The Basics of Interpreting Oil Analysis Results

You’ve taken the oil sample, sent it to the lab and the results have just arrived in your inbox. Now what? If you scan the report looking for “red lights” and “green lights”, just know you’re not alone. That’s how most people are reading an oil analysis report. But there’s so much more value if you take another look.

In this webinar, we will help your businesses take the next step and look beyond the traffic light system so that you can better understand your used oil analysis reports. The best thing – it doesn’t cost a dime! All the cost of a used oil analysis program is spent on the bottles themselves, so any further insight you can obtain from the data is pure upside.

Key Takeaways:

  • How to read a basic used oil analysis report
  • Key metrics to help you understand oil health
  • Key metrics to understand machine health
  • Easy methods for spotting trends in data

Oil analysis and interpretation hold tremendous potential and are often overlooked. In fact, based on visiting various sites and engaging with customers, nearly 98-99% of businesses are already conducting oil analysis. They invest in collecting samples and sending them to labs for analysis, which involves upfront costs. Now, here’s the exciting part: the real value lies in the interpretation of the data we’ve already collected. We’ve put in the effort to gather the samples, and now it’s time to unlock the insights and make informed decisions. While optimizing the sampling process is important, the power is truly in your hands. With access to all this valuable data, you have the opportunity to shape your own future in the realm of lubrication.

The 4 Types of Maintenance

Let’s delve into the different types of maintenance that are likely familiar to most of us. We can simplify them into four categories

  • Reactive – Fix it when it breaks.
  • Preventive – Fix it at pre-determined intervals.
  • Predictive – Fix it when the problem is sensed.
  • Proactive – Fix the root cause before the problem event.

To illustrate this, let’s think about heart health. Proactively maintaining your heart means adopting a healthy diet and exercising regularly to prevent deterioration in the first place. Moving into the predictive domain, we can measure statistics like blood glucose and cholesterol to intervene when necessary. This could involve lifestyle changes or medication as prescribed by a doctor. 

Now, when it comes to preventive maintenance, it’s like scheduling open heart surgery periodically to clean out arteries and prevent them from clogging up. However, this approach carries its own risks. Just as every surgery poses dangers to the body, there’s the potential for maintenance-induced failures in our assets. Unnecessary surgeries can lead to infections or prove too much for the body to handle, resulting in unfortunate outcomes. 

Lastly, we have reactive maintenance, which is akin to waiting for our heart to stop and then attempting to restart it. Clearly, this isn’t an ideal strategy for heart health. However, there are circumstances where reactive maintenance is reasonable, such as for non-critical small assets that are more cost effective to replace than repair. 

While reactive maintenance used to be more common, recent supply chain shortages have made asset replacement less straightforward. It highlights the importance of moving towards proactive and predictive maintenance strategies to optimize asset performance and avoid unexpected breakdowns.

Where Does Oil Analysis Fit as a Maintenance Type?

When it comes to oil analysis, we’re primarily operating in the predictive and proactive realm. We gather information about both the oil and the asset to make decisions that cover both predicting failures before they happen and taking proactive actions to prevent degradation in the first place. To further understand, you can categorize the results of oil analysis into three main areas fluid condition, contamination levels, and asset wear. Each of these areas provides valuable insights.

Asset Wear

The wear information is predictive since it indicates the degradation of the asset. For those familiar with the P to F curve, this wear information tells us where we are on that curve, bridging the gap between problem initiation and failure.

Contamination Levels

On the other hand, the proactive domain focuses on contamination. We know that contamination is a common cause of machine failures. By measuring contamination levels in the oil, we can take action, such as filtering out contaminants, to prevent failures from occurring in the first place.

Fluid Condition

Similarly, fluid condition plays a crucial role. In some cases, the root cause of failure is allowing the oil to degrade to a point where it becomes unsuitable for use. By measuring and addressing fluid conditions, whether through bleeding, topping up, or using additives, we can prevent degradation from happening in the first place.

To simplify, in predictive maintenance, we focus on wear information, which reveals asset degradation. In the proactive domain, we prioritize contamination levels and fluid condition to prevent failures caused by contamination or degraded oil. By understanding these different aspects and their corresponding areas on the P to F curve, we can make informed decisions and take appropriate actions to optimize maintenance strategies and maximize asset performance.

What Are the Sections of an Oil Analysis Report?

Alright, let’s dive into step one. You’ve taken your oil sample, sent it off for analysis, and now it’s time to review the report that has landed on your desk. Nowadays, reports usually come in the form of an email, but regardless of whether you use ALS, Fluid Life, or another chosen laboratory, or even conduct on-site oil analysis with spectroscopic machines, the anatomy of a report follows a similar structure. Remember, while the specific format may vary slightly between reports, the key sections and groupings of information remain consistent. So, let’s explore further into the report to uncover more valuable insights. (Also, note that you can download the presentation at the top right of this page to save the visuals and follow along with this oil analysis report breakdown.)

Sample Information

At the top of the report, you’ll typically find user input information. This section contains details about the sample that you provided to the lab, such as the age of the oil or equipment, volumes, and other relevant information. It may also include information about the asset itself, such as an asset ID number and its type. These initial details set the foundation for the rest of the report.

Oil Parameters

The next section of the report is generally about oil parameters. So, let’s unlock the secrets hidden within this box as we uncover the intricate details of the oil’s condition and gain a deeper understanding of its overall health. This is where we explore crucial factors such as viscosity, oxidation, nitration, and total base number (TBN). These parameters primarily provide insights into the condition of the fluid itself. However, it’s important to note that some of these parameters also offer valuable clues about the machine’s wear and contamination levels.

For instance, the PQ index serves as a helpful indicator for identifying the presence of contaminants like soot, water, and coolant. It gives us a glimpse into the extent of contamination affecting the oil. While this section may touch on contamination and wear, its primary focus is to shed light on the fluid condition.

Wear Information

Now, let’s continue down the page to uncover valuable information about asset wear. This section is specifically focused on wear metals, and it’s based on the analysis of ICP (Inductively Coupled Plasma) metals. When you come across that extensive list of different elements from the periodic table, what the laboratory is doing is making informed estimations about the presence of metals within your machinery. If these metals are detected in the oil, it’s a strong indication of wear taking place.

However, it’s important to understand that these estimations are educated guesses. The lab doesn’t have a complete picture of what’s happening inside your machine. Therefore, distinguishing between what represents wear and what is merely a contaminant becomes a crucial aspect we’ll discuss further when we explore how to interpret the results.


Next is contamination. It’s important to note that identifying contaminants is also based on educated guesswork. In the context of oil analysis, the lab assumes that certain elements like silicon, sodium, and potassium are contaminants. By detecting the presence of these elements, we gain valuable insights into the nature of the contaminants affecting the oil. While it’s not a definitive confirmation, this information provides us with a better understanding of the potential contaminants present in the oil sample.


Lastly, let’s delve into the additives section of your oil analysis report. Additives provide us with insights into the fluid condition, specifically regarding additive depletion in the oil. However, it’s important to remember that these interpretations are again based on educated guesses. For instance, the lab assumes that calcium is related to the detergent package. While it’s an assumption, it helps us gauge the condition of the additives present in the oil.

How to Interpret Oil Analysis Results

Level 1: Traffic Lights

Currently, most businesses operate at level 1, where they receive their results and rely on a simple traffic light system or even emojis to indicate the overall status. Green means all is well, while yellow or red highlights areas that need attention or have exceeded certain thresholds.

However, we need to recognize that these limits and indicators are often arbitrary. They might be set by the Original Equipment Manufacturer (OEM) for specific equipment, or they could be based on industry rules of thumb. Your chosen laboratory might have its own internal limits or statistical analysis methods to determine thresholds. It’s crucial to ensure that the lab is using appropriate and relevant limits, especially if your equipment is under warranty tied to specific parameters.

At level 1, the lab-generated comments accompanying the traffic light system are generic and auto-generated based on algorithms. While they may offer some guidance, they often lack depth and tailored insights. A manual review of every result is impractical for labs handling large volumes of samples daily.

Currently, about 90% of businesses stick to Level 1 analysis due to time constraints and limited expertise. However, as assets increase in importance and criticality, it’s essential to move to Level 2 interpretation.

Level 2: Interpretation

Level 2 analysis goes beyond the traffic light system and generic comments. It involves a deeper understanding of the specific asset and its unique operating conditions. At this level, one should consider factors such as the asset’s age, maintenance history, and the goals of the maintenance program. Level 2 analysis allows for a more tailored approach and provides actionable insights based on the specific requirements of the equipment. By striving to reach Level 2 analysis, businesses can enhance their decision-making and optimize asset maintenance strategies, particularly for more critical assets. Let’s explore the possibilities and benefits of advancing to Level 2 in result interpretation.

This level involves taking the interpretation of results into our own hands. We can start by examining the additional information provided by the lab, such as contaminant and additive categories. However, we must keep in mind that these categorizations are educated guesses made by the lab. It’s essential for us to bring our knowledge of the specific application and environmental factors into the analysis.

Guides can assist us in understanding the possible sources of contaminants. Metals like aluminum and silicon, for instance, are often found together and can indicate dirt ingress if their ratios align. This deeper understanding enables us to make more informed interpretations.

Oil Analysis Interpretation Case Studies

To illustrate the importance of interpretation, let me share three case studies. In one case, an engine oil showed a caution for oxidation levels. However, the short oil life and the use of a different test method by the lab actually led to a false alarm. Understanding the test method and OEM criteria is crucial in such situations.

Another example involves jet oil used in aviation. The lab’s traffic light system raised an alarm about low phenol levels. However, the unique formulation of the oil resulted in phenol-like byproducts during oxidation, making the alarm unnecessary. Avoiding unnecessary oil changes is essential, especially for expensive products like jet oil.

Lastly, a diesel engine oil analysis prompted an alert for copper levels, suggesting potential bearing damage. However, the recent oil cooler replacement explained the presence of fresh copper and ruled out the need for engine disassembly. Combining operational and maintenance information with test results is vital for accurate interpretations.

In summary, we need to synthesize the information from the lab, including the traffic lights, test methods, formulation knowledge, and operational insights. By going beyond the basic analysis, we can enhance our understanding and make more informed decisions for our assets.

Level 3: Trend Analysis

Level 3 is where things start getting sophisticated. Trend analysis becomes crucial as it provides valuable insights. Typically, oil analysis reports present trend information, graphically displaying parameters such as viscosity and contaminants over the last few test results. It is important to collect consistent results for the same asset to ensure accurate trend analysis. However, it is advisable to be cautious with graphical representations as they can often be misleading.

Contrasting Trend Results

Let’s take the example of bearing analysis. We can observe two different trends: one alarming and the other not so concerning. The red line signifies an acceleration in copper levels, indicating a progressively worsening problem over time. This is a cause for greater concern. On the other hand, the orange line shows a gradual decline, suggesting a leveling out of the issue.

Examining these trends over time, we can understand corrosion better. As the acidity of the oil increases, it becomes more corrosive to copper components like bearings or coolers. This leads to an acceleration of the problem as copper catalyzes oil oxidation, generating more acids and causing further corrosion. In contrast, passivation involves forming an inert layer on copper surfaces. As fresh copper exposure diminishes over time, the trend levels out. If we had observed these trends in previous results using Chevron Delo, we would have gained valuable knowledge. One trend would have raised concerns, while the other would have provided comfort.

Accurate Trending Requires Combining Results with User Input Data

To develop accurate trends, we need to combine the information from the report with user input data. This includes recording the sampling date, equipment age, oil age, makeup volume, asset name, and type. Neglecting this information can lead to flawed analysis. For example, knowing the lubricant’s name is crucial when examining additive depletion trends. Deviations from the norm can be due to using the wrong lubricant or intentionally switching to a different one.

Choose Your X-axis Parameter Wisely

Different contaminants exhibit varying trends. Water, which accumulates slowly due to atmospheric absorption, should be plotted against calendar time. In contrast, soot, a byproduct of engine operation, should be plotted against engine hours or oil hours. Aligning the appropriate parameter on the X-axis enhances trend accuracy.

Understand the Importance of Intervals Between Data Points

Considering the interval between data points is also vital. Presenting equal intervals between dates can be misleading. It is recommended to download the data and analyze it independently using tools like Excel. Linear representations may not effectively capture deviations. Plotting data based on oil drains or grouping similar assets can provide better insights into deviations and performance discrepancies.

Know the Independent and Dependent Variables

When we analyze oil, we’re not dealing with unrelated variables. Instead, we’re looking for connections between different factors. Take oxidation, for example. We know that it’s usually linked to viscosity. Now, viscosity is the most critical result on the oil analysis page. It’s what primarily safeguards your equipment, accounting for about 99% of its protection. So always start by checking the viscosity number, which is typically within an acceptable range. However, if we want to gain a better understanding of the relationship between oil degradation, specifically oxidation, and viscosity, it’s helpful to plot them together.

You see, as oxidation occurs, it tends to increase the acid value. Therefore, if you’re facing an issue with the Total Acid Number (TAN), it’s worth examining its connection with oxidation. It’s all about comprehending how different results relate to one another. And honestly, the key is to experiment. When you receive a peculiar result, nobody knows the exact outcome in advance. Just have fun playing with the data and see if you can uncover any of these relationships.

By analyzing trends and identifying deviations, we can intervene and investigate the causes. Grouping assets and comparing their performance can help identify underperforming units within a fleet.

Oil Analysis and Interpretation Supports Reliability, Sustainability, and Profitability

Our ultimate goal is to achieve reliability, sustainability, and profitability. To reach that goal, we can apply some key principles we’ve discussed. Remember, level 1 involves using traffic light analysis to quickly assess the situation. Level 2 takes us deeper into interpretation, providing a more comprehensive understanding. And finally, level 3 brings us to trend analysis, where we can identify long-term patterns. By implementing these principles and delving into the different levels of analysis, we genuinely believe you can attain the reliability, sustainability, and profitability you aspire to achieve.

Oil analysis and interpretation are powerful tools that hold tremendous potential for businesses. While many organizations already invest in oil analysis, the true value lies in the interpretation of the data that has been collected. By unlocking the insights from oil analysis results, businesses have the opportunity to make informed decisions and optimize their maintenance strategies.

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The Basics of Interpreting Oil Analysis Results

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