other areas. Efforts to use diagnostics should focus on these areas as the root causes of most disruptions.

A facility or company trying to evaluate its own performance or to set goals for improvement can use overall equipment effectiveness (OEE) as the yardstick. OEE represents the product resulting from multiplying plant availability times performance times product quality (figure 2). A reduction in OEE invariably means a reduction in profitability.

Determining OEE requires a large amount of data to generate quantitative values. This is difficult to do with manual performance and maintenance data collection. Also, improving OEE requires one to calculate it first, in a way consistent enough to allow meaningful before-and-after comparisons. This also requires automated data collection and analysis.

Launching such a project may sound like a huge undertaking, but there are tools to make it possible and practical, with a relatively quick return on investment.


FIGURE 4. Cavitation produces minute pressure differentials that can be detected before damage occurs.

Defining a Plant Resource-Management System

The suggestion of launching a major project related to maintenance and reliability will likely be met with some reluctance because:

  • Plants generally consist of a mix of equipment types and vendors, so anything trying to tie them together will have to be highly adaptable and flexible.
  • Resources for any new projects are hard to come by. Seemingly, every department is asking for something, so maintenance must make a strong case for how implementing this program will create a sufficient return on investment.
  • The people needed to undertake such a launch are probably already engaged with other responsibilities or may be new with limited experience. Seasoned technical veterans are getting harder to find.

With these realities, using a platform able to manage plant resources generally and manufacturing assets specifically is important. What does such a platform look like?

  • A plant resource-management system must provide capabilities that are able to reduce maintenance costs associated with plant equipment of many kinds.
  • It must support better utilization of these resources from the point of view of maintenance and operations.
  • Where there is not already sophisticated I/O supporting smart field devices, a field network must be added to remotely monitor each device and update system status.
  • Any indications from the diagnostics of any developing failure within the device itself or the immediate process area must be captured and reported. These might include detecting possible valve malfunctions, clogged pressure pipes/impulse lines, cavitation or other issues.

Such systems depend on leveraging digital technology to the fullest. For example, if a plant has a mix of shut-off and control valves that use digital valve controllers and smart actuators from multiple vendors, a plant resource-management system must be able to communicate with every one of those devices. It will capture data in the way the original vendor presents it and perform the supporting analysis without the need for custom code.

The management system must provide plug-ins to accomplish these and other tasks. Even if they are not a valve vendor, an automation supplier can provide these types of services through distributed control, plant resource management and other systems.

Once the plug-in is installed, the system can automate commissioning and periodic loop checks to save time. If the diagnostic capabilities detect something — a transmitter failure causing a corrupted process-variable reading, for example — it can send a message to the control room so operators will know they need to take appropriate action.


Real-time diagnostics from valves, meters and other devices helps operators keep close track of their status and identify maintenance issues before one fails.

Building on Smart Device Capabilities

As already discussed, plant resource-management systems leverage the capabilities of the smart transmitters built into process instruments and valve controllers. Such capabilities have been built into most transmitters for the last 10 to 15 years. The degree of sophistication has evolved over that time, however, and all manufacturers do not use the capabilities of the smart transmitters in the same way. Moreover, the diagnostic capabilities of a magnetic flow meter, differential pressure transmitter and digital valve controller will be much different. For purposes of this article, we will consider general similarities.

So, how can these capabilities be put to work? Let’s look at them across a plant lifecycle:

  • Commissioning.
  • Equipment configuration management.
  • Daily maintenance.
  • Equipment replacement.
  • Turnarounds.

Commissioning. Sending technicians and operators around the plant to check terminations, verify loops and create reports is time consuming and error prone. When launching a new plant or restarting from a major turnaround, a resource-management system can automatically check loops using HART and Foundation Fieldbus and then complete the task by generating reports.

Equipment Configuration Management. When information is not managed centrally, parameter tracking becomes largely manual and is difficult to keep up to date. A resource-management system can maintain a central store of equipment data, making it easier to keep information current. It also is possible to do bulk parameter settings of devices by using a prepared template.

Daily Maintenance. Finding time for technicians to check equipment manually often slips to low priority, so the work does not get done regularly. A resource-management system watches device diagnostic information continuously, and it is available continuously and remotely as needed.

Equipment Replacement. If a field device needs to be replaced, the installing technician must determine how the old unit was configured and attempt to duplicate it manually. By contrast, a resource-management system stores the configuration for every device. It is a simple matter to upload the configuration to the new unit, without needing to hunt for settings or input them manually.

Turnarounds. Making manual checks of hundreds field devices during the time constraints of a turnaround schedule can run experienced technicians ragged. A resource-management system has condition data on all field devices, so only those needing attention are addressed, and the technicians know exactly what has to be done in advance.

Case in Point: Improve Valve Maintenance

An example will show how a plant resource-management system can leverage the capabilities of the smart transmitters to improve valve maintenance.

Valve Diagnostics. There are more narrowly focused ways to apply this approach for specific types of manufacturing assets. As mentioned earlier, valves tend to be a maintenance headache in many plant environments because they are frequently called upon to move to a commanded position. When the correct plug-in for a given valve type is loaded into the resource-management system, it becomes a simple matter to monitor the diagnostics (figure 3). The system can look for:

  • Stiction.
  • Opening deviation.
  • Linkage abnormalities.
  • Hunting.
  • Air supply pressure.
  • Seal or gasket leakage.

Long-term data retention from frequent tests and operational information can be used to spot changes indicating mechanical degradation and call for appropriate maintenance. Key performance indicators (KPIs) can be established for critical valves to ensure they are performing as needed.

Cavitation Detection. Other more specialized abilities include the ability to detect process abnormalities such as cavitation (figure 4). Various devices can detect advanced cavitation due to the characteristic “pumping rocks” sound it produces, but this is long after damage to the pump and piping could already be happening.

It has been difficult to detect the early signs of cavitation before substantial damage occurs. With early detection, plant personnel can spot developing problems and take corrective action to avoid pump damage or total failure.

With one system that addresses cavitation, a high sensitivity differential pressure transmitter collects unfiltered pressure data from the suction side of a pump. Advanced analysis distills the differential-pressure data to create actionable information and identify plausible root causes for pump cavitation occurrences. The system automatically monitors unfiltered pressure data to detect minute fluctuations, which is a precursor to more serious cavitation issues. With this data-driven information, maintenance engineers can develop the preventive maintenance plans for reliability programs to improve pump operations.

Driving improvements in plant uptime and maintenance efficiency requires a clear understanding of the plant’s condition at all times. Collecting diagnostic data using smart devices and analyzing it using intuitive presentation with dashboards and key performance indicators (KPIs) can help achieve operational excellence and plant profitability. With effective implementation, it is possible to build on initial successes to realize greater improvements. 

3 Case Studies Show How Plant Resource-Management Systems Can Help

Condition monitoring is not a new technique. Due to advances in field device, networking and asset-management software technologies, it is becoming easier and less expensive to implement. These and other related improvements reduce implementation cost and time, reducing the payback period for condition-monitoring projects.

Condition Monitoring at a Coal-Chemical Plant

A petrochemical company built a new 600,000 tons per year methanol-to-olefins (MTO) plant and a 100,000 tons per year polypropylene plant, along with all the necessary utility and auxiliary facilities, in China.

The MTO plant uses catalysts to convert coal-derived methanol into olefins such as ethylene and propylene. This MTO project uses a proprietary process characterized by high olefin selectivity, high methanol conversion and low catalyst consumption. To ensure safe and stable operations at this MTO plant, which handles materials that are highly flammable and explosive, precise process control is required.

For this large-scale greenfield MTO plant, the main control system supplier delivered a process control system and a plant resource-manager software package for plant-asset management.

The MTO plant has a large number of HART-enabled pressure transmitters, flow meters, valves and other devices from different suppliers. Real-time diagnostics from these devices helps operators keep close track of their status and identify maintenance issues before a device fails. For central management of these devices, they are all integrated with the process control system via plant resource-manager software package.

Using the HART protocol and the process control system network, the plant resource-management system gathers the device data and diagnostic information in a single database. If a device problem is identified, engineers are able to check the device in time and clarify the cause. This centralized asset management minimizes trips to the field and ensures a more proactive maintenance approach. During plant startup, this system also helped the engineers check all loops.

Condition Monitoring at an Olefins Plant

A petrochemical complex in Thailand produces 900,000 tons per annum (tpa) of ethylene and 800,000 tpa of propylene, which are used in downstream plants to produce 400,000 tpa of high density polyethylene and 400,000 tpa of polypropylene.

The main automation contractor worked closely with the engineering, procurement and construction (EPC) contractor to deliver a control and instrumentation solution for this greenfield project. It included a production control system; a safety instrumented system; process gas chromatographs; analyzers; an analytical instrument management system; HART differential pressure transmitters, temperature transmitters and flow meters; asset management services; an event analysis package for alarm reduction; and an advanced process control package.

To manage the more than 5,000 field instruments installed throughout the large complex, the end user company opted for a remote-monitoring solution based on main automation contractor’s plant asset-management software. It reduces the maintenance workload for field technicians and generates summary reports for future reference. It is backed by asset-management services that monitor the system continuously to identify issues and implement corrections to improve both availability and performance rate while reducing maintenance costs over the plant lifecycle.

The olefins plant has approximately 20 critical safety valves that are rated for safety integrity levels 1, 2 and 3 — and each needs to be checked periodically. The plant-resource manager’s partial-stroke test function allows these tests to be run from the control room. This eliminates the need for technicians to go to each device to manually check operation, reducing workload and improving safety.

Condition Monitoring at an Ethylene Plant

A Brazilian petrochemical company completed commissioning of an ethylene plant within a petrochemical complex. This plant uses ethanol produced from sugarcane as its feedstock to produce 200,000 tons per year of bioethylene, also known as green ethylene. As such, it is the world’s first commercial-scale plant of its type to use 100 percent renewable raw materials.

At an adjacent polymerization plant in the same complex, the green ethylene is converted into polyethylene resin and plastic for sale to various consumer packaged goods companies.

The main automation contractor engineered, installed and commissioned an integrated control and instrumentation solution that included a process control system, a safety instrumented system, Foundation Fieldbus devices and plant resource-manager software.

To get the most out of its assets, the end user company decided that all the field devices at the new plant should be interconnected using Foundation Fieldbus. For a solution, they turned to the main automation contractor due to its experience implementing Foundation Fieldbus solutions. The company configured pressure transmitters, differential pressure transmitters, magnetic flowmeters, Coriolis flowmeters, temperature transmitters and valve positioners — as well as other vendor’s devices — in about 200 fieldbus segments throughout the plant. Prior to plant startup, all device configuration was done using field device management technology. By using the plant resource-manager’s function view window, engineers working in the control room were able to speed up the process of checking loops and confirming valves.

With the plant now fully operational, plant operators receive a steady flow of data from field devices. From them, status of both process conditions and field devices can be confirmed on the plant resource-manager’s display in the control room.

case studies

As these three examples show, driving improvements in plant uptime and maintenance efficiency requires a clear understanding of the plant’s condition at all times. Collecting diagnostic data using smart devices and analyzing it using intuitive presentation with dashboards and key performance indicators can help achieve operational excellence and greater plant profitability.