The Acid Number of a lubricant, sometimes called the “Total Acid Number” or TAN, is a commonly reported value for oil analysis and is generally considered an indication of oil aging and degradation.

But what does it mean, and how is it determined? Let’s break down what is reported, what techniques labs use, and if this parameter truly helps us pursue our goals for our lubricant monitoring programs.

The Mod. Squad

When I started my career at a U.S. Nuclear Power Plant in the late 1980s, I was hired as a recently degreed chemist to work in the facility’s maintenance department.

Admittedly an odd fit, but the wisdom of the move was to bring someone with some mechanical aptitude as an intern, and a chemistry background, into a maintenance department tasked with starting something called the “Predictive Maintenance Group.” On my first day, I was walked into a room full of laboratory instrumentation still in the shipping boxes and was told, “Here is an oil analysis laboratory. Go build it.”

That means there was no one to tell me, “This is how we have always done it.” Or point to an existing procedure or guide.

So I went to the ASTM Standards and created my own procedures. I was naïve enough to believe that that’s how everyone did oil analysis. So I was shocked when I visited a well-known and reputable laboratory to tour their facility. I noticed a jumbo box of paper clips beside the Acid Number titrator.

“What do you have these paperclips here for?” I asked.

I was told they were used as “disposable stirrer bars .” I was shocked, as I knew that the standard was very specific in the use of stirrers and the cleanliness required. I asked how they knew that the paperclips were sufficiently clean and consistent and how this met the requirements for the standard.

Next, I was told about a dirty little industry secret. The “mod.” designation. They explained that most of their ASTM standard methods were reported with the designation “mod.” for modification or modified, which means that the exact requirements of the standard were not followed but that a modified method was utilized to streamline the process to make it more economically competitive. And they explained that “Everybody does it. If we didn’t, we couldn’t perform the analysis cost-competitively.”

So what does that mean for the Acid Number test?

Is it essential for our laboratories to follow the standard precisely? Can the values possibly be different if they don’t? How do we know if a lab’s modifications to the standard method directly or potentially influence the measured parameters?

Unless auditing and periodic comparisons of measurements are made, such as the ASTM Proficiency Test Program, and evaluated for impact, the influence of such “shortcuts” might not be fully understood by the customer paying for the analysis.

How Is My Lab Testing for Acid Number?

If a customer submits samples to a lab for Acid Number analysis, you are probably like most and only get a single value returned. As a result, a quantity of potassium hydroxide per gram of oil, or mg KOH/g. Perhaps next to that is even an explainer of “D664” or maybe the dreaded “D664 mod.”

Does that help me understand what the lab did to arrive at that number?

When I began performing lubricating oil titrations, I utilized a Kyoto titrator to help automate the process per D664. Of course, instead of paper clips, I cleaned and dried Teflon stirrer bars for every titration and generated a titration curve for each sample.

Often, especially for the cleaner oils I tested, the titration curve was clear and produced two inflection points, one for weak and one for strong acids. Other times, there would be a glitch in the data near the inflection point, causing the automatic titrator to miss the endpoint, causing me to go back and manually calculate the endpoint.

The automatic titrator method allows the endpoint to be determined without an inflection point and taken as the value corresponding to a new value obtained every day in the lab using buffer solutions.

What about the volume of oil used to titrate?

The D664 method provides a table to determine the volume to be used and ranges from 20 grams of sample to just 0.1 grams. However, even for the most likely samples seen in an oil analysis lab, two very different titrations may be necessary, a low acid number value for new turbine and R&O oils of anticipated values <1.0 requiring 20 grams of sample, to the common additized gear oils that are between 1.0 and 5.0, requiring 5 grams of sample.

So, does my high-throughput lab check each sample and adjust titration volumes accordingly? Maybe they aren’t titrating my oil at all.

FTIR for Acid Number

With all of these complications, variations in method, and time-consuming steps to achieve an accurate titrated Acid Number, it is unsurprising that many labs have utilized Infrared Spectroscopy to determine the Acid Number value.

Initially, this approach to determining the Acid and Base numbers was pioneered at McGill University and involved a pre-treatment of the sample with a strong base or acid, and allow these to neutralize the acids and bases present in the used sample. An excess was used, and the leftover portion could be accurately quantified to determine how much acid or base had been in the sample.

However, today, few employ this method and instead utilize a chemometric approach to evaluate a used oil FTIR or I.R. spectrum and compare it to a reference spectrum. Assumptions are made about the types of acidic compounds that are typically formed and dominant in the used samples that have undergone oxidation. Calculations are made based on the height of peaks in these areas, correlating them to an Acid Number value.

If the assumptions about the source of acidity and oxidation hold, the Acid Number values reported in this way can be reasonably accurate. But they do not necessarily directly reflect the D664 titrated values that the used oil might produce. There are generally three ways to approach FTIR instead of chemical titration of used oil samples.

They are the Partial Least Squares method, a linear fit of the stoichiometry of prepared samples, or a combination of these approaches. The accuracy of these results depends on the vigor of the method used by the lab and the applicability of the references used to any particular sample that the lab subsequently encounters.

Some commercial labs have invested significant time in researching and developing methods to streamline the values produced by FTIR methods. Still, the customer that provides the sample is often unaware of how one lab’s techniques and approach may compare to another.

Is My Oil Becoming More Corrosive?

Even when we know that the test for Acid Number is being consistently performed and according to the applicable ASTM method, is there a complete understanding of what the Acid Number tells us?

I have seen, published in many places and presented by many experts over the years, explanations of the Acid Number or TAN, indicating that an increased value represents an increased “corrosive potential” of the lubricant.

My early attempts at introducing some new synthetic oil formulations to replace mineral oils in nuclear power plant components were initially rejected, citing that the new synthetic replacements had a higher Acid Number than the new oil data sheets for the existing mineral oils.

It was necessary to inform and teach the decision-makers that there was no connection between the Acid Number and the corrosive potential of the components in the machine.

This is outlined directly in the D664 standard, which states in the scope, “…the test method is not intended to measure an absolute acidic property that can be used to predict oil performance under service conditions. No general relationship between bearing corrosion and acid number is known.”

There are circumstances where the oil’s Acid Number is increasing, indicating increasing corrosive potential. That is when the oil is contaminated with strong and possibly mineral acids as part of the process near or in the machine or contaminants in the environment that the oil operates in.

Two examples might include diesel engines and specific compressors. In a diesel engine, the oil is initially formulated with an overbased detergent, with the understanding that fuel burning generates acidic byproducts that can build up in the oil over time. Initially, these are neutralized by the detergent, but eventually, the strong mineral acids may exceed the neutralization capacity and begin to build up in the oil.

This is why some use the testing strategy for both Base Number and Acid Number in combustion engines, looking for that point when the oil has lost its capability to keep the Acid Number low.

Another example would be natural gas compressors, mainly when the source gas is relatively “sour” or high in acidic content. As these gases would migrate into the compressor oil, Acid Numbers will rise sharply and reflect the increasing corrosive potential of these strong acids.

In some ways, I appreciated the former designation of TAN or Total Acid Number. It underscored the idea that this count included weak and strong acids. A significant increase in the Acid Number might reflect the addition of strong acids, a combination of strong and weak acids, or perhaps only weak acids (from hydrocarbon oxidation).

Without digging further, we don’t know, and the Acid Number is a fairly blunt tool for understanding what is happening regarding the chemistry of our oil.

Is Acid Number Even the Right Test?

After disconnecting the concept of measuring corrosion potential from the Acid Number, we return to the method’s original intent: to monitor the “…relative changes that occur in oil during use under oxidizing conditions…” (also from the D664 scope).

And this is indeed how many utilize Acid Number to monitor the oil’s degradation over time while in service, as evidence of its oxidation. However, this condition is primarily a lagging indicator.

In other words, the oil must undergo physical conversion from the original unoxidized hydrocarbon (typically) to an oxidized species that changes those molecules’ properties, including the ability to maintain a dynamic protective fluid film. As the Acid Number increases, the amount of molecules that have been compromised also increases.

However, the effect of potential damage to the machine in compromised lubricating films is not necessarily proportional to the increase in the Acid Number measuring this effect. Unfortunately, wear levels can start to increase before a substantial change is seen in the Acid Number, reflecting an accumulation of damaged molecules of lubricant.

If instead of targeting lubricant condition for the degraded ability to prevent damage, the desire is to prevent this degraded condition altogether, a leading indicator of degraded molecules would be required.

This is why in many monitoring strategies, other methods, such as the RULER technique (ASTM D7590), are utilized as a sign of the loss of the ability of the lubricant to prevent oxidation so that proactive measures can be made to replenish or replace the oil to reset the capability of the oil to resist oxidation.

In this regard, the Acid Number of the oil, concerning the degree of oxidation of the oil molecules, is similar to the “oxidation” parameter reported by Infrared Spectroscopy methods.

Infrared spectra are used to quantify the appearance of carbonyl groups, which are absent in many, mainly mineral, base oil formulations. The carbonyl groups can appear as carboylic acids, ketones, and aldehydes formed by the process of oil oxidation and are, therefore, a lagging indicator of the oxidation of viscous film-forming molecules in the lubricant.

So Where Do We Go From Here?

A review of any lubricant analysis program must start with the goals of the asset owner. Why am I performing Acid Number, how am I using the results, and what do I expect this investment in producing a trendable and comparable number will provide concerning my lubricant and my machine?

If we first ask these questions, we can then determine the initial decision point, which is whether or not the Acid Number adds any value to my lubricant analysis program.

If my goals are proactive, that I wish to detect the degradation of oils early and with enough time to act to avoid abnormal wear, oil degradation, and the formation of varnish, then Acid Number may not be the test to use.

In that case, leading indicator tests like RULER and MPC for varnish potential and large reservoir tests like RPVOT may be required and completely overtake the Acid Number from a lubricant management decision standpoint.

Work with your laboratory to better understand what tests and methods they use to provide you with an Acid Number and ensure they will help you meet your goals. An informed asset owner looks beyond a simple cost-per-sample approach and aligns their asset goals to the strategy of test slate selection and data result action.

References

Petrucci, R.H. and Wismer, R.K., General Chemistry with Qualitative Analysis, MacMillan Publishing Co., 1993.

McMurry, J., Organic Chemistry, Brooks/Cole, 1984

D664 – 18, “Standard Test Method for Acid Number of Petroleum Products by Potentiometric Titration”, ASTM, West Conshohocken, PA.

Why The Most Popular Oil Analysis Test Ever Might Actually Be the Worst

Over the years, oil analysis has gone from something adopted by just a few asset owners with critical components to a universal tool to achieve reliability.

 As oil analysis entered the mainstream, laboratories emerged to serve this growing demand, in many cases using or developing innovative and robust analytical techniques to unlock the information hidden in each sample submitted.

 As efforts evolved to standardize and create uniform approaches to analysis, the end-user community began to expect the advantages of competitive pricing to get maximum value for their investment in oil analysis services.

Of course, there is nothing wrong with pursuing value for your money. Still, perhaps somewhere along the line, the commercial lab industry began to bend a bit to the demands of the purchasing agents pushing for lower-cost analysis solutions.

After all, you can have the best lab in the world, but no one will benefit if you don’t win any purchase orders. But whether an asset owner demands a highly detailed and outcome-oriented test slate or seems to be looking to perform something called “oil analysis” for the lowest possible per-sample price, there may be one test that seems to end up on everyone’s test slate and is perhaps the most confusing, subjective, inaccurate, and useless test ever devised for oil analysis – the Crackle Test.

Do I Have a Water Problem?

The lowest common denominator for oil analysis may be wear condition determination. Everyone seems interested in the asset’s condition, the more significant value component of the machine-oil state.

But it is almost universally recognized that one of the most common and troubling contaminants that can derail an otherwise healthy machine, and its lubricant, is the presence of water. “If only there were a simple (and cheap) way to know whether I need to be worried about water” seems to be the sentiment and statement that would lead to a resourceful person suggesting that yes, we can do this with a simple laboratory hot plate.

Albert Einstein said, “Everything should be made as simple as possible, but not simpler.”

In truth, his quote was more complex, ironically, and referred to irreducible basic elements and without having to surrender the adequate representation. The latter draws concern when you carefully consider the method and value of the crackle test carefully.

 A solution to the “Do I have a water problem” question must address what a water problem is, how water impacts the machine in question, how water impacts the lubricant it is occupying, what are the minimal values at which an impact is felt or measurable, and the alerting and alarming levels at which we wish to monitor the water concentration.

An asset owner would likely want to believe that at water concentrations below the lower limit of detection of the method, they need not worry about water’s impact on their asset or its lubricant.

Or, a second and more defining analysis test can be triggered using the screening technique with high confidence and little chance that a potentially damaging condition would go undetected.

How Low Can the Crackle Test Go?

Because the Crackle Test does not have an associated ASTM Standard, we cannot rely on the precision statement that such a method would supply. Therefore we must look at what the published literature says about the technique or how the performing laboratories represent their particular version of the method.

One published article states, “Under carefully controlled lab conditions, the crackle test is sensitive to around 500 ppm (0.05 percent) of water-in-oil depending on the type of oil.”¹

Another source states, “But as you migrate away from engine oils into industrial oils, the 500 ppm detection limit is no longer valid in all oil types; specific oil types exhibit different crackle detection limits.”²

This last article outlines a study by the authoring lab that determined that with varying lubricant types and used lubricant conditions when compared to accurately determined values (Karl Fischer method), the detection varied from a lowest positive limit of 100ppm to a highest negative at 1830ppm. This means that sometimes oils can be contaminated with as much as 0.15% moisture or higher and be undetected by the crackle test.

To look at this myself, I selected several samples from our lab that had already been tested to ppm levels and subjected them to a procedure for Crackle Test.

This procedure used a small hot plate with a white ceramic surface with only minor staining from use, using the controller setting at 170° C. At this setting, I measured the surface temperature to be approximately 320° F. (Let’s talk about temperature accuracy and stability in a moment).

I checked five samples with measured moisture levels ranging from 48 ppm to 2412 ppm, as outlined in the table below. Two of these samples were below the 500 ppm threshold, usually cited as the lower limit of detection, while the other three were well above this value.

Of these, the only sample that would have an obvious and clearly observed “Positive” Crackle Test result was the Chiller compressor sample, with only 464 ppm H2O as the measured result.

This positive result is undoubtedly from the refrigerant absorbed into the lubricating oil. There was no clear threshold to screen these samples for further analysis in this population of varying types of synthetics and mineral oils.

How Low SHOULD Your Moisture Level Test Be Able to Go?

So even if the Crackle Test could reliably detect and screen samples above and below 500 ppm, with the method here or some enhanced approach, is it good enough for screening purposes?

One of the key reasons to detect and quantify moisture contamination is the potential impact on bearing life. Figure 2 below shows a relationship between moisture level and life impact for rolling element bearings based on the disruption of an effective EHL film in the presence of higher moisture levels.

This chart shows a cut-off line of 1000 ppm H2O, or 0.1%, as the “observable limit.” Even if we assume that we can reliably detect moisture down to 500 ppm, this chart shows us that there is a 60% reduction in life for these bearings when moisture levels are maintained at that level.

With a focus on machinery life and sustainability, should we be content with employing monitoring techniques that, under the best of conditions, only begin to alert us to the presence of a contaminant that can be robbing us of 60% of the life and thus the investment in this capital asset?

If asset owners truly understood this limitation of the method, I doubt that it would be approved as a screening test for monitoring their machinery.

My experience as an asset owner responsible for lubricant monitoring included standby nuclear power plant components that were expected to be kept in a state of readiness, even when they were not routinely operated to support the plant.

In one such location, we employed housekeeping and cleanliness standards, along with motor heaters that would keep the oil warm in standby condition to prevent the buildup of moisture in the oil.

In this state, the monthly samples routinely returned very low moisture levels as measured by the Karl Fischer Test of 20-40 ppm moisture. So when an oil sample I took rose to 85 ppm, I took notice.

A review of the motor manufacturer and lubricant supplier guidelines showed an operating limit of 1000 ppm moisture. So while there was no “condemning limit” in play, the clear increase in moisture raised concerns that were only detectable due to the routine and precise trending of the ppm moisture levels.

Because a primary concern was the integrity of the bearing housing water cooler as the source of this moisture, a hydro-test pressure check was performed on the cooler. A leak was found that was calculated to increase at a significant rate when the motor would be called for an extended run, and by finding the low level of water contamination, a significant issue was avoided.

So Really, What IS the Crackle Test Method?

It seems like an easy question to answer, but with testing, if no standard exists, no clear guidance is there for the correct and consistent way to measure. For example, a search of published literature produces the following hot plate temperatures for performing the test:

300° F, 320° F, 400° F, and 600° F

I was shocked to find 600° F published as a temperature to use for the Crackle Test, and I now believe that someone mistakenly converted 320° Celcius to Fahrenheit.

Still, it underscores the problems with a method with no agreed-upon standard. Even the variation from 300 to 320 to 400° F could significantly vary results.

What about the hot plate? Most methods say to use “approximately 320° F,” for example, perhaps recognizing that hot plate temperatures are not precisely controlled. In fact, a hot plate is typically an on-off thermostatically controlled heat source, generally requiring moderation with a target volume of liquid being heated.

Suppose one watches a hot plate surface over time. In that case, the temperature will dip low below the target temperature, then turn back on and cause the temperature to rise above the target fairly significantly.

For my tests in this article, while attempting to maintain a hot plate center temperature of 320° F, a variation was seen from 308.4 to 327.8° F. The hot plate temperature is not uniform across the hot plate.

An infrared image can show that the hot plate is hottest in a pattern where the surface is closest to the underlying heating element. Another factor is the amount of oil added to the hot plate and how quickly.

When a drop of oil touches the hot plate, the oil itself has a cooling effect on the surface, and it will take some time for the surface temperature to heat back up. So there are many limitations to truly ensuring that the heat from a hot plate is sufficient and uniform and that the moisture in the sample is heated to or close to that target temperature.

And the Value of the Crackle Test Is …

To say that the Crackle Test provides no value is not accurate.

For something to provide no value, it should leave you with the same information you had before you performed the test. I will argue that the Crackle Test is worse than a test of no value.

The Crackle Test is harmful. It gives the asset owner a false sense of security that moisture is not a problem when a “negative” result is received. The only validity for a screening test is that it must reliably tell us when additional testing is required.

The Crackle Test fails to meet this requirement by allowing samples contaminated with water to escape further scrutiny: the follow-up and accurate testing options such as Karl Fischer or VaporPro (ASTM D6304 and D7546) could find and accurately quantify these potential problems.

The argument is typically that the Crackle Test is just a screening test, a go-no-go gauge to see if further testing is warranted. A field test that can find the worst-of-the-worst to prioritize action.

But if the test itself cannot be relied upon to inform us when additional testing is required consistently, it has no value. It should not be found in a laboratory test slate when protection against the damage of water contamination is needed for any critical lubricated asset.

References

1. Noria Corporation, “Monitor Water-In-Oil with the Visual Crackle Test”, Machinery Lubrication, March 2002.
2. Eurofins, “Crackle Test: Do You Know Your Detection Limits?”, Data Interpretation, Program Management, Routine Testing, https://testoil.com/program-management/crackle-test-do-you-know-your-detection-limits/ May 2011.

Oil analysis has a strong history of being incorporated into maintenance strategies to optimize lubricant life and protect oil-lubricated assets from wear and damage. Grease-lubricated components, which are much more widely present, are often neglected from consideration because of some of the challenges of obtaining representative grease samples and methods for analyzing small quantities typically available.

More recently, developments of grease sampling tools and enhancement of grease analysis methods have led to global standards for grease sampling and analysis and the opportunity to incorporate this as a strategy to improve sustainability in these assets.  

Standards and methods for sampling various grease-lubricated components and analysis tools and tests for characterizing grease consistency, wear, contamination, and oxidation condition have been developed and are widely adopted.

Using these tools to optimize grease life, reduce waste and maintenance resources, improve grease-lubricated assets’ availability and uptime, and extend grease-lubricated components lead to sustainable asset management practices.

Principles of Sustainability

There are numerous principles of sustainability applied to various economic undertakings and industries. A common basis for these initiatives is the 17 Goals of Sustainable Development from the United Nations

Keying in on several of these goals, a list of “Attainable Goals of Sustainable Development through Grease Sampling and Analysis” can be provided:

• Conserving Energy – Selection of optimal viscosity and grease consistency at operating temperature to prevent friction and wear AND minimize energy losses
• Conserving Natural Resources – Utilizing Condition-Based Grease Replenishment to minimize lubricant consumption; early identification of abnormal wear for proactive intervention to purge contaminants and extend equipment life
• Minimize Environmental Impacts – Reduce waste by reducing grease consumption, timely and targeted grease replenishment instead of time-based or lagging indicator
• Economically Sound Processes – Factoring the total cost of operation rather than the price of the product, greater RONA (Return on Net Assets) on equipment with longer life.
• Enhancing Employee, Community, and Product Safety – Less over-greasing means less spillage and potentially fewer maintenance tasks.

Grease Sampling Considerations

Existing practices for obtaining grease samples from bearing housing and gears often need to be more consistent. They likely do not represent the actual condition of the “active” grease near the lubricated surface. The challenge in optimizing a grease analysis is the development of tools that utilize a smaller amount of grease that enables representative grease samples without disassembling the component. 

In the example of the Grease Thief, such a sampling fitting is also optimized for the subsequent laboratory analysis with just 1 gram of grease.

The Grease Thief was developed for this purpose, with the first design focusing on pillow block bearings. At the National Institutes of Health, failures were being experienced on critical grease-lubricated fan bearings. 

Without a good way to test greases, vibration analysis was used to detect failures in progress and schedule repairs. The root cause of the problem was often overlooked. After implementing the Grease Thief tool for sampling, systemic issues were identified, including grease mixing and greases contaminated with particulate during greasing. By sampling the equipment in the field, many potential problems were identified and corrected without damage to the bearing.

The principle behind the Grease Thief is obtaining a targeted grease sample from the live zone. Similar to the principle of a liquid sample “thief,” the device can travel from the access hole to the active lubrication location near the bearing or gear mating area and bypass the non-representative grease. 

The sampler remains closed with the piston in place over the opening until it is positioned to core a representative sample.

To achieve this, the grease sampler is inserted into a t-handle extension to permit remote actuation and capture of the sample at the site of active grease use and wear generation adjacent to the mating gears or bearing surface.

Grease Analysis Approach

A program that targets the “Attainable Goals of Sustainable Development” will include a test slate for grease analysis that helps to inform decision-making to address these goals. 

An example of this was a grease analysis project initiated by Boeing to enhance the asset availability and sustainability of the Chinook helicopter, a key component for cargo and personnel movement for numerous military organizations worldwide.

The analysis test slate selected would be based on the known oxidation stressors and contaminant sources found in the machine application and additives present in the grease to extend life. The ASTM Standard Test Method for evaluating in-service greases is D7918.

This method uses the tests identified in TABLE 1, which list the key parameters measured and assessed in the grease. Two additional tests (TABLE 2) are typically included in the analysis, although they are not found in the current version of the ASTM D7918 standard.

The Rotating Disc Electrode (RDE) Spectroscopy test and Fourier-Transform Infrared (FTIR) Spectroscopy test provide elemental and molecular spectroscopy results, respectively, and complement the analysis performed in D7918 by monitoring non-ferrous wear particles, additives, contaminants, and the oxidation of the grease. 

While the ASTM D7918 method does provide for a particle counting test, a thin-film direct imaging technique, it was determined that the variables in the greases used in the aircraft, as well as the anticipated conditions of the greases, may make this method ineffective due to insufficient optical clarity of the grease. Therefore, the particle counting function was substituted by monitoring the grease’s elemental Silicon (Si) levels as measured by the Rotating Disc Electrode Spectrophotometer.

As the most common source of external particulate was expected to be sand or dirt based on operating environments and action of air turbulence, Silicon was deemed to be a suitable indicative parameter to measure the ingression of these particles.

The individual grease sample results were compiled to find the seven parameters influencing grease life. These included elemental iron (Fe), elemental silver (Ag), elemental Silicon (Si), ferrous debris level, moisture, Die Extrusion Index (consistency), and oxidation index.

These parameters were plotted as a function of flight hours since the last grease service to determine the interval at which each parameter began to degrade. A curve fit was developed for each graph based on the flight hour trend behavior of the parameter. These relationships were primarily linear, but some were logarithmic. 

The formula for the curve fit was used to calculate the number of flight hours that corresponded to the target parameter replenishment level. The optimal service interval was described as the number of service hours that would allow grease replenishment before the onset of degradation.

In this way, each component would be adequately protected against wear and damage by ensuring that the grease would be replaced by new grease before it degraded or accumulated significant contaminants. An example of the regression analysis used to project the optimal interval is shown in FIGURE 5.

In the case of this parameter, “Oxidation Rating,” the target parameter replenishment level was selected at a value of 75, which corresponds to the remaining 25% of the original level of anti-oxidant additive protection. In this case, the curve fit line equation produces a value of 171 flight hours.

Findings

As a result of the study, the majority of the lubrication intervals were extended, many double the established grease service intervals currently fielded by the various operators. This extension allows each operator to adjust their grease servicing intervals, thus allowing a reduction in downtime and maintenance costs while ensuring the continued safe operation of the aircraft.

The benefit of the study is that final service interval determinations can be aligned with existing maintenance intervals to support a maintenance optimization effort completed by Boeing. These results translate to fewer interruptions to operations for required servicing.

In total, an estimated reduction from 98 lubrication tasks per 1000 flight hours to just 56 lubrication tasks per 1000 flight hours, and a reduction from 20 service interruptions per 1000 flight hours to just ten service interruptions per 1000 flight hours.  

Sustainable approaches to asset management, electricity generation, transportation infrastructure, and other capital-intensive enterprises must be found to continue in an economically viable manner. 

Our resources are limited, and approaches that optimize our use of these valuable resources are necessary sooner rather than later. Many corporations now recognize a responsibility to achieve this and are adopting new strategies to meet such goals.

A closer look at grease lubrication and recently developed technologies for grease sampling and analysis can help organizations operating grease-lubricated assets accelerate initiatives to increase sustainability in their enterprises.