Tagged: oil tests

Oil Properties / Reliability / Used Oil Analysis

From Measurement to Action

Start measuring the air in your system. The most useful air-in-oil measurement is not the one that produces the largest number of parameters. It is the one that supports a better engineering process.

  • Define a representative baseline.
  • Detect a meaningful deviation.
  • Interpret it together with fluid, component, and operating context.
  • Investigate the most plausible mechanism.
  • Verify whether the intervention changed the measured behavior.

Many practitioners only view air as an issue when they see foam. By this time, it is too late and damage has already occurred to the system. Even small bubbles can have system consequences, as shown in the diagram below.

figure 6
Figure 6: System-level consequences which can be detected by the presence of small bubbles through deepfluid’s technology

Many operators are not aware of the impacts of air-in-oil and quite often, it is labelled as something else. However, it usually shows up as a foam problem, unexpected NVH, control instability, temperature problem, cavitation problem, pump problem or an oil problem. The key is to monitor these effects in different settings.

Starting with studying air release, dispersion and formulation effects under controlled conditions in the lab. Moving to the testing phase where bubble behaviour is related to operating conditions, design changes and system response. Then finally to the field where changes can be tracked over time to support root-cause analysis and confirm any improvements.

This is the benefit of using the deepfluid technology as it can capture data from the various phases to bring about actionable insights to improve the reliability of operating systems.

Find out more in the full article, "From Lab Insight to Field Action: How Air-in-Oil Diagnostics can support better Troubleshooting" featured in Precision Lubrication Magazine by Sanya Mathura, CEO & Founder of Strategic Reliability Solutions Ltd, , 

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August 18, 2026
Oil Properties / Reliability / Used Oil Analysis

The 360 Approach – One Shared Data Language Across the Lubrication Value Chain

At Deepfluid, they have adopted a 360 approach where they can assist all the stakeholders involved in the lubricant industry as it relates to the oil being in the equipment. It connects formulation development, laboratory testing, component testing, system validation, field operation, maintenance, troubleshooting, and verification of corrective actions.

With the 360 approach, various stakeholders can be involved to ensure that the lubricant is fully assessed in different situations, from the testing and development of the lubricant to its actual application in the component then finally to the end user by ensuring they get the results they need.

An additive supplier may investigate formulation effects. A lubricant manufacturer may compare air-release and foam behavior. A filter or seal supplier may study aeration or air ingress. An OEM may correlate bubble behavior with efficiency, thermal management, or NVH. An operator may investigate an abnormal field deviation. An external oil laboratory or research institution may provide controlled reference analysis.

The questions differ, but the underlying air-in-oil metrics can remain comparable.

Not one product for every stakeholder, but one measurement logic that allows different stakeholders to work on the same fluid-system question from different positions in the value chain.

The 360 approach ensures that all aspects are taken into consideration for the oil, from the lab testing to the field development, with all the stakeholders involved. This guarantees that the final product is reliable and the user should have a valuable experience.

360
deepfluid's 360 approach

Find out more in the full article, "From Lab Insight to Field Action: How Air-in-Oil Diagnostics can support better Troubleshooting" featured in Precision Lubrication Magazine by Sanya Mathura, CEO & Founder of Strategic Reliability Solutions Ltd, , 

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August 18, 2026
Oil Properties / Reliability / Used Oil Analysis

Case Study – From Abnormal Air-in-Oil Data to a Targeted Seal Investigation

Deepfluid’s direct measurement system can be used not only to analyze the interaction between oil and air during operation but also to monitor the overall system behavior and the reliability of the installed components.

The leak-tightness of hydraulic circuits is essential and critical for the safe operation of these systems. Leaks can allow air and particles to be drawn into the system under negative pressure and oil to be forced out of the system under positive pressure. The presence of air significantly alters operating behavior by changing viscosity, density, fluid level, and lubricating film thickness. These factors can lead to damage such as pitting, scuffing, and micro-dieseling.

If an operator or service technician frequently inspects an application’s oil tank—either directly or through large sight glasses—high air content can be detected by significant cloudiness in the oil.

However, if the application’s oil tank is located in a hard-to-reach position, operates autonomously, or is only accessed during shutdown, such extreme conditions are detected very late, in the laboratory—if at all—before costly damage occurs. This is the case with the operation of wind turbines. Although speed, torque, temperature, particle content, and potential oil leaks are detected, suction-side air ingress, for example, cannot be detected.

figure 5A
Figure 5A. Recurring Air-in-Oil Deviation During Gearbox Operation. A synchronized view of air content, pressure context, and bubble population illustrates how recurring events can support a targeted investigation of possible suction-side or sealing-related air ingress.

In the case study presented, a defective shaft seal was detected through direct measurement on a supply pump for the injection lubrication system of a wind turbine, based on an iteratively and periodically occurring very high air content and loud noise. A minor issue that can have serious financial consequences.

Risks posed by excessive air content and their costs, using a 2.5 MW turbine as an example:

  • Higher operating temperature, which requires additional cooling
  • Increased cooling capacity (between 4.9 kW and 9.4 kW) due to reduced thermal conductivity (0.14 W/(mK) → 0.125 W/(mK)), costing between 7k€ and 10k€ per year
  • Change in friction conditions in conjunction with increased cooling capacity: 43k€–82k€ per year
  • Risk of faster oil aging due to accelerated oil oxidation and thermal oil oxidation: 1 additional oil change (24k€–60k€)
  • Total mechanical failure of the main gearbox renders the entire system uneconomical.

In this component, there was persistently high air content which we are able to identify and link to abnormal ingress of air into the lubrication system. However, we also saw the pressure drop during pump operation. This was an indicator for suction-side or sealing-related air ingress. We also noticed a dense bubble population which indicates critical oil-air dispersion under operating conditions. There was a deviation from a similar gearbox indicating that this was a system-specific malfunction rather than normal behaviour.

If these were not identified at this early stage, the equipment would run the risk of micro-dieseling, cavitation, oxidation and temperature increase. This would lead to mechanical damage in the gearbox or oil supply components, eventually leading to reduced lubrication reliability and accelerated wear.

Find out more in the full article, "From Lab Insight to Field Action: How Air-in-Oil Diagnostics can support better Troubleshooting" featured in Precision Lubrication Magazine by Sanya Mathura, CEO & Founder of Strategic Reliability Solutions Ltd, , 

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August 18, 2026
Oil Properties / Reliability / Used Oil Analysis

One Portfolio for Controlled and Dynamic Evidence

The Deepfluid portfolio applies this methodology through three connected solutions.

 

The Air-in-One Lab Analyzer establishes controlled references.

The Optical Inline Sensor captures dynamic behavior.

visiQ connects both into a comparable engineering process.

 

figure 4
Figure 4. One Measurement Logic from Lab to Field. From Lab to Field does not mean that laboratory, test-rig, and operating conditions are identical. It means that the same Air Intake, Retention, and Release logic—and the same bubble-level metrics—can be applied across different environments and compared within one engineering workflow.

Deepfluid Air-in-One Lab Analyzer

The Deepfluid Air-in-One Lab Analyzer combines air release, foam, and time-resolved bubble behavior within one integrated and automated workflow.

Defined aeration, fluid handling, automated temperature conditioning, optical measurement, foam observation, data transfer, and cleaning can be connected into repeatable test sequences. A fully automated AIR test can capture the complete progression from baseline through Air Intake and Retention to Air Release.

Throughout this sequence, the system measures the physical development of the oil-air dispersion rather than only recording a final release time or foam volume, including Air Content, Bubble Size and Bubble Size Distribution, Bubble Count and Bubble Population, Oil-Air Interfacial Area, and time-resolved Intake, Retention, and Release behavior.

The Air-in-One Lab Analyzer also supports automated test campaigns. Lubricant and additive developers can compare fluid candidates, formulation variants, additive packages, antifoam concentrations, temperature profiles, or aeration durations using the same test logic and evaluation structure.

This makes it possible to investigate not only whether a fluid meets a defined air-release or foam specification, but also why different formulations produce different Air Intake, Retention, Release, and foam responses. Engineers can examine how the bubble population develops before visible foam forms, how much air remains dispersed after aeration stops, and how temperature or formulation changes influence the subsequent recovery.

The approach is not intended to replace standardized ISO or ASTM air-release or foam tests. These methods remain essential for reproducible specification checks and lubricant qualification. The Air-in-One Lab Analyzer adds a complementary, process-aligned R&D perspective that goes beyond a single pass/fail value.

It enables lubricant developers, test engineers, and technical decision-makers to investigate the mechanisms behind Air-in-Oil behavior, compare formulations under application-related conditions, and develop a more complete understanding of Air-in-Oil Contamination before it becomes a field troubleshooting issue.

Standardized tests confirm whether a requirement is met. The AIR workflow helps engineers understand how the result develops—and how that behavior translates from Lab to Field. It is not a replacement for the standardized tests but rather a tool to understand Air-in-Oil Contamination from an R&D perspective.

Deepfluid Optical Inline Sensor

The Deepfluid Optical Inline Sensor transfers the AIR Framework into dynamic test and operating environments.

Instead of recording only a single air-content value, it can capture complete Intake, Retention, and Release behavior over defined time windows. Engineers can observe when a bubble population begins to form, how rapidly it develops, which size classes dominate, how much air remains dispersed after the operating state changes, and how quickly the system returns toward its baseline.

This adds a time-resolved view of transient events. A load change, speed ramp, thermal transition, pressure drop, component-switching event, or start-stop cycle can be evaluated as a complete AIR sequence rather than as an isolated data point.

The sensor can be used in representative inline or bypass configurations, subject to application-specific review. All device configurations have also been developed for demanding high-pressure applications above 150 bar.

When bubble-level data are combined with temperature, pressure, speed, load, flow, efficiency, vibration, or noise, the measurement supports direct comparison between fluids, components, machine variants, and operating conditions. It can also be used to verify whether a design change or corrective action altered the measured Air Intake, Retention, or Release behavior.

The sensor does not automatically diagnose a root cause. It records how the dispersed air phase responds to a defined event, operating state, or intervention and provides evidence for a more focused engineering assessment.

visiQ by Deepfluid

visiQ by Deepfluid provides the common comparison and reporting layer.

Devices and measurement sessions can be assigned to projects, enabling structured data management across development programs, test campaigns, and field investigations. Evidence Snapshots remain linked to the corresponding measurement points and operating context.

The platform supports machine-to-machine, system-to-system, component-to-component, fluid and formulation, and before-and-after comparisons.

For example, the same machine and lubricant can be evaluated under different ambient conditions or load cycles. Conversely, different components can be compared under the same operating profile, or similar machines can be benchmarked across locations. This helps engineering teams distinguish more systematically between fluid-related, component-related, system-related, and environment-related differences.

visiQ also supports automated reporting, reducing the effort required to compile recurring test results, before-and-after comparisons, and structured project summaries.

Find out more in the full article, "From Lab Insight to Field Action: How Air-in-Oil Diagnostics can support better Troubleshooting" featured in Precision Lubrication Magazine by Sanya Mathura, CEO & Founder of Strategic Reliability Solutions Ltd, , 

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August 18, 2026
Oil Properties / Reliability / Used Oil Analysis

One Shared Data Language – From Lab to Field

Particularly for OEMs, it is important to be able to transition the product from the lab to the testing phase, then into the field. In the lab, they can control the operating conditions, study the air intake and release, dispersion and formulation effects. Afterwards, they can relate bubble behaviour to operating conditions, design changes and system response. Finally, they can execute in the field and track the changes over time to support any root cause analysis for the future and confirm improvements. This is a movement from controlled conditions in the lab to dynamic conditions in testing to finally real-world conditions in the field.

Typically, conventional sensors will give parameters such as a change in dielectricity, a foam tendency, some noise or vibration and an oil condition change just as a result, without knowing the root cause. However, with Deepfluid, they are able to actually make physical behaviour visible and directly explainable. The size and shape of a bubble can be seen, classified and quantified. This allows for the actual oil-air contact surface area to be determined, and this can be trended over time to establish patterns.

What Recurring Patterns Can Bubble-Level Data Reveal?

Direct optical measurement does not identify a root cause on its own. Its practical value lies in revealing repeatable physical patterns that can be compared with operating conditions, representative baselines, and similar systems.

Examples include:

  • An increasing population of small bubbles under steady load may be consistent with continuous air ingress or churning.
  • Recurring air-content spikes synchronized with pump starts, pressure drops, or speed changes may point to an event-related source of Air Intake.
  • A shift toward larger bubbles following a load or pressure transition may reflect bubble expansion, coalescence, or the beginning of Air Release.
  • A slow return to baseline after an operating event indicates that air remains retained in the fluid-system combination or is released only gradually.
  • Similar Air Content with different bubble-size distributions, bubble counts, or oil-air interfacial areas shows that the physical state of the dispersion is not necessarily the same.
  • Different AIR profiles under comparable operating conditions can help distinguish normal system behavior from a machine-, component-, or environment-specific deviation.

Before-and-after measurements add another practical dimension. By repeating the same operating cycle after a change to a seal, reservoir, component, fluid, or control strategy, engineers can verify whether the intervention altered Air Intake, Retention, or Release behavior.

These observations should be treated as investigation signals rather than automatic diagnoses. Their meaning becomes clearer when bubble-level evidence is evaluated together with pressure, temperature, load, speed, flow, vibration, noise, and a representative baseline.

Find out more in the full article, "From Lab Insight to Field Action: How Air-in-Oil Diagnostics can support better Troubleshooting" featured in Precision Lubrication Magazine by Sanya Mathura, CEO & Founder of Strategic Reliability Solutions Ltd, , 

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August 18, 2026
Oil Properties / Reliability / Used Oil Analysis

AIR as a Practical Lab-to-Field Framework

The Deepfluid AIR Framework turns insights from bubble-level evidence into three entirely new practical engineering questions and metrics:

1 Air Intake

Air Intake describes not only how quickly air enters the fluid system and under what conditions it is generated or introduced, but also how much air the oil can actually absorb over a specific period of time.

2 Air Retention

Air Retention describes how much air remains dispersed, how long it remains in the system, and how the bubble population changes.

3 Air Release

Air Release describes how quickly and completely the fluid-system combination returns toward its baseline after aeration or an operating-state change. By having the Air Intake value, Deepfluid addresses a new question that has not yet been covered by conventional air release laboratory tests: “At what initial air content by volume does my air-release measurement actually begin?”

AIR is not an abstract research model. It is a practical structure for planning tests, defining measurement windows, comparing fluids, evaluating component and design variants, analyzing operating states, and verifying corrective actions.

figure 3
Figure 3. The AIR Framework: Intake, Retention, and Release. The AIR Framework structures air-in-oil behavior as a time-resolved sequence. In controlled testing, aeration duration, temperature conditioning, measurement intervals, and recovery phases can be defined; the same logic can be applied to operating events in testing and field environments.

In the laboratory, air release no longer has to be viewed only as a single endpoint under one fixed condition. Individually defined aeration durations, automated temperature conditioning, and time-resolved optical measurement make it possible to run a fully automated AIR test.

Such a sequence can establish a bubble-level baseline before aeration, follow the bubble population during a defined Air Intake phase, quantify Air Retention after the air supply stops, and measure the Air Release curve over time. The same workflow can connect air content, bubble-size distribution, and bubble-population dynamics with subsequent foam formation and foam decay.

This makes it possible to compare different fluids, additive concentrations, temperatures, or aeration durations within structured, automated test campaigns. The laboratory therefore moves closer to application-related questions without giving up controlled and repeatable conditions.

In testing and field operation, the same AIR logic can be applied to defined operating windows. A cycle may begin at a stable baseline, follow an increase in air content during a load, speed, pressure, or temperature change, quantify how much air remains dispersed, and measure recovery afterward.

The resulting bubble-level metrics can be related to operating data such as temperature, pressure, speed, load, flow, efficiency, vibration, or noise.

The conditions are not identical across lab, testing, and field environments but the measurement logic is.

AIR turns air release from a single laboratory result into a practical understanding of the full cycle around how air enters, remains, and leaves a fluid system.

Find out more in the full article, "From Lab Insight to Field Action: How Air-in-Oil Diagnostics can support better Troubleshooting" featured in Precision Lubrication Magazine by Sanya Mathura, CEO & Founder of Strategic Reliability Solutions Ltd, , 

by
August 18, 2026
Oil Properties / Reliability / Used Oil Analysis

How Air in Oil gets Measured

Typically, oil condition monitoring is performed through standardized laboratory tests at specified intervals. A representative sample is taken on-site from the system being monitored and analyzed in the laboratory under controlled conditions. This allows for a detailed analysis of numerous parameters that reflect the condition of the oil, such as viscosity, density, and air release behaviour in accordance with DIN ISO 9120.

However, when the sample is pulled from the equipment, it must travel some distance to the lab. During this transit, the oil sample may lose some characteristics that defined the system in which it was operating. While this does not corrode the integrity of the sample, it may not define an accurate representation of system conditions.

In the laboratory, it is not possible to correlate the oil’s interaction with the system’s behavior, which is characterized by constantly changing process conditions such as pressure, temperature, flow rates and air-contents. As these process conditions change, the measurable properties of the oil also change proportionally, and these properties directly determine the efficiency and service life of both the system and the oil. Comprehensive monitoring of the system’s condition can therefore only be achieved through laboratory analysis in conjunction with field measurements.

This approach allows for direct measurement of how the oil interacts with the equipment and generates data points that were previously unthinkable. This enables operators to make predictions that can extend the service life of the oils and make plant operations more efficient or less prone to errors.

 

What Gets Measured

It is well known that, during the operation of hydraulic systems and transmissions, air is inevitably though unintentionally mixed into the oil. The air content alters the oil’s properties by creating a multiphase mixture, thereby influencing measurable operating parameters in both the short term (efficiency, NVH, temperature) and the long term (oxidation, additive depletion, oil aging).

The Deepfluid bubble profiling technology combines an intelligent vision module and an intelligent LED system. This captures real-time images of the fluid as it flows through the device. Through the use of computer vision-based image processing, each air bubble is identified, sized and classified on a continuous basis. This allows trends and patterns to be recognized and established. No on-line calibration and constant re-calibration is required for this equipment, and it can work across various types of oils with different viscosity ranges and colors or aging-states.

The Deepfluid optical approach evaluates bubbles within a defined size range of 8 to 500 micrometers and generates time-resolved information such as:

  • air content,
  • bubble-size distribution,
  • bubble count,
  • bubble-population dynamics,
  • oil-air contact surface / interfacial area, and
  • transient air events.
figure 1
Figure 1. Same Air Content. Different Bubble Behavior. Two fluid states can show the same volumetric air content while differing in bubble-size distribution, bubble count, oil-air interfacial area, and release tendency. Air content alone does not fully describe an oil-air dispersion.

Until now, measuring air content has been possible primarily through indirect analytical methods. In this approach, the conductivity of the oil, excluding air content, was referenced to the conductivity of the oil-air mixture during operation. This allows for the analysis of air content percentages under constant conditions. The biggest problem with this measurement is the change in the oil during continuous operation of the system, since water content, particle content, temperature, and additive content are constantly changing, making continuous measurement during operation impossible.

As shown above in Figure 1, the traditional method of measuring the air volume does not accurately depict what is happening in the oil. The air volume of 0.65% only measures one aspect of the oil. With the direct measurement by Deepfluid, users can get deeper insights and explore another dimension of oil condition monitoring by measuring the bubble diameters during operation and compare it with the same technology in a lab-based air-in-oil analysis. Based on this information, short term behaviour (density change, viscosity change, lubricant film thickness, Air-Intake, Air-Release-Behaviour, thermal conductivity and NVH) as well as long term response (oxidation, additive depletion, mechanical robustness, risk of pitting) can be detected and their respective influence targeted.

A key feature is the availability of so-called Evidence Snapshots. Each calculated measurement point can be linked to an optical image of the fluid at that moment. Engineers can review the underlying image, verify the detected bubble population, and relate an unusual value to the physical condition on which it is based.

This creates point-level traceability between the calculated metric and the visible evidence.

Evidence Snapshots do not replace numerical specifications for repeatability, accuracy, or measurement uncertainty. They add transparent verification and support more informed technical discussion between lubricant developers, test engineers, component specialists, and reliability teams.

figure 2
Figure 2. From Optical Evidence to Quantitative Bubble-Level Data. Direct optical measurement links calculated air-in-oil metrics to the underlying fluid image. Evidence Snapshots provide point-level traceability between air content, bubble-population data, and the recorded physical condition.

The optical approach has also been demonstrated with visually challenging fluids, including dark, aged, and soot-loaded engine oil. As with any optical method, application limits must be understood. However, Deepfluid’s bubble-level analysis is not restricted to transparent new oils.

The objective is not to replace conventional oil analysis, pressure, temperature, vibration, or standardized air-release and foam testing. It is to add direct evidence about the dispersed air phase and its dynamics.

Find out more in the full article, "From Lab Insight to Field Action: How Air-in-Oil Diagnostics can support better Troubleshooting" featured in Precision Lubrication Magazine by Sanya Mathura, CEO & Founder of Strategic Reliability Solutions Ltd, , 

by
August 18, 2026
Oil Properties / Used Oil Analysis

Interpreting the Oil Analysis Report in Practice

Now, we will actually read a report to help put all of these into practice.

Here is a sample report from Eurofins for a turbine oil. In this report, the various types of tests are classified according to wear metals, additives, and contaminants, as shown in Figure 2.

According to the report, samples have been collected over a period of time. This helps with the trending of the data, so we can spot when the values start varying from the “normal levels”. The reference values are also provided in the first column to help users determine whether these values fall within tolerance limits or not.

Figure 2: Sample Turbine Oil Analysis Report

Typically, the lab will provide some type of traffic light system where:

  • Red – indicates there may be an abnormal reading or the oil should be changed immediately, as certain values have surpassed the critical limits.
  • Amber – shows that the values are approaching the warning limits, but there is still some time to investigate and fix the problem.
  • Green – tells us that all values are within the tolerance limits and the oil is performing normally.

For this report, they also include additional tests as shown in Figure 3.

Figure 3: Additional Tests for Turbine Oils
Figure 3: Additional Tests for Turbine Oils

For turbine oils, understanding the demulsibility of the oil is important, as this is the oil’s ability to separate from water, or rather, not to form an emulsion. Excessive water in the oil can lead to rust or even a washout of the additives.

The Foam test is also administered to detect the oil’s ability to release air from the oil, ensuring that the air doesn’t get trapped. If air is trapped, it can lead to microdieseling and cavitation on the inside of the equipment.

RPVOT – Rotating Pressure Vessel Oxidation test is also performed, as it indicates the expected oxidation of the oil. MPC (Membrane Patch Colorimetry) and Ultracentrifuge detect the potential of the oil to form varnish, and the RULER® values give the actual quantity of antioxidants present.  These values are all critical for monitoring the health of the turbine oil, as it is very susceptible to oxidation and the formation of varnish.

In essence, reading the oil analysis report involves understanding what the tests are meant to measure, knowing your equipment and its operating conditions, and having a history of your equipment.  These factors all contribute to trending the data to ensure that there are no surprises with unplanned downtime due to wear or oil degradation.

References

Eurofins. (2025, September 06). Annual Turbine Analysis. Retrieved from Eurofins Testoil: https://testoil.com/services/turbine-oil-analysis/annual-turbine-analysis/

Find out more in the full article, "How to Read Oil Analysis Reports and translate Data into Reliability" featured in Reliable Magazine by Sanya Mathura, CEO & Founder of Strategic Reliability Solutions Ltd. 

by
November 15, 2025
Oil Properties / Used Oil Analysis

How to Interpret Your Oil Analysis Results

Have you ever received your bloodwork results from your doctor, only to be more confused than ever? With all the long names and numbers just sitting on the piece of paper, Google (or ChatGPT) becomes your best friend to help interpret what they mean. However, even with these tools of reason, there is usually a disclaimer that states, “Please consult your doctor for a more accurate interpretation”.

Numbers alone don’t tell the whole story – context is what makes oil analysis meaningful.

One of the reasons for constantly looping your doctor back into the mix is that they have your history, they know how your body responds to certain things, and values which may get flagged because they are outside of the limits may be waived away by your doctor because it is normal for your body based on your history and DNA.

The same applies to oil analysis. Depending on the application and operating environment, certain conditions may be met that can be interpreted as unusual. Still, if you’re familiar with your system, you will understand the reason behind the numbers.

Figure 1: DIN 515519 table showing viscosity limits
Figure 1: DIN 515519 table showing viscosity limits

Viscosity

As mentioned earlier, viscosity is the most important characteristic of a lubricant. If it is too thick for the application, this can lead to efficiency loss, increased heating, and a slowdown of the system. Essentially, a significant amount of work needs to be done on the oil to make it compatible with the application.

On the other hand, if it is too thin, then we run the risk of improper lubrication. Therefore, we increase the chances of wear occurring in the applications.

Viscosity is usually measured at either 40°C (for industrial applications) or 100°C (for engine applications). However, most labs put a ±5% tolerance limit for many oils. But why use such a random figure? The DIN 51519 table is used to determine ISO viscosity, with each value within a 10% range, as shown in Figure 1.

When you see an ISO VG 100 oil, the chances are that the actual viscosity of that oil varies between 90-110cSt. Therefore, if we start seeing our results vary by around 5% or trend towards the outer limits of any viscosity class, we know that something is going on with our oil.

Presence of Wear Metals

Wear metals prove that some type of wear is occurring. However, depending on their quantity, they can also provide some more insights into what is actually wearing away and whether it is normal wear or abnormal wear. Wear is reported in parts per million (ppm) or as a percentage. Here’s how to convert those percentages to ppm:

100% = 1,000,000ppm

1% = 10,000ppm

0.1% = 1,000ppm

The most common wear metals tested include Aluminum, Iron, Chromium, Copper, Lead, and Tin. Depending on the application, there are varying levels at which these will be flagged.

Table 1 provides an example of various applications and their respective limitations. These will vary based on your OEM and environment, but can be used as a general guideline. All numbers in Table 1 are in ppm.

Table 1: Wear metal limits for various applications
Table 1: Wear metal limits for various applications

AN/BN and the Presence of Contaminants

Contaminants are any foreign material in the system. Sometimes, lab tests may not be able to detect contaminants in a system because they are not specifically designed to identify that particular contaminant.

In these cases, users would need to specify what additional contaminants the lab should look for, or perform a broader FTIR (Fourier Transform Infrared) analysis to identify all the components in the oil and then determine which of them are contaminants.

The most common contaminants tested include Silicon, Water, and Fuel. Although AN/BN (Acid Number and Base Number) may not be considered a contaminant, it helps quantify the acid in your system, which shouldn’t be there; therefore, in some ways, it can be viewed as a contaminant. However, it is primarily a physical property and is listed separately.

Acid and base numbers act like an early warning system for oil health.

Table 2: Tolerance limits for some contaminants
Table 2: Tolerance limits for some contaminants

For diesel engines, BN is measured as having high base numbers, which will decline over time as acids accumulate. If the BN value declines to around 50% of its original value, then we have an issue with the acids increasing too quickly in the oils. On the other hand, AN is used for all other industrial oils (gears, hydraulics, etc.). There are varying limits for AN depending on the application, as shown in Table 2.

Silicon usually indicates the presence of sand, which is highly abrasive. This can accelerate wear in any equipment by essentially turning the oil into sandpaper and wearing away the insides of the equipment. Some of its limits are shown in Table 2.

Water in any form is highly destructive to all assets. However, some systems can tolerate a bit more water than others. This can be due to the nature of the oils (good demulsibility) or the nature of the systems, where heat is involved to help remove the water. Water in the system can lead to an increase in viscosity and disrupt the oil layer.

As such, the lubricant will not be able to form a full film to protect the asset. Water can also create an emulsion in the oil or lead to corrosivity issues. Table 2 gives some examples of limits for various systems.

Fuel contamination is an issue for most diesel engines. The presence of fuel in your oil can lead to a lower viscosity (hence the oil can no longer protect the components) and an increase in the flash/fire point of the oil, which can be particularly dangerous. We have some limits noted in Table 2.

 

Presence of Additives

It is more challenging to place these tests in a one-size-fits-all table, as oil formulations are consistently changing. The best way to interpret these additives would be to compare them against the initial values for the finished lubricant.

For your oil analysis program, always have a representative sample of the new oil so that comparisons can be made against it as the oil ages in the system. Additionally, the presence of additives in your report when they shouldn’t be there is also a sign of contamination, likely with another type of oil.

Find out more in the full article, "How to Read Oil Analysis Reports and translate Data into Reliability" featured in Reliable Magazine by Sanya Mathura, CEO & Founder of Strategic Reliability Solutions Ltd. 

by
November 15, 2025
Oil Properties / Used Oil Analysis

Why Different Oils Require Different Tests

Oil analysis reports often wear an invisible cloak, and only if we have a wizard capable of revealing what the numbers mean, they will more than likely end up in a drawer or file on the computer. There are many similarities between oil analysis and blood tests, as they both serve similar functions.

They both test fluids, quantify the results according to different categories, and provide envelope limits within which these values should exist. If the values fall outside these limits (either below or above), we need to take action to prevent failure of the critical asset (or human organ accordingly).

An oil analysis report is less about numbers and more about the story they reveal.

In this article, we will focus on understanding the basics of reading an oil analysis report, interpreting the results, and developing action items based on the information collected. We will take a closer look at reports on turbines (rotating equipment), gear, hydraulics, and engine oils, and what this all really means for your equipment.

Why Different Oils Require Different Tests

Before we dive into the report, we need to establish that not all oils are the same! As such, different oils are required for various types of applications. Therefore, each type of oil will require slightly different tests to determine whether it is performing optimally or not. However, there are a few tests that remain the same for all oils.

The most critical characteristic of an oil is its viscosity. As such, all oils are typically tested to determine whether their viscosity meets the requirements. Another function of the oil is to prevent wear. Thus, most oils are tested for the presence of wear particles, as this can help the user identify if any wear is occurring in the asset.

Oils should be kept clean; therefore, tests are performed to determine the presence of any contaminants, and these are carried out on most oils. Similarly, additives help oils perform their functions; hence, their presence or absence should be quantified to determine if they are indeed achieving their functions for all oils.

Tests for viscosity, the presence of wear metals, contaminants, and additives are the standard sets of tests that should be performed on any oil. There are more detailed tests that examine the specifics of various types of applications, but we will delve into these later in the article.

Find out more in the full article, "How to Read Oil Analysis Reports and translate Data into Reliability" featured in Reliable Magazine by Sanya Mathura, CEO & Founder of Strategic Reliability Solutions Ltd. 

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November 15, 2025