Moving Beyond Detection to Deliver Reliability

For maintenance managers and reliability professionals, identifying a problem is only the beginning. The real objective is preventing it from happening again.

In demanding industries with processing and manufacturing equipment that operate under high loads, harsh environments, and tight production schedules, when a gearbox, hydraulic system, or bearing fails, the cost extends far beyond replacement parts. Uptime, safety, and production are on the line.

Oil analysis plays a critical role in early detection. But when advanced diagnostics are applied, it becomes a powerful tool for root cause investigation.

Routine Testing Identifies the Symptom

Standard oil analysis parameters like wear metals, contamination levels, viscosity, oxidation, and particle counts are essential for trending and early warning. They answer important questions like: Is wear increasing? Is contamination entering the system? Is the lubricant degrading prematurely?

However, for reliability engineers tasked with eliminating repeat failures, elevated iron levels or rising particle counts just aren’t enough. Those results identify the symptom – not the failure mechanism.

Understanding the mechanism is what drives corrective action to prevent future problems.

Filter Debris Analysis: Examining What the Filter Captures

In high-load applications common in production and manufacturing operations, significant wear debris is often captured by the filter before it can be detected in a standard oil sample.

Filter Debris Analysis retrieves and evaluates that trapped material, providing a clearer picture of active damage. Using Analytical Ferrography and Micropatch testing to examine particle size, morphology, and composition, analysts can determine whether the debris originates from rolling element fatigue, gear tooth spalling, severe sliding wear and even break-in conditions versus progressive failure.

For a maintenance manager, this level of detail supports informed, smarter decisions; to continue operating under monitoring, schedule a controlled shutdown, or take immediate action. It replaces guesswork with evidence.

Define the Wear Mode

Analytical Ferrography testing uses magnetic separation and microscopic examination to characterize wear particles in detail. This method distinguishes between wear modes and can answer these questions:

Are wear particles caused by rubbing wear during normal operation?
Is it cutting wear caused by abrasive contamination?
Is lubrication film failure causing severe sliding wear?
Is it fatigue wear caused by surface distress?
Are chemicals causing corrosive wear?

For facilities where contamination control and lubricant performance are critical, identifying the wear mode is often the turning point in a root cause investigation.

For example, severe sliding wear may indicate inadequate viscosity selection or excessive load. Cutting wear often traces back to contamination control deficiencies in breathers, seals, or overall maintenance practices. Fatigue wear may reveal misalignment or load distribution problems.

Without microscopic confirmation, these distinctions are difficult to make. With it, corrective actions become targeted and sustainable.

Microscopic Contaminant Identification: Finding the Entry Pathway

Contamination remains one of the leading root causes of equipment failure across all industries. Advanced microscopic analysis can identify:

• Silica from environmental dirt
• Process materials unique to processing and manufacturing facilities
• Fibers from filters or cleaning materials

Reliability managers can use this information to address ingress points, refine storage and handling practices, or adjust filtration strategies. Instead of repeatedly changing oil, facilities can eliminate the source.

Turning Data Into Reliability Strategy

For reliability engineers, the goal is not simply monitoring machine health – it is building a no-surprises culture around asset performance.

Advanced oil analysis techniques such as Filter Debris Analysis and Analytical Ferrography transform a condition monitoring program into a diagnostic partnership. They provide evidence-based insight that supports root cause analysis, justifies maintenance planning decisions, and reduces repeat failures.

In high-demand production environments, that distinction matters.

Oil carries the story of what is happening inside your equipment. When you look beyond the numbers and examine the evidence, you move from reacting to failures to preventing them. And that is where real reliability gains are made.

In industrial and manufacturing facilities, lubrication and condition-monitoring programs focus on equipment that runs every day, such as compressors, gearboxes, pumps, turbines, and hydraulic systems that keep production moving. These critical assets are often routinely sampled, trended, and reviewed because their failure has an immediate and visible impact on operations.

But there is another side to operations that often receives less attention until it’s urgently needed in emergencies: backup power generators.

When backup power fails, the consequences aren’t minor – they’re catastrophic. You can’t troubleshoot an oil problem during a grid failure.

Backup generators are expected to perform flawlessly under the worst possible conditions, during storms, grid failures, or emergency shutdowns. Yet many facilities treat them as “standby” assets rather than mission-critical ones. The reality is simple: when backup power fails, the consequences can be severe, resulting in lost production, safety risks, equipment damage, and costly downtime.

Fluid analysis plays a critical role in ensuring backup generators are ready on a moment’s notice in the event they’re needed to maintain uninterrupted operations.

Standby Equipment, High Consequences

Unlike continuously operating industrial equipment, backup generators may run infrequently or under variable conditions. Long idle periods, short test runs, and sudden load demands introduce unique risks that traditional time-based maintenance alone cannot fully address.

Oil degradation, fuel contamination, and coolant issues often develop quietly while generators sit idle. Without routine fluid analysis, these problems remain hidden until startup, and when it’s far too late to correct them.

The worst time to discover a fluid problem is the moment you need your generator to perform.

Treating backup generators with the same condition-based mindset applied to primary assets is essential for reliability.

Oil Analysis: More Than Just Hours on the Meter

Oil analysis is often associated with runtime hours, but for backup generators, time and environment can be just as damaging as operation.

Routine oil testing helps identify:

• Oxidation and oil degradation during extended idle periods through Viscosity, Oxidation, and Base Number (BN) testing
• Contamination from dirt, moisture, or coolant leaks using Elemental Analysis by ICP and Water Content
• Abnormal wear metals indicating internal component issues through Elemental Analysis by ICP and Ferrous Debris Monitoring testing
• Improper viscosity or additive depletion that can reduce engine protection and lead to accelerated wear

Trending oil results over time allows maintenance teams to distinguish between normal aging and developing mechanical problems. This is especially important for generators that may appear “healthy” based on limited run hours but are slowly deteriorating internally.

The Most Overlooked Risk: Diesel Fuel

Fuel quality is a leading cause of backup generator failure. Diesel fuel can degrade significantly during storage, especially when exposed to moisture, temperature fluctuations, or poor housekeeping practices.

Routine diesel fuel testing helps monitor:

• Water contamination and condensation through Karl Fischer testing
• Microbial growth that leads to sludge and filter plugging through Microbial and Adenosine Triphosphate (ATP) testing
• Fuel stability through Thermal Stability and fuel acidity through Copper Corrosion testing
• Contamination through Viscosity and Flashpoint testing
• Identify fuel type and detect the presence of petroleum-based contaminants using Distillation, API Gravity, and Cetane Number testing
• Particulate contamination that can damage injectors using Particle Count testing and Elemental Analysis by ICP testing to detect signs of dirt and tank corrosion

Fuel-related issues often surface only during startup or load testing: exactly when reliability matters most. A proactive diesel fuel testing program enables corrective actions, such as fuel polishing, tank cleaning, or additive treatment, before an emergency occurs.

Coolant Analysis: Protecting the Engine You Can’t Afford to Lose

Coolant condition is critical to engine health, yet it is frequently under-tested in backup power systems. Depleted inhibitors, improper chemistry, or contamination can lead to corrosion, liner pitting, overheating, and premature engine failure.

Coolant analysis provides insight into:

• Freeze point and boil protection through Glycol Concentration and Freeze/Boil point testing
• Signs of glycol breakdown and degradation through Ion Chromatography
• Additive depletion and corrosion inhibitor health using pH, Reserve Alkalinity, Nitrite/Molybdate testing, and Organic Acid Monitoring through High Performance Liquid Chromatography (HPLC) testing
• Contamination from oil, diesel fuel, or external sources through Visual Analysis and Elemental Analysis by ICP
• Scale-forming minerals, improper coolant mixtures, and water quality indicators through Hardness, Chlorides, Sulfates, and Conductivity testing

Regular coolant testing ensures the cooling system can handle sudden load demands and temperature spikes when generators are required to run continuously.

Turning Fluid Data into Reliability

The value of fluid analysis lies not just in testing, but in using results to make smarter maintenance decisions. Trending oil, fuel, and coolant data together provides a comprehensive view of generator health and allows teams to prioritize actions based on condition rather than assumptions.

If you’re already trending fluid data on your primary assets, there’s no reason your backup generators should be flying blind.

For industrial facilities that already have strong lubrication programs in place, extending fluid analysis to backup generators is a natural and necessary step in maintenance planning.

Reliability Isn’t Optional

Backup generators may not run every day, but when they do, failure is not an option. Fluid analysis provides the earliest warning of developing issues and ensures these critical assets are ready when the unexpected occurs.

If your lubrication program protects the equipment that drives production, it should also protect the equipment that keeps everything running when production and safety are on the line.

Maintenance teams are entering a new era, one where data-driven insights enable automation and transform how equipment health is monitored and maintained. For years, the industry has been moving from preventive maintenance to predictive maintenance, but what’s next? It’s predictive reliability.

For lubrication and condition monitoring programs, this means harnessing connected data and smarter systems to make faster, more accurate decisions that predict problems before they impact uptime.

Setting the Foundation

To move toward actually predicting maintenance, the foundation and the data must be strong.

Condition monitoring relies on continuous streams of information from oil analysis, vibration sensors, thermography, and telematics. However, these data sets are often siloed, inconsistent, or manually reported, which significantly limits their usefulness. Data standardization is key. Standardized data formats, consistent naming conventions, and unified reporting structures enable automated systems and machine learning models to analyze, interpret, compare, and act on information.

Without reliable data, even the most advanced AI platform can’t identify meaningful trends or correlations. Prioritizing standardized data processes ensures that every data point can be confidently integrated into reliability systems.

For POLARIS Laboratories®, data standardization comes into play with customers’ database of equipment, OEM, components, assets, lubricant manufacturers, and those of the like. It’s imperative that this data be kept accurate, up to date, and as complete as possible.

Cloud-Based Reliability Systems

Cloud technology has accelerated this transformation by centralizing condition monitoring data. Through cloud-based platforms powered by API connections, maintenance and reliability managers can securely access results, trends, and recommendations in real time – from anywhere in the world.

For example, POLARIS Laboratories’ API integration, HORIZON® Connect, automatically feeds oil analysis results into a customer’s Computerized Maintenance Management System (CMMS) or Enterprise Resource Planning (ERP) system. This eliminates the need for manual data entry, reduces delays, and creates a single source of truth for decision-making. Cloud systems also support continuous learning; as more data is analyzed, AI-powered models can refine predictions and improve reliability.

AI and Condition Monitoring

Integrating artificial intelligence into condition monitoring practices can enhance what traditional analysis can achieve. Instead of reviewing static data points, AI algorithms evaluate trends over time and across equipment fleets, identifying subtle anomalies that might signal early signs of wear or contamination.

For example, AI can detect minor deviations in lubricant properties, such as gradual increases in oxidation or shifts in base number, that precede measurable wear. When integrated with other data streams, such as vibration and load, these patterns can pinpoint root causes of failure before they escalate. Rather than waiting for sensor alarms, maintenance teams can receive predictive insights that guide them to act sooner.

This is especially valuable in lubrication analysis, where AI models can compare millions of test results across different equipment types, environments, applications, and formulations. The result is a system that continuously learns and improves its ability to predict issues and recommend maintenance actions.

Feedback Loops and Continuous Improvement

AI and Machine Learning technologies thrive on feedback loops. In a condition monitoring program, every maintenance action (such as replacing a bearing or adjusting oil-drain intervals) generates data that feeds back into the condition monitoring system.

With an established API connection between oil analysis and maintenance systems, this also provides feedback to the laboratory, which can, in turn, improve analysis of future samples.

Setting up this feedback loop can help assess the effectiveness of those actions and adjust future predictions accordingly. Over time, the system becomes increasingly accurate and capable of recommending optimal interventions with minimal human oversight.

For lubrication management, this feedback cycle ensures that maintenance strategies evolve in sync with real-world equipment performance. The result is a more adaptive, efficient maintenance process that maximizes asset health and minimizes waste.

Clearing the Path Forward

As reliability teams prepare for the next generation of condition monitoring, the integration of AI, cloud-based platforms, and strict data standardization will define the leaders in uptime, safety, and operational efficiency. The future of reliability is intelligent, connected, and powered by data.

Lubrication analysis plays a vital role in predictive and preventive maintenance for diesel engines. Among the most informative tests available are Acid Number (AN) and Base Number (BN), two complementary measurements that provide insight into oil health, additive performance, and the potential for damaging conditions inside the engine.

The true picture of oil health emerges only when acid number and base number are analyzed together.

While historically BN has been the primary focus in diesel applications, changing lubricant formulations and emissions-driven oil designs have made AN testing equally critical. Together, AN and BN monitoring support condition-based maintenance strategies, reduce unplanned downtime, and optimize oil drain intervals.

Understanding the Fundamentals of Acid Number and Base Number

Acid Number (AN) measures the amount of acidic compounds in a lubricant. Acids can form from oxidation, nitration, or sulfur byproducts of combustion, and they can be highly corrosive to internal components if left unchecked. A rising AN signal indicates degradation and potential corrosive wear.

Base Number (BN) measures the alkaline reserve in an oil or the capacity of additives (primarily detergents) to neutralize acids formed during engine operation. As the oil ages and these additives are consumed, the BN value declines.

Both parameters are critical for oil condition monitoring: BN tracks how much “protection” against acids remains, while AN indicates how much corrosive material has already accumulated, and is the preferred test due to its ability to measure at lower levels, more on this later in the article.

The Role of Acid Number and Base Number in Diesel Engine Performance

In diesel applications, the balance between AN and BN provides a powerful indicator of lubricant condition. A healthy oil will show a gradually decreasing BN alongside a relatively stable, slowly increasing AN. When BN drops too low, acids are left unneutralized; when AN rises too high, corrosive attack accelerates.

Modern low-ash diesel oils have changed the rules – tracking both acid and base numbers is now essential for accuracy.

The challenge in today’s engines is that newer low-SAPS (sulfated ash, phosphorus, sulfur) formulations (introduced to prevent plugged diesel particulate filters (DPFs) and EGR failures) start with lower BN values and of`ten deplete more slowly. Some products are designed for emissions compliance and reduced ash formation due to low starting base numbers. As a result, relying solely on BN alone can be misleading.

In these cases, monitoring AN is vital. Even while BN remains relatively stable, AN can increase due to oxidation, fuel dilution, or coolant leaks. This dual tracking is why an increasing number of operators in Europe and globally now perform both AN and BN testing on diesel engine oil samples.

Impact on Oil Drain Decisions

One of the most practical applications of AN and BN analysis is in determining oil drain intervals. Traditional time- or mileage-based drain schedules often result in premature oil changes (waste) or delayed changes (risk of damage). Condition-based monitoring, by contrast, uses AN and BN data to identify the oil’s true remaining useful life.

AN does not increase linearly. Instead, it follows a curve: a slow, gradual rise at first, followed by a sharp increase once antioxidants are depleted. This inflection point represents the end of the oil’s life, when oxidation accelerates and corrosive wear risk rises rapidly. Effective condition-based maintenance requires identifying this inflection point and scheduling oil changes 10–20% before the oil reaches it.

By trending BN depletion alongside AN increase, maintenance teams can strike the right balance and extend drains safely while avoiding the steep escalation of wear and damage.

Standard Test Methods for Measuring Acid Number and Base Number

Several ASTM methods are commonly used for AN and BN measurement:

• ASTM D2896 (BN) – Uses a potentiometric titration with perchloric acid; highly sensitive but can give elevated values in used oils. (This test is designed for new oil only and should not be used for used oil, as the acid used in the titration will react with wear metals in used oils)
• ASTM D4739 (BN) – Uses hydrochloric acid; considered more representative of remaining alkalinity in used oils
• ASTM D664 (AN) – Potentiometric titration with KOH, used to determine acidic constituents in petroleum products
• All test methods report mg KOH/g

The choice of method depends on oil formulation, application, and whether the sample is new or in service. Many labs report both D2896 and D4739 for BN to give operators a complete picture. However, D2896 is not recommended as it is not a suitable method for new oils; most labs in Europe do not perform D4739 and use a modified method (different solvent) for D2896.

As modern diesel oils begin with lower base numbers, traditional test methods lose precision – making careful method selection critical.

BN was designed for fluids with a starting BN of ~ 12 mg KOH/g. Now they have a starting value of about 6 mg KOH/g. Neither method for measuring BN is accurate at lower levels.

On the other hand, AN was designed for lower levels (>4 mg KOH/g) and gives a better discrimination of the new fluids as they age. AN is a titration with potassium hydroxide (KOH). The KOH reacts mainly with carboxylic acids.

Carboxylic acids are degradation products caused by the oxidation of lubricating oil and additives. Thus, AN, in conjunction with FTIR (Fourier-transform Infrared) oxidation, gives an excellent definition of the oxidative state of a lubricating fluid.

Engine Damage Risks from Imbalanced Acid and Base Numbers

If AN and BN trends are ignored, several damaging conditions can occur inside a diesel engine:

• Corrosion of bearings and liners from acidic byproducts attacking metal surfaces
• Ring and cylinder wear from both acidic attack and ash formation when BN is insufficient
• Accelerated wear and deposits from oxidation products, sludge, and varnish as AN spikes
• Reduced reliability and costly downtime due to preventable mechanical failures

Finding the Critical Balance

As diesel engine oils evolve to meet emissions and performance requirements, maintenance practices must adapt. Relying on BN alone is no longer sufficient, particularly with low-SAPS, ultra-low-ash formulations. By monitoring both AN and BN, operators can accurately track oil condition, optimize drain intervals, and prevent corrosive wear.

Fluid analysis isn’t just about data; it’s about actionable insight. The balance between AN and BN is one of the most powerful tools in the maintenance toolkit, ensuring engines operate efficiently, safely, and for the long haul.

If your maintenance strategy includes getting more life out of your lubricants while ensuring equipment reliability, then optimizing, not merely extending, your oil drain intervals should be your focus.

The term “optimize“ is preferred over “extend“ when discussing drain intervals. While it may be possible to extend drain intervals, doing so without proper insights and data can compromise lubricant health and equipment performance and shorten equipment life.

Define Your Objective

To safely optimize your oil drains and get more out of the lubricants, start by defining what success looks like whether it’s increasing runtime hours, mileage, or reducing lubricant consumption without increasing risk.

Before changing drain intervals, rule out contamination – filtration and clean oil often determine success more than the lubricant itself.

If you’ve tried to optimize intervals in the past and efforts fell short, you may want to investigate environmental contaminants like dirt, rather than the lubricant’s performance. In this scenario, to safely optimize intervals, you will need to look at your contamination control practices. Are you using the correct filter? Is there better filtration available? Are you starting with clean oil? Before modifying drain intervals, evaluate these contamination control strategies to ensure they aren’t the limiting factor.

Use Oil Analysis to Guide Decisions

Oil analysis laboratories can help you achieve your goal of optimizing drain intervals through established Key Performance Indicators (KPI’s) measured through testing.

Results from laboratory testing can indicate the amount and levels of acid, oxidation, nitration, and the oil’s viscosity. These parameters are benchmarked against Original Equipment Manufacturer (OEM) and lubricant manufacturer guidelines. As long as they fall within acceptable limits and trending supports stability, it may be safe to extend lubricant use.

Real-World Scenarios

In one scenario, a customer in the dredging industry had a goal to optimize drains for a hydraulic power unit. Oil analysis flagged results for Acid Number at the lowest severity, 1 (Figure 1). After a few trending samples of low-severity results, the laboratory confirmed the customer was able to extend the drain interval by 500 additional hours.

Figure 1

On the other hand, oil analysis can indicate when it is not safe to extend drains, too. In this example, a mining customer received a sample report where both Base Number and Oxidation were flagged high on the severity scale (Figure 2) and outside of the acceptable limits; therefore, it is not safe or recommended to continue to use the lubricant.

Lean on Your Laboratory

All in all, it is possible to optimize lubricant drain intervals to get more use out of the lubricants on hand. Work closely with your oil analysis laboratory; they can interpret results, monitor trends, and help set safe, data-driven optimization strategies. One-off test results are useful, but trend data over time is essential to optimize drain intervals without risk confidently.

Optimizing lubricant drain intervals can reduce costs, extend oil life, and improve reliability. However, success depends on careful planning and data-based decision-making through oil analysis. Partnering with your laboratory experts ensures changes are made with reliability in mind.

Degradation of the lubricant circulating through your system can impact equipment performance, reliability, and lifespan. When an oil degrades, it loses its ability to properly lubricate, meaning friction increases – accelerating wear and tear on the components. This wear and tear in the metals leads to the failure of the equipment’s bearings, gears, and other moving parts.

Degraded oil becomes more and more susceptible to contamination of dirt, soot, fuel, and water and requires more frequent changes – increasing costs and downtime. Going undetected can cause severe failures and shut down operations quickly.

What Causes Oil to Degrade?

Oxidation and other contaminants can cause the formation of acidic degradation compounds (carboxylic acids, ketones, and esters) that corrode metal surfaces, leading to pitting and the damage of critical components. In addition, nitration (common in high-temperature operating environments) further accelerates the formation of nitric acid and damage to components.

Most often found in natural gas engines, nitration results from a reaction of nitrogen oxides (NOx) from the air with the oil, leading to acid formation, and most often is a result of combustion byproducts reacting with the lubricant.

Nitric acid formation can cause corrosion of engine parts as well as an increase in the oil’s viscosity, making it less effective at reducing friction. An increase in nitration compounds in high-temperature operating conditions can accelerate the breakdown of the oil, leading to a decrease in the oil’s ability to lubricate and do its job effectively.

Determining Oil Degradation

Oxidized oil loses its ability to dissipate heat, leading to increased operating temperatures and overheating. When degraded, oil becomes more susceptible to contamination, which causes the buildup of particles and clogging filters, reduces oil flow, and causes pressure drops that put strain on the system to work harder.

If you’re experiencing these issues, your oil could be degrading. To make matters worse, overheating can lead to faster oxidation of the fluid (Arrhenius Rate Rule – the rate of oxidation doubles for every 10°C).

Oxidized oil loses its ability to dissipate heat, leading to overheating and pressure drops.

Performing oil analysis regularly can identify rising oxidation and nitration levels in your engine oil, allowing you to take corrective action before significant damage occurs.

Using FTIR (ASTM E2412) to Measure Oxidation and Nitration

Fourier Transform Infra-Red Spectroscopy (FTIR) is a very powerful analytical testing technique for quantifying many parameters of used fluids for condition monitoring purposes. During testing, infrared light is passed through the oil sample, measuring which wavelengths are absorbed by the molecules, allowing identification of specific function groups and chemical compounds and properties. (Figure 1).

At POLARIS Laboratories^®, we use FTIR, ASTM E2412, which monitors contaminants like water and soot. Oxidation, nitration, and sulfation of base stocks are observed as evidence of degradation. The objective of ASTM E2412 is to diagnose the operational condition of the machine based on fault conditions observed in the oil.

If you are not performing FTIR analysis, you really should. It is a low-cost, simple test that sheds a lot of “light” on the condition of the fluid that cannot be done easily with other tests.

Oxidation testing performed by FTIR measures the breakdown of a lubricant due to age and operating conditions and is reported in abs/cm (absorbance units per centimeter). By observing specific absorption, FTIR testing detects the presence of carbonyl groups (C=O), such as ketones, esters, and carboxylic acids, that result from oxidation in the oil.

Nitration testing is also performed using FTIR (ASTM E2412 method), which indicates the presence of nitric acid, which speeds up oxidation. Nitrates exhibit peaks in the infrared spectrum, allowing FTIR to identify their presence in the oil.

Too much disparity between oxidation and nitration can point to air-to-fuel ratio problems.

Too much disparity between oxidation and nitration can point to air-to-fuel ratio problems. As oxidation and nitration increase, so can acid number and viscosity, while base number can begin to decrease.

In the results example here (Figure 2), high levels of oxidation and nitration reported on this sample can be correlated to oil degradation, resulting in high levels of wear metals and concerns related to the oil’s viscosity. Maintenance actions to diagnose further and address the root cause are recommended in the comments.

In this graph (Figure 3) of FTIR results, you can see the increases in oxidation and nitration results indicated by the FTIR testing compared to the new lubricant values.

Oxidation/Nitration Results Reported

When analyzing and reporting on the test results, the starting values of the new lubricant (product and grade) are considered. It’s good to note that the starting values of conventional lubricants will differ from synthetic. Customers can send in a baseline or new lube reference sample, which will be included in reports for reference and trending history comparisons. When the data analysts review test results, they look for deviations from the baseline lubricant values.

Based on the results, maintenance actions are recommended to address the root cause of lubricant oxidation and nitration.

Importance of Oxidation/Nitration Testing

POLARIS Laboratories^® recommends oxidation/nitration for industrial and mobile test packages as it’s imperative to protect equipment that performs under high temperatures or combustion environments and prolongs machine life.

Detecting wear-causing oil degradation early can avoid unplanned failures and downtime.

This includes industrial machinery like gasoline, diesel, natural gas engines, turbine engines in power plants, gearboxes, transmissions, high-pressure hydraulic systems, and reciprocating compressors. Detecting wear-causing oil degradation due to oxidation/nitration early can avoid unplanned failures and keep operations running without interruption.

Contamination within lubricants circulating through equipment can range from air, water, or, the most damaging, particles. The most common cause of equipment failure is particle contamination in the lubricant, and, specifically, 80% of hydraulic system failures can be traced back to contamination caused by particles. Particles can enter a system in various ways and cause a wide range of issues.

The Cost of Contamination: Why Particles Damage Machinery

Particles found within the lubricant could be dirt, metal, sand, soot, and rust. These particles can damage the machine, particularly hydraulic equipment, but components like compressors, turbines, robotics, gear systems, and bearings can also experience damage.

These small, hard particles can scratch the machine’s surfaces and, as a result, cause a cascading increase in wear—this compounding damage leads to major, costly failures.

These hard particles can also cause other concerns, such as lubricant degradation, clogged filters, jammed valves, surface erosion, overheating, and a loss of system efficiency. With such a wide range of issues, it’s no wonder particles contribute to most equipment failures.

Testing for Particle Contamination

Standard oil analysis tests such as Elemental Analysis by Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) can quantify the concentration of contamination. However, it has a major limitation. ICP-OES can only fully analyze a particle under approximately 10 µm in diameter.

Further, it gives no indication of the particle’s morphology. Additional test methods can investigate the size and shape of the particles. Discovering this additional information can lead maintenance teams to identify the source of the contamination and assess the damage that has occurred to the component.

The test method recommended for the most reliable and accurate particle size distribution measurement is Automatic Particle Counting using ASTM D7647. This method uses two solvents (Toluene and Propan-2-ol) to dissolve soft, non-destructive particles, like oil additives, varnish, or water, so they are not counted along with the hard particles.

You only need to identify the hard particles like dirt and metal that will cause the formation of more particles through the impact on the surfaces of the machinery. The instrument used to perform the test uses laser light obscuration to detect and count particles over a range of sizes, collating the counts into size categories:≥ 4µm, ≥ 6 µm, ≥ 10 µm, ≥ 14 µm, ≥ 21 µm, ≥ 38 µm, ≥ 70 µm and ≥ 100 µm.

The number of each size category is used to determine the level of contamination in the oil. Results are presented as the number of particles per milliliter at several micron sizes, and findings are reported using ISO 4406, or ISO Code.

Understanding Particle Sizes and Their Impact on Reliability

Lower ISO code numbers are more desirable overall, potentially having less impact on machinery, though size and filter rating may mitigate that. All things being equal, larger particles have a greater chance of spanning the oil film diameter between two metal surfaces and could damage one or both. As the surface is damaged, more particles are created, resulting in a snowball effect that leads to potential critical failures in the system.

However, the sample could have been collected after the source of the particles and before they were collected in the fluid filter. In this case, the smaller numbers could be more important because they cause pitting or sliding wear at other points in the system.

Filtering out small particles poses its own problem, as they are more difficult to capture than larger particles and require specialized filters to collect. Particle Count Testing can help indicate the need for additional filtration or suggest portable filtration, as seen in the following laboratory examples.

Particle Count Testing to Increase System Cleanliness

In the following example, particle count testing was performed on a guide bearing using a very high ISO fluid (such as ISO 680 with a similar consistency to light corn syrup) in an air heater for a power generation unit. The particle count results came back extremely high, resulting in an overall report severity of 4:

Repeat severities on this sample report can indicate an action was taken, but it was not sufficient to address the source of particle contamination in the system.

High-viscosity lubricants tend to result in higher ISO particle counts due to the fluid’s high internal friction. This friction creates greater resistance to flow, trapping particles within the fluid and preventing them from moving quickly or settling out. After reviewing the high particle count results, the data analysis team recommended actions, suggesting the use of portable filtration to improve system cleanliness.

In the next example below, testing was performed on a conveyor carrier bearing in a plant/industrial setting. Particle count testing provided extremely high results, indicating potential bearing/bushing wear that could increase due to dirty fluid. The analyst’s maintenance recommendations suggested performing vibration analysis to confirm the problem and inspect the unit for bushing wear.

Advanced Testing Beyond Particle Counts: Morphology and Analysis

Performing Particle Count testing will provide information on the different sizes of particles and their distribution in the oil but will not determine their morphology. To determine specific, exact types of hard particles present within the lubricant, tests like Filter Debris Analysis, Micropatch, and Analytical Ferrography are recommended. These tests include images of the particles, size, and type indicated with a severity provided by the use of microscopic techniques.

How to Measure System Cleanliness for Maximum Reliability

Particle Count is one of the best available tools for measuring system cleanliness. This test is suitable for most turbine, compressor, hydraulic, transmission, and gear oil fluids and systems. Evaluating the use case, objectives, and system type is key to determining whether particle counting and other tests may provide the most valuable data. Particle Count is crucial to maintaining the performance and longevity of sensitive components with small clearances.

Traditional fluid analysis relies on pre-set flagging limits to evaluate the severity of a sample. These limits, refined over time through statistical analysis, provide a baseline for assessing whether test results indicate any maintenance needs.

If a sample falls within acceptable limits, it’s a green light to continue operation. If not, the accompanying fluid analysis report offers insights and actionable recommendations to help pinpoint issues.

 At POLARIS Laboratories®, we’ve accumulated decades of data from millions of tested samples, building a massive database that includes lubricant type, grade, machine hours, filter type, equipment and component details, and more.

Using 25 years of historical data, we’ve developed flagging limits based on customer submissions and Original Equipment Manufacturers (OEM) guidelines. These robust thresholds provide reliable guidance for equipment maintenance.

 Imagine a system that uses this wealth of data to forecast how equipment health will progress and change over time, moving customers from reactive to proactive maintenance.

 But what if we could take this a step further? Imagine a system that uses this wealth of data to evaluate the current state of equipment health and forecast how it will progress and change over time to provide predictive maintenance far in advance.

The system is programmed to learn and improve itself over time as it processes more information. This means moving fluid analysis customers from reactive to proactive maintenance, from diagnostic analysis to predictive analysis.

 As data science technologies advance POLARIS Laboratories® is at the forefront reshaping the future of fluid analysis using Artificial Intelligence (AI) and Machine Learning (ML). Our team has just launched a new, robust, and powerful analysis engine that calculates and identifies indicators to generate a readable technical statement, resulting in a streamlined approach to understanding and acting on the information.

 By leveraging our vast data sets, we can customize and fine-tune flagging limits and continually adapt as new data from equipment and lubricants becomes available. This evolving analysis provides even more precise recommendations, creating a dynamic feedback loop where the system “learns” from patterns in component, equipment, and lubricant data along with historical results.

This engine represents the advanced capabilities of fluid analysis, combining data analytics with technology to drive reliability and improve maintenance recommendations, and it’s here. Introducing: Aurora.

 Aurora is rolling out across our laboratory network, continuously learning in the background to refine its predictions.

Customers won’t see changes on their reports right away, but rest assured, the system is advancing in the background to enhance future recommendations.

 As we continue to develop, improve, and perfect this technology, we’re trailblazing the fluid analysis industry in an effort to provide the most accurate, reliable, and timely results for customers so they can save more of their equipment.

As temperatures drop in the winter, the impact on equipment performance can be substantial. In extreme cases, such as remote mining operations in Alaska, where temperatures plunge to dangerous lows, equipment can experience immediate oil thickening within minutes of shutdown.

Due to these extreme conditions, continuous operation becomes necessary, with engines needing to run non-stop, even during refueling and oil changes.

While your operations may not face such extreme conditions, cold weather can still affect mobile equipment exposed to the environment or fixed equipment in non-climate-controlled settings. The following insights can help you mitigate potential cold weather challenges and keep your operations running smoothly.

The Importance of Routine Fluid Analysis

Routine fluid analysis is essential for maintaining equipment and optimizing uptime. However, additional tests can safeguard against cold-weather complications in preparation for winter. Below are key tests to consider incorporating into your maintenance program as temperatures drop.

Viscosity Index Testing (ASTM D2270)

Oil thickens (viscosity increases) when exposed to cold temperatures, making it harder for equipment to pump oil through filters and passages during start-up. This can lead to oil starvation and increased wear on critical components. In severe cases, the oil may become so thick that equipment fails to operate.

The Viscosity Index test measures the oil’s stability across varying temperatures, ensuring that it remains functional during colder months. One of the things to look for with this test is a high viscosity index, which indicates better resistance to temperature fluctuations.

Water by Karl Fischer (ASTM D6304C)

Water contamination can freeze in cold conditions, leading to burst pipes, clogged passages, and potential equipment failure. Water by Karl Fischer testing is the most accurate method for detecting water contamination, identifying levels as low as 10 parts per million (ppm).

Freeze Point (mod. ASTM D3321)

Coolant, commonly referred to as antifreeze, plays a crucial role in protecting your equipment from freezing temperatures. Freeze Point testing determines whether your coolant can withstand low temperatures and whether adjustments are needed to maintain optimal protection.

Cloud Point Test (ASTM D7689)

As a petroleum-derived product, diesel fuel faces challenges similar to those of lubricants in cold weather. Waxy paraffinic crystals can form at low temperatures, leading to clogged fuel filters, fuel starvation, and potential equipment shutdown.

Cloud Point testing measures the lowest temperature at which these crystals begin to form. This test lets you take preventative measures, such as switching to a more winter-appropriate diesel fuel type (e.g., #1 diesel instead of #2) or adding anti-gelling agents.

In short, by implementing these cold weather preparation strategies, your equipment will continue to perform optimally, minimizing downtime and avoiding costly repairs during winter operations. Hopefully, these tips will encourage you to contact your fluids analysis provider and plan a proactive approach to your winter maintenance.

With a little forethought and a few extra tests, you can be sure you and your equipment are both ready to handle the lower temperatures!

Grease has been used since ancient times, and new technologies and equipment design require us to improve our understanding and perception of it. These advancements enable those working with grease to recognize better its impact, effective properties, and the proper methods for testing grease samples, shedding new light on its applications and benefits.

The Importance of Monitoring Grease

Through these continuous technological advancements, the formulations of grease have significantly expanded, making it a crucial component to monitor when maintaining and enhancing the performance of modern equipment across various industries.

Greased equipment in mobile and industrial industries is getting more scrutinized as predictive and proactive maintenance are becoming the standard. To this end, greased components need to be viewed as crucial as any lubrication program, and any downtime resulting from failed greased components should be thoroughly investigated to determine the cause of the failure. Was it environmental conditions, over or under lubrication, incorrect grease, or exceeding the equipment design capacity?

The Benefits of Grease Analysis

By testing grease components, analyzing and recognizing wear trends, and determining lubricant properties, we can increase the capacity to react to potential equipment failures. These failures can lead to a reduction in production and compromised safety. While many industry sectors view greased components as replaceable or run-to-failure parts, testing these components allows us to become more informed.

Technological advancements now allow for precise determination of wear concentration and lubricant conditions. With routine testing, we can identify and provide the information to better schedule lubrication intervals, plan equipment repair, and determine the best time to replace components, thus increasing uptime and productivity. With this knowledge, industries can effectively conduct Root Cause Analysis (RCA) to prevent future failures.

Today, failure can be prevented with as little as 2 grams of grease. ATSM D7718-11 Standard Practice for Obtaining In-Service Samples of Lubricating Grease was created to make the process more accessible. This standard describes the method to obtain in-service grease samples that can be tested for trending purposes.

The basic tests, which include Ferrous Density, FTIR, color, and water, are used as a screening tool.

In addition, more complete evaluations of grease include testing for Total Water, Remaining Useful Life (RUL) Antioxidants Levels, Microbial, Elemental Metals, and Extrusion Values. These tests’ key component is for each to be compared to a known provided baseline sample.

The Wear that Grease Testing Identifies

Data obtained from grease evaluations can assist in identifying not only the characteristics of the grease itself but also the quality of the base oil it provides for lubrication.

Effective grease should lead to minimal wear metals. Elevated levels of antioxidants with extended Remaining Useful Life (RUL) across several samples may indicate a need to reassess current relubrication schedules. Proactive monitoring of these factors can reduce lubrication expenses and ensure consistent reliability.

On the other hand, a high wear metal concentration could be a sign of an increase in lubrication, as this would lead to the base oil not providing the correct fluid film for protection.

The National Lubricating Grease Institute (NLGI) grade measures the hardness of grease in relation to pumpability and soap structure, and the ISO Viscosity grade provides the proper fluid lubricant film protection. In addition, tools such as the Analytical Ferrogram give insight into the type of wear being generated and are a great aid in the RCA process.

For example, when analyzing a recent grease sample with severe levels of Ferrous Debris for a crane wheel bearing, it was recommended that an analytical ferrogram be performed. The amount and type of wear observed indicated insufficient lubrication was occurring, yet regreasing was being conducted at regular intervals.

There was no indication that the bearing was in failure mode. However, an abundance of fresh wear was generated. And, since the lubrication regime was boundary, the base oil viscosity plays an important role. Usually, with a slow-moving crane bearing, a base oil Viscosity of ISO 320 or 460 is standard.

This grease being tested had a base oil Viscosity of ISO 220, which caused an increase in wear as the lubricant film was insufficient for the heavy loading occurring. A recommendation was made to contact the crane manufacturer for further guidance on the proper grease for that operating condition.

Looking through this new lens of analyzing grease, adding regular testing on grease components can help reduce unnecessary downtime and increase overall safety.