April 2023

Special Focus: Maintenance and Reliability

How companies can take advantage of APM solutions to reduce planned maintenance

According to Löfsten, “the costs of maintenance are estimated to be between 15% and 40% of production costs.” Consequently, efforts to reduce such costs without compromising risk to equipment, personnel safety and environmental integrity are welcomed.

Brooks, M., AspenTech

According to Löfsten,1 “the costs of maintenance are estimated to be between 15% and 40% of production costs.” Consequently, efforts to reduce such costs without compromising risk to equipment, personnel safety and environmental integrity are welcomed.

The function of maintenance should be to enable the level of product output required by the business at the minimum maintenance cost, while honoring the endemic risks. Typical approaches balance corrective maintenance with preventive maintenance. Corrective maintenance restores equipment function after it fails or is deemed to fail and covers strategies of planned run-to-failure and the unexpected failures with unplanned downtime. The most expensive maintenance is emergency maintenance after a forced shutdown when all resources are utilized in an urgent situation to fix the problem and restore production. Running equipment to the point of failure can cost 3–10 times the cost of regular maintenance.2 Consequently, preventive maintenance attempts to quantify potential failures and implement corrective action steps to ensure equipment does not reach a failure mode, thus avoiding such emergency costs.

Strategies for preventative maintenance

Strategies for preventive maintenance have been developed based on interpretations of the P-F curve: a simple diagram highlighting the transition from normal running equipment, through degradation, and functional failure up to catastrophic failure.

The P-F curve was first introduced in 1978 by United Airlines engineers Stanley Nowlan and Howard Heap. They performed a study for the U.S. Department of Defense that showed that repairing or replacing assets based on the condition was more effective than doing so based on age.3

The practice of preventive maintenance has been immersed in developing strategies to plan maintenance that reduces failure occurrences. The generally held consensus is that the interval for planned inspections should be at least half of the calculated P-F time—perhaps a distortion of the Nyquist frequency (or folding frequency), the highest frequency that can be restored from a recorded time sample  dataset4 to fully represent a situation, which suggests that sampling at half the P-F failure frequency is adequate to interpret failure frequencies. All of this is based on the assumed accuracy of the P-F time. This leads to an extremely labor intensive and costly strategy, along with variability and inconclusive efforts to discover the degradation that will lead to failure. In real situations, equipment that exhibits higher risk and consequences of failure would be inspected and serviced at a higher frequency, which elevates costs.

FIG. 1. The P-F curve.

Detecting impending failures with advances in condition-based monitoring

Fortunately, advances in condition-based monitoring, especially predictive analytics in asset performance management (APM) implementations, can greatly improve detection of impending failures (the P-F interval). This results in early action to prevent or correct equipment abnormalities and greatly reduces those costs. APM-based predictive maintenance uses advanced monitoring techniques with machine-learning algorithms to provide recognition of patterns that indicate normal operations, abnormal operations and the distinct patterns representing extremely early detection of impending failures. In effect, such techniques move the p-point much earlier, providing earlier warnings of degradation and failure in weeks and months, not just days. The main principle is a precise prediction of likelihood of failure affording an appropriate time window to determine the proper time for safe, planned maintenance intervention.

This is a sound strategy for critical equipment, but more unrealized benefits can emerge from considering a newer maintenance strategy involving automated monitoring. At the core of the technology is a monitoring engine that performs intense, detailed inspection of dozens—and up to hundreds—of variables on and around a piece of equipment. Such an engine is much more capable of recognizing more detailed patterns over many more dimensions in the multi-variate and temporal digital shadows than humans can. In addition, a monitoring engine can perform this duty every few minutes for earlier warnings of imminent and potential failures in months and weeks, rather than days.

In contrast, a planned maintenance inspection with a once-a-week or once-a-month schedule cannot compete with the inspection intensity or periodicity, and it cannot provide the extreme early warnings of equipment malfunction. Additionally, the capability and cost of such inspections on important but lower criticality equipment can be dramatic. One maintenance manager at a large processing plant declared 52% of his maintenance budget was absorbed by inspections on pumps, but not the highly critical equipment. A large South American oil company was able to reduce its annual maintenance budget by 25% by replacing several manual inspections with lower cost and more thorough automated services.

Determining the right time for a shutdown

Upon a prediction of time-to-failure, APM-based initiatives enable facilities to determine the optimal time to initiate the shutdown and advise the correct order of activities to minimize profitability losses. The shutdown can be planned according to the availability of spares and staffing resources. Knowing a failure is imminent enables the orchestration of an improved operations schedule leading up to and during the outage, which can facilitate honoring customer delivery commitments.

APM tools can also determine the actual or real criticality of a piece of equipment, not just as a standalone but as an integral part of the system as a whole, calculating its real value to the bottom-line production. Consequently, these tools can determine the absolute risk of poor equipment performance and the cost of different decisions on availability, redundancy, equipment sizing and process intermediate storage. This capability contributes significantly to plans made in the maintenance department and their bottom-line performance.

In all of this, maintenance does not stand alone, but as a functional department contributing to the wider financial and sustainability goals of a business enterprise. Reducing the estimated 15%–40% of production costs is a lofty goal. The first step is granting planned maintenance the early detection of malfunction to avoid unplanned shutdowns, plan orderly safe and shorter shutdowns where necessary, and minimize production losses. In addition, it soon becomes clear that using an APM monitoring engine in place of ongoing inspection services is cheaper and more thorough. This reduces manual maintenance costs and has a significant effect on overall plant profitability. HP


  1. Löfsten, H., “Measuring maintenance performance—in search for a maintenance productivity index,” ScienceDirect, January 2000.
  2. Auton, D., Penny, J., “Stop Wasting Money on Deferred Maintenance,” Cushman & Wakefield, Buildings.com, October 15, 2018, online: https://www.buildings.com/mechanical/article/10185912/stop-wasting-money-on-deferred-maintenance
  3. Bernet, J., G. Perry and D. V. Loon, “P-F curve explained: History, definition, importance,” emaint.com, March 3, 2022, online: https://www.emaint.com/blog-p-f-curve-explained-history-definition-importance/
  4. ScienceDirect.com, “Nyquist frequency,” 2013, online: https://www.sciencedirect.com/topics/earth-and-planetary-sciences/nyquist-frequency

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