By bringing condition monitoring to the remaining rotating machinery, plants could multiply efficiencies, ROI, and cost savings.

The financial risks of ignoring balance‑of‑plant assets

Reflect on this: a typical power generation facility may house hundreds of rotating machines. Traditionally, only the “few” critical machines are labeled as “critical” due to their impact on production and the substantial costs associated with their potential failures. Determining criticality usually means the machine:

  • Is un-spared (or not 100% spared)
  • Has a substantial direct impact on process stream
  • Operates continuously with planned outage intervals (measured in years rather than months)
  • Has safety implications if it fails
  • Has high downtime costs
  • Or is very expensive to repair

Your facility may have many or fewer assets, but these ratios generally hold true in terms of the “critical few” and the “less-critical many.” However, your balance-of-plant (BOP) assets can also dramatically impact critical assets.

Critical assets are individually impactful because if they fail, production halts instantly. Understandably, most asset health management efforts and budgets are focused on these critical assets—they are usually the best instrumented machines in the enterprise.

BOP assets—often around 99%—are collectively impactful. For example, efficiency losses that manifest in condensers actually start in BOP systems such as vacuum pumps, circulating water pumps, and cooling towers. However, they are under-addressed because the cost of monitoring them has traditionally been too high.

In place of condition monitoring, a laissez-faire approach to balance-of-plant maintenance is more common, often consisting of one or more of these actions:

  • Run to failure, which means putting off maintenance until the machine fails
  • Manual data collection and human-intensive review of alarms and data
    • Only feasible if collection frequencies are less than 1x per month
    • Not practical if failure modes progress faster than 1x month
    • Asset coverage is limited based on available resources
  • Online monitoring with manual review of alarms
    • Often impractical due to the large number of monitored machines—alarm fatigue becomes common
    • Overwhelmed by data, organizations are unable to turn data into actionable information
  • Some form of general AI
    • Known as “generic AI,” where data from various sensors is fed into a general-purpose AI model
    • Generally this approach will yield suboptimal results for quite some time because of the long timelines required to clean your own data as well as build and train the model

In general, reliability teams tend to deprioritize BOP monitoring simply because there are too many assets to monitor and too many alarms to make the data meaningful.

Rethinking your 99% strategy

A more nuanced, scalable approach needs to be implemented to transform the health and performance of your BOP machinery. To be effective, that approach needs to give you the ability to:

  • Use prescriptive diagnostics, including root cause analysis and repair recommendations, to rule out threshold-based alerts
  • Leverage purpose-built AI to filter for alerts that matter
  • Off load to the AI layer as much analysis, diagnosis, and prescriptions as possible to free up team bandwidth
  • Combine purpose-built AI with a large library of robust, clean data

As a result, early detection and diagnostics will help teams plan maintenance ahead of time instead of firefighting and facing emergency shutdowns.

System 1 Machine Health, powered by Augury, built for the power generation & energy industry

Bently Nevada’s System 1 Machine Health solution is purpose-built AI that works with Ranger Pro condition monitoring sensors. Instead of requiring teams to set up threshold-based alerts or decision-tree-based embedded rules, System 1 Machine Health leverages the collective knowledge of over 150 million hours of machines monitored to recognize failure patterns, diagnose root causes, and prescribe fixes.

By actively filtering in only the alarms that matter, System 1 Machine Health helps reliability teams monitor the 99% balance-of-plant machines with the same level of detail as a human, 24/7/365, without getting overwhelmed with alarm floods or wasting time on fire-fighting.

With System 1 Machine Health, you and your teams will be able to:

  • Reduce alarm fatigue and respond faster to alerts that matter
  • Focus on necessary maintenance routines and plans, days or weeks ahead
  • Lower inventory capital by ordering spare parts only when they are needed
  • Free up workers so that they can focus on high-value work
  • Eliminate unnecessary downtime and maximize production

Greater insight. Higher efficiency.

Increased insight means smarter use of time and resources—better prioritization and less unnecessary field work.

>CLICK HERE to learn how Machine Health could revolutionize your reliability program with our all-new eBook<