What Is Total Acid Number (TAN)?

When Oil Becomes the Enemy

A maintenance manager reviews the monthly performance report and notices a troubling pattern. Three bearing failures in the last quarter, all on equipment with recent oil changes. Seals were replaced twice on hydraulic systems that passed visual inspection the week before. A gearbox rebuild that wasn't scheduled for another year. The oil looked clean in every case. Filters showed normal pressure drop. The calendar said everything was on track.

It turns out the problem was invisible. While the oil appeared fine, it had turned chemically aggressive. Acidic compounds formed through oxidation were attacking metal surfaces, degrading elastomer seals, and breaking down the protective film between moving parts. By the time discoloration appeared or operating conditions felt rough, internal corrosion had already compromised critical components. The team was changing oil on schedule but missing the chemical degradation happening between changes.

Gaps in visibility

This is where most lubrication programs fail. Visual inspection catches gross contamination but misses acid formation entirely. Calendar-based changes provide consistency but ignore the actual oil condition. Some systems run too long and damage equipment, while others get premature changes that waste money. And, lab reports arrive as PDFs days after sampling, disconnected from work order systems and asset history. Your teams know oil degrades, but they lack the visibility to act before equipment pays the price.

Total Acid Number (TAN) monitoring provides that visibility. Expressed in mg KOH/g (milligrams of potassium hydroxide per gram of oil), TAN quantifies exactly how acidic the lubricant has become. Unlike pH measurement, which only works in water, TAN is specifically designed to work with oils and non-aqueous fluids. It reveals chemical degradation long before physical symptoms emerge, giving maintenance teams the early warning needed to prevent bearing corrosion, seal failures, and accelerated wear.

The shift from reactive to predictive approaches requires more than periodic lab values. TAN data must flow into maintenance workflows, trigger alerts when thresholds are exceeded, and drive work orders to prevent problems from escalating. 

When integrated with CMMS platforms that unify condition monitoring inputs, TAN becomes a predictive maintenance driver that protects equipment, optimizes oil life, and turns invisible degradation into manageable risk.

What Is Total Acid Number (TAN)?

TAN measures oil acidity in mg KOH/g, quantifying how much base is needed to neutralize acidic compounds that form as lubricants degrade through oxidation, contamination, and heat.

At its core, TAN answers a specific question. That is, “how acidic has this oil become?” The measurement is expressed in milligrams of potassium hydroxide (KOH) per gram of oil. This unit tells you exactly how much strong base you would need to neutralize all the acidic compounds present in a sample. When fresh mineral oil typically registers 0.05 to 0.5 mg KOH/g, and the same oil later shows 2.0 mg KOH/g, you know acid formation has accelerated and the oil is becoming chemically aggressive.

The chemistry is direct. As oil operates under heat, pressure, and exposure to oxygen, it oxidizes. This oxidation creates organic acids, peroxides, and other acidic byproducts. TAN testing uses potassium hydroxide, a strong base, to neutralize these acids. The amount of KOH consumed during this neutralization reveals the total acid content. The presence of more acids requires more KOH, which translates to a higher TAN reading.

This differs fundamentally from pH measurement. pH works by measuring the concentration of hydrogen ions in aqueous solutions. Oil is not water-based, so pH strips and meters give meaningless results when applied to lubricants. 

TAN testing uses titration methods designed explicitly for non-aqueous fluids, making it a suitable metric for industrial lubrication monitoring. When a reliability engineer needs to know if turbine oil, hydraulic fluid, or gear oil has degraded, pH tells them nothing. TAN tells them everything.

The equipment context matters because different systems have different TAN sensitivities. Turbine oils operate under stringent cleanliness and chemistry requirements, where even small increases in TAN signal problems. For instance, hydraulic systems tolerate moderate TAN values but still suffer seal damage and valve corrosion when acids accumulate. And, gearboxes handle higher TAN levels than turbines, but they eventually experience bearing pitting and surface corrosion. 

Each application has its own baseline and action limits, but the principle remains that constantly rising TAN means oil is shifting from protective to destructive.

Glossary Snapshot

• mg KOH/g: Milligrams of potassium hydroxide needed per gram of oil, the standard unit for expressing TAN
• Neutralization point: The moment during titration when all acidic compounds have reacted with base, signaling the endpoint of the test
• Acid value: Another term for TAN, used interchangeably in technical literature and lab reports
• Trending capability: The ability to track TAN changes over time, revealing whether oil is aging normally or experiencing accelerated degradation

Why TAN Matters for Equipment Reliability

Rising TAN signals that oil has shifted from protective to destructive, attacking metal surfaces, degrading seals, and accelerating wear long before visible symptoms appear.

The damage happens at the molecular level first, then works its way into physical failures that shut down equipment. 

Bearings

Acidic compounds in degraded oil create an electrochemical environment that accelerates corrosion on bearing races and rolling elements. This produces surface pitting and roughness that increases vibration, generates heat, and eventually leads to catastrophic bearing failure without advance warning. The bearing might look acceptable during a visual inspection, while microscopic corrosion is already compromising its structural integrity.

Seals

Seals face a different attack mechanism. Acids chemically interact with elastomer materials, causing swelling, hardening, or softening depending on the seal compound and acid type. This deterioration shows up as fluid leaks and contamination ingress, both of which accelerate further oil degradation. A hydraulic system might maintain pressure while seals are quietly degrading, then suddenly experience multiple leak points within weeks of each other.

Oil degradation

The oil itself loses protective capability as TAN rises. Acidic compounds interfere with oil film formation between moving parts, reducing film strength and allowing increased metal-to-metal contact. Friction rises throughout the system, wear accelerates, and components that should last for years begin to fail in months. At the same time, oxidation products polymerize and precipitate, forming sludge and varnish that clog oil passages and restrict flow to critical areas. These deposits create localized hot spots that drive even more oxidation in a self-reinforcing cycle.

Cost and operational impact

The financial consequences extend far beyond oil change costs. Oil condition indicators, including TAN, are trended with other signals to preempt failures. Systematic monitoring reduces misses and supports earlier interventions, protecting equipment and reducing the cost of quality. Rising TAN correlates with end-of-life predictions, framing business value through optimized drain intervals, reduced wear risk, and fewer unscheduled outages when TAN is trended with other parameters. 

Inadequate corrosion control leads to early failures, downtime, and repairs. Chemical degradation accelerates wear, linking proactive monitoring and corrective actions to extended component life and reduced frictional losses. Poor corrosion control accelerates wear and failure, increasing maintenance costs and downtime. In contrast, systematic monitoring lowers the probability of failure and repair costs, supporting higher operational effectiveness and throughput. 

It is nearly self-evident that investing in TAN monitoring and condition-based maintenance is better than repeatedly paying for bearing replacements, seal kits, and unplanned downtime that could have been prevented with early warning.

Impact by role

Plant Managers see the cascade effects when acid corrosion causes unplanned equipment failures. Production schedules slip when a critical line goes down for an emergency bearing replacement. Customer commitments are missed because a hydraulic system that was supposed to run another month starts leaking and loses pressure mid-shift. And, capital allocation decisions become distorted when emergency repairs consume the budget that was earmarked for strategic improvements. TAN monitoring provides the visibility plant managers need to protect production capacity and maintain delivery reliability.

Maintenance Managers gain the ability to shift from calendar-based to condition-based oil changes. TAN trending reveals which systems can safely run longer and which need earlier intervention. This enables better resource planning, as oil changes and related maintenance can be scheduled during planned windows rather than forced into emergency slots. When a manager can show TAN data that justifies an oil change decision, the maintenance action becomes defensible rather than debatable.

Reliability Engineers and technicians receive early warnings that enable intervention before permanent equipment damage occurs. A rising TAN value might trigger an oil analysis workup that reveals water contamination, leading to seal replacement before bearings pit. A sudden TAN spike could expose a process cross-contamination issue before it causes a system failure. For the technician sampling oil and the engineer analyzing trends, TAN provides the actionable intelligence that separates proactive maintenance from firefighting.

Pain Points When TAN Monitoring Fails or Doesn't Exist

Most teams struggle with fragmented data, manual processes, and disconnected systems that make proactive TAN monitoring nearly impossible.

The most frustrating aspect of TAN monitoring is that the degradation happens invisibly. Oil can maintain its color, pass a visual clarity check, and show acceptable viscosity by feel while acid compounds silently accumulate. 

Oil sampling

A technician samples oil that appears perfectly clean, and two weeks later receives a lab report showing that the TAN has doubled. By that point, bearings have been running in corrosive conditions for weeks. The damage is already progressing, but nothing looked wrong to the naked eye.

Changing oil by calendar

Calendar-based oil changes compound the problem by ignoring the actual condition. A turbine may be scheduled for an oil change every 5,000 hours, regardless of whether the TAN level is at 0.3 mg KOH/g or 2.5 mg KOH/g. One system gets a premature change that wastes oil and labor, while another runs too long and damages bearings. Neither decision is based on chemistry. Both are based on a date that has no relationship to what's happening inside the equipment.

Waiting for lab results  

When lab results finally arrive, they show up as PDFs in email or printed reports filed in binders. "Manual entries, inconsistent machine states undermine OEE/OOE dashboards and continuous improvement." The TAN value remains disconnected from the work order system, asset history, and condition monitoring platform. A maintenance planner sees the report but has no automated way to create a work order, no historical trend to reference, and no integrated view of what else is happening with that equipment. The data exists but remains isolated from action.

Frequency of testing

Testing frequency suffers from the same disconnection. Teams face "inaccurate/low-frequency data collection, over-aggressive PM schedules, shortage of skilled labor, and poorly executed tech rollouts." Critical equipment might get sampled quarterly when monthly trending would catch problems earlier. Lab costs and logistics drive testing cadence rather than equipment criticality. When results do arrive, interpretation depends on individual knowledge rather than systematic comparison to baselines and thresholds.

Delays and errors from manual TAN monitoring

The manual nature of most TAN programs introduces constant delays and errors. Technicians hand-write sample labels, planners manually enter lab results into spreadsheets, and maintenance managers review printed reports to decide if action is needed. Each handoff creates an opportunity for mistakes, lost information, and time gaps. A sudden TAN spike might not trigger an investigation for weeks because no automated alert exists.

Stuck in reactive cycles

Meanwhile, operational realities consume the time that could go toward proactive monitoring. "Breakdowns, jams, bad centerlines, missing materials, and shift handoff failures" keep maintenance teams in reactive mode. When every day brings urgent problems that require immediate attention, condition monitoring tasks often get deferred. Oil sampling happens late or gets skipped entirely. Lab reports pile up unreviewed. The team knows TAN matters, but can't maintain consistent monitoring while fighting fires.

The result is a gap between knowing TAN is important and actually using it to drive decisions. Teams recognize that acidic oil damages equipment, but lack the integrated systems, automation, and workflows needed to act on TAN data before problems escalate into failures.

Essential TAN Testing Methods

Standardized ASTM methods ensure consistent, repeatable TAN measurements that enable reliable trend analysis and defensible maintenance decisions.

The two primary approaches for TAN measurement differ in how they detect the neutralization endpoint, but both follow the same fundamental principle. First, add the potassium hydroxide solution incrementally until all acidic compounds are neutralized, and then calculate the amount of base consumed. Choosing the correct method depends on accuracy requirements, equipment investment, and testing environment.

Potentiometric vs. color indicator

Potentiometric titration (ASTM D664) uses electronic sensors to detect the exact moment when acids are neutralized. The oil sample is dissolved in a toluene and isopropanol mixture. Then, an automated titrator adds a standardized KOH solution while monitoring voltage changes with glass and reference electrodes. When the neutralization point is reached, the voltage shifts sharply, signaling the endpoint. 

This method provides objective, precise results that do not depend on operator interpretation. The equipment cost is higher, requiring pH meters, magnetic stirrers, and calibrated electrodes, but reproducibility is excellent. This makes potentiometric testing the preferred choice for critical applications and when trend analysis demands tight data consistency.

Color indicator titration (ASTM D974) relies on a visual color change to signal neutralization. The oil sample is prepared in the same solvent mixture, but p-naphtholbenzene indicator is added. As the KOH solution is manually titrated into the sample, the indicator shifts from orange to green-brown at the neutralization point. The operator must judge when the color change occurs, which introduces some variability between testers and lighting conditions. Equipment requirements are simpler and less expensive, using basic glassware and visual comparison charts. For routine monitoring with trained operators, this method provides sufficient accuracy at a lower cost.

Automated methods, as specified in ASTM D664 and D4739, emphasize practical constraints such as time, reagent cost, and interferences that limit the testing cadence. Automation enables higher-frequency monitoring, which improves reliability outcomes by detecting oil degradation earlier. 

Steps for accurate TAN measurement

Sample preparation

Representative sampling requires taking oil from operating equipment at normal temperature while the system is circulating. Clean sampling equipment, proper container selection, and clear labeling with equipment ID, date, and location are essential. Samples must be stored in sealed containers away from heat and light if testing is delayed. 

Common errors that compromise results include sampling from drain ports with settled contaminants, using contaminated equipment, exposing samples to air, and sampling during shutdown when oil is not circulating.

Titration procedure

The titration process requires calibrated equipment, fresh standardized KOH reagent, and proper technique to detect the neutralization endpoint accurately. Potentiometric methods use electronic sensors to detect voltage changes at neutralization, whereas color indicator methods rely on visual detection of color shifts from orange to green-brown. 

Procedural errors, such as contaminated glassware, improperly calibrated electrodes, expired reagents, incorrect solvent ratios, and poor mixing, introduce variability that degrades trend reliability and can lead to incorrect maintenance decisions.

Result calculation and documentation

Calculating TAN values from titration data uses this formula: 

TAN = (mL KOH used × Normality of KOH × 56.1) / grams of sample. 

The 56.1 factor converts the result to mg KOH/g units, establishing the standard measurement that maintenance teams track over time. 

A sample calculation is, if 2.5 mL of 0.1 N KOH neutralizes 4.0 grams of oil, then: 

TAN = (2.5 × 0.1 × 56.1) / 4.0 = 3.5 mg KOH/g.

Document results properly by recording the sample source, test date, method used (D664 or D974), and any observations about sample appearance or condition. Note the operating hours of the equipment, any recent maintenance, and environmental conditions (if relevant). This documentation becomes essential for root cause analysis when TAN values change unexpectedly.

Building a trend database requires a consistent recording format and accessible storage. Whether using spreadsheets, lab information systems, or integrated CMMS platforms, the goal is to make historical TAN values easy to retrieve and compare. Trending reveals more than individual readings. A steady increase suggests normal aging, while sudden spikes indicate contamination, overheating, or additive depletion requiring immediate investigation.

Factors That Affect TAN Values

Understanding what drives TAN changes helps distinguish normal oil aging from problems requiring immediate attention.

Multiple factors influence acid formation in lubricating oils, and recognizing their effects prevents unnecessary oil changes while catching real problems early. Establishing baseline TAN values for specific equipment and operating conditions, then watching for deviations, provides more actionable intelligence than relying on generic industry limits.

Oil oxidation

Oil oxidation represents the primary driver of TAN increase in most industrial applications. When lubricant molecules react with oxygen under heat and pressure, they form acidic compounds that directly raise TAN values. 

This process is fundamental to oil aging and happens to some degree in every system, but the rate varies dramatically based on operating conditions and oil formulation.

• Oxygen reaction at elevated temperatures: Oil molecules break down when exposed to oxygen, particularly at temperatures above 60°C (140°F), creating carboxylic acids and other acidic byproducts that accumulate over time.
• Formation of organic acids and peroxides: Oxidation produces not just acids but also peroxide intermediates that further accelerate degradation, creating a self-reinforcing cycle as acids catalyze additional oxidation.
• Temperature acceleration effects: For every 10°C (18°F) increase in operating temperature, oxidation rates roughly double, meaning oil running at 90°C degrades four times faster than oil at 70°C.
• Catalyst effects: Metal wear particles (especially copper and iron) and water contamination act as oxidation catalysts, dramatically accelerating acid formation even when other conditions remain constant.

Contamination sources

External contaminants introduce acids directly into the oil system or accelerate the formation of acids through chemical reactions. Even seemingly clean systems can develop contamination through regular operation, seal degradation, or environmental exposure.

• Water ingress: The most common contaminant, water promotes oxidation reactions and can carry dissolved acids from condensation, process leaks, or atmospheric moisture, making it both a direct acid source and an oxidation accelerator.
• Process chemicals and cross-contamination: Leaking heat exchangers, shared piping, or improper filling procedures can introduce acids from adjacent systems, showing as sudden TAN spikes unrelated to normal oil aging.
• Combustion byproducts: Engine oils face unique challenges from sulfuric and nitric acids formed during combustion, which blow by piston rings and contaminate the crankcase oil.
• Atmospheric acids: Plants in coastal areas or near industrial facilities may see sulfur dioxide and nitrogen oxides dissolve into oil through breathers and vents, creating acid contamination over time.
• Metal wear particles as oxidation catalysts: Iron, copper, and other metal particles generated by normal wear accelerate oxidation by providing catalytic surfaces where acid-forming reactions occur more readily.

Base oil type and formulation

The starting point for TAN monitoring depends heavily on what type of oil is in the system and how it was formulated. Different base oils have inherently different oxidation resistance and natural acidity levels.

• Mineral vs. synthetic oxidation resistance: Synthetic oils (PAO, ester-based) typically resist oxidation better than mineral oils and start with lower baseline TAN values, often 0.01 to 0.3 mg KOH/g, compared to 0.05 to 0.5 mg KOH/g for conventional mineral oils.
• Natural acidity levels by oil type: Some base oils, particularly those derived from naphthenic crude or containing natural esters, have higher initial acidity that must be accounted for when setting action limits.
• Additive package effects on baseline TAN: Certain additives, particularly rust and corrosion inhibitors, are naturally acidic and raise new oil TAN readings, making it essential to establish baseline values for each specific product rather than assuming all oils should start near zero.

Additive depletion

Fresh oil contains antioxidant additives specifically designed to slow acid formation by interrupting oxidation reactions. These additives work by chemically sacrificing themselves, and once depleted, the oil loses its primary defense against acidic degradation.

• Antioxidants sacrifice themselves to protect base oil: Compounds like phenolic and aminic antioxidants intercept oxidation intermediates and neutralize them, but each molecule can only perform this function once before being consumed.
• Depletion causes sudden TAN acceleration: While antioxidants remain active, TAN rises slowly and predictably, but once the additive package is exhausted, acid formation accelerates rapidly as the base oil oxidizes without protection.
• Shows as a TAN spike after a stable period: Trending often reveals months of gradual TAN increase followed by a sharp upturn, signaling that additive depletion has occurred and the oil is approaching end of life.

Operating conditions

The operation of equipment and the effectiveness of maintenance practices in controlling oil condition have a significant impact on TAN development rates. Two identical systems can exhibit dramatically different TAN trajectories solely based on operating parameters and maintenance execution.

• Temperature: The single most critical factor, with higher bulk oil temperatures and localized hot spots (bearings, gear mesh points) driving exponential increases in oxidation and acid formation rates.
• Duty cycle: Continuous-run equipment develops TAN differently than systems with frequent start-stop cycles, as thermal cycling stresses oil molecules and promotes moisture ingress during shutdown periods.
• Load and stress levels: Heavy loads create higher pressures and temperatures at contact points, accelerating localized oxidation and increasing the rate at which acids form in critical areas.
• System cleanliness and filtration: Effective filtration removes oxidation catalysts (metal particles) and contaminants that accelerate TAN increase, while poor filtration allows these materials to circulate and drive acid formation.
• Maintenance practices: Proper breather maintenance prevents moisture and atmospheric contamination, prompt leak repair stops water ingress, and timely seal replacement prevents external contaminant entry, all of which control TAN development rates.

Tractian AI-Powered Oil Analysis Integration

Tractian's CMMS transforms TAN from a periodic lab value into a real-time predictive maintenance trigger that automatically drives work orders and resource allocation.

The gap between knowing TAN values and acting on them disappears when oil condition data flows directly into maintenance workflows. Tractian's platform receives TAN results from lab systems or manual entry, then automatically compares each value against equipment-specific thresholds and trending baselines. When TAN exceeds a warning limit or increases at an abnormal rate, the system generates alerts to the right people and can automatically create work orders with pre-populated equipment history, oil specifications, and recommended actions.

Technicians access current and historical TAN data through mobile interfaces, even when offline, allowing them to review oil condition while standing at the equipment. Maintenance managers see dashboards that display TAN trends across all assets, highlighting which systems are approaching action limits and which can safely extend their current oil life. 

This visibility eliminates the guesswork and manual tracking that typically delays intervention. The platform integrates TAN with other condition monitoring inputs like vibration analysis, thermography, and runtime data to build a comprehensive picture of asset health. 

Rising TAN, combined with increasing bearing temperatures and elevated vibration levels, signals a lubrication problem that requires immediate attention. A stable TAN with normal vibration suggests oil can run longer despite calendar age. By unifying these signals, teams move from siloed data points to coordinated predictive maintenance that catches problems before they escalate into failures.

Benefits of AI-Powered TAN Monitoring

Automated TAN tracking eliminates manual processes, catches degradation earlier, and connects oil condition data directly to maintenance execution.

Execute Your TAN Monitoring Strategy

Successful TAN programs begin with critical equipment, establish baselines, set trend-based limits, and integrate data into CMMS workflows that drive actionable insights.

Implementation follows a phased approach that builds capability progressively while delivering quick wins. The goal is to transition from calendar-based oil changes and reactive failures to condition-based maintenance, which extends oil life safely and identifies problems before they damage equipment.

Phase 1: Establish baseline and scope

This phase focuses on identifying the most critical equipment and understanding the current oil condition under regular operation. The foundation of any TAN program is knowing where you stand today before attempting to track changes over time.

• Select critical equipment where lubrication failures have the highest impact: Prioritize turbines, hydraulic systems, and gearboxes in primary production lines over ancillary equipment. Document the oil type, capacity, operating conditions, and current change intervals for each.
• Define testing methods and frequencies by asset type: Balance testing costs against equipment criticality. Use monthly potentiometric testing for critical assets and quarterly color indicator testing for less critical systems.
• Set initial TAN baselines under normal operating conditions: Sample when equipment runs at typical load and temperature, taking multiple samples over several weeks to account for normal variation and calculate average baseline TAN.
• Identify integration points with existing CMMS and lab systems: Determine whether lab results can flow electronically into maintenance platforms or require manual entry, mapping how TAN data connects to equipment records and work order triggers.

Phase 2: Implement systematic testing

This phase establishes the operational discipline necessary to generate reliable and consistent TAN data. Even the best analytical methods fail without a proper sampling technique and documentation standards.

• Train staff on proper sampling and handling: Ensure technicians understand why sampling at operating temperature matters, how to avoid contamination, and proper labeling and storage procedures.
• Establish lab relationships or in-house testing capability: Choose between commercial labs (certified methods, no equipment investment, longer turnaround) and in-house testing (capital investment, training requirement, faster response).
• Create documentation standards for results: Require every TAN result to include equipment ID, sample date, test method, operator, oil type, equipment hours, and observations about sample appearance or operating conditions.
• Begin trend database development: Build systems to easily retrieve, visualize, and compare historical TAN values, whether using spreadsheets, laboratory information systems, or CMMS platforms.

Phase 3: Set limits and triggers

This phase translates TAN data into maintenance action by defining when intervention is needed and automating response workflows. Limits should reflect equipment-specific reality rather than generic industry guidelines.

• Define action thresholds based on equipment criticality and oil type: Set investigation triggers at 1.0 mg KOH/g increase for critical turbines and 2.0 mg KOH/g for less critical hydraulic systems, adjusting manufacturer recommendations based on actual experience.
• Establish rate-of-change alerts (not just absolute values): Flag abnormal rate increases automatically, as TAN doubling in one month signals problems even if absolute values remain below generic limits.
• Create escalation protocols for sudden TAN increases: Document who investigates the root cause, what additional tests are ordered, and how quickly action must be taken so that the response is consistent regardless of who is on duty.
• Integrate limits into CMMS for automatic work order generation: Eliminate the gap between knowing oil is degraded and scheduling action by automating workflows when TAN thresholds are exceeded.

Phase 4: Integrate with other condition monitoring

This phase builds the complete asset health picture by combining TAN with other condition indicators. Isolated parameters tell incomplete stories, while integrated monitoring reveals cause-and-effect relationships.

• Correlate TAN with viscosity, particle counts, and wear metals: Rising TAN with increasing iron and copper levels indicates active corrosion, while rising TAN with stable viscosity suggests acid formation without oxidation thickening.
• Cross-reference with vibration analysis and thermal imaging: Increasing bearing vibration, combined with rising TAN points, indicates lubrication-related wear, while elevated bearing temperatures with high TAN suggest oil film breakdown.
• Build multi-parameter health models for critical assets: Weight TAN alongside other condition indicators to support better decisions about when to intervene and what action to take.
• Use platforms like Tractian to unify condition monitoring inputs: Enable dashboards where maintenance teams see TAN, vibration, temperature, and other signals in one view for integrated decision-making.

Continue to Optimize

This phase is ongoing and ensures the TAN program delivers measurable value and evolves based on experience. Tracking program effectiveness reveals where thresholds need adjustment and documents return on investment.

• Track TAN prediction accuracy vs. actual failures: Compare TAN-triggered oil changes against later analysis of drained oil to determine if thresholds are too conservative or need tightening.
• Monitor oil change timing optimization: Track how condition-based decisions compare to previous calendar-based intervals, documenting which systems safely extend oil life and which require earlier intervention.
• Measure reduction in lubrication-related failures: Quantify decreases in bearing replacements, seal failures, and hydraulic system rebuilds, along with avoided downtime and repair costs to demonstrate program value.
• Benchmark across similar assets and sites: Identify best practices and outliers by comparing why one gearbox maintains stable TAN while an identical unit shows rapid increases.

Build Reliability Through TAN Monitoring

The shift from reactive to predictive maintenance starts with visibility into problems while they're still manageable. TAN monitoring illuminates chemical degradation before bearings pit, seals leak, or internal corrosion compromises components. When integrated with viscosity, particle counts, wear metals, vibration analysis, and thermal imaging, TAN builds the complete asset health picture that enables confident maintenance decisions. 

Teams distinguish between normal aging and contamination events, plan condition-based oil changes during scheduled windows rather than reacting to failures, and optimize oil life based on actual conditions rather than arbitrary calendar intervals. The business outcomes follow directly from here. Uptime improves, cost control strengthens, asset life extends, and production schedules are maintained when lubrication problems are addressed proactively.

Tractian's CMMS provides the platform that connects monitoring to execution. TAN data integrates with other condition monitoring inputs in unified dashboards, automated workflows trigger alerts and work orders when thresholds are exceeded, and mobile access puts trends in technicians' hands at the point of work. Cross-site visibility enables benchmarking and the identification of best practices. 

The result is a predictive maintenance program where TAN monitoring drives decisions that protect equipment, optimize costs, and deliver measurable improvements in reliability.

Tractian’s execution-first platform empowers teams to anticipate needs, eliminate fire drills, and keep the focus on reliability and results, where it belongs.

Request a demo to see how Tractian can help you make stockouts the rare exception in your facility.

FAQ

What's the difference between TAN and pH for measuring oil acidity?

TAN measures acidity in oils through titration, quantifying the amount of potassium hydroxide required to neutralize the acidic compounds present in the lubricant. pH only works in water-based solutions and provides meaningless results when applied to oil. TAN testing uses specific solvents to dissolve oil samples, then determines the exact mg KOH/g values, which can be trended over time to reveal degradation.

How often should we test TAN for critical equipment?

The testing frequency should match the equipment's criticality and operating severity. Critical turbines typically require monthly TAN testing, while hydraulic systems benefit from testing every one to three months. Less critical equipment can be tested quarterly or semi-annually. Systems operating under high heat, heavy contamination, or extended duty cycles require more frequent monitoring to detect sudden changes that may signal problems.

What TAN values indicate that oil needs to be changed?

Action thresholds depend on the type of oil, the criticality of the equipment, and baseline values, rather than universal limits. The rate of change matters more than the absolute values. Most programs trigger an investigation when the TAN increases from 1.0 to 2.0 mg KOH/g for critical equipment or from 2.0 to 3.0 mg KOH/g for less critical systems. Sudden increases that double TAN in one month signal problems even if absolute values remain moderate.

How does Tractian CMMS integrate TAN data with maintenance workflows?

Tractian automatically compares TAN results against equipment-specific thresholds and trending baselines. When TAN exceeds limits or increases abnormally, the system generates alerts and can automatically create work orders pre-populated with equipment history and recommended actions. Technicians access TAN trends through mobile interfaces while on the floor, and managers view dashboards relevant to manufacturing, food and beverage, mining, mills & agriculture, or automotive manufacturing plants, which display patterns across all assets to identify which systems require attention.

How does Tractian help prevent lubrication-related failures through TAN monitoring?

Tractian turns TAN into an active predictive maintenance trigger by automating the connection between oil condition and maintenance action. The platform trends TAN alongside vibration, thermal, and wear metal analysis, automatically flags abnormal increases before equipment damage occurs, and generates work orders that ensure intervention happens during planned windows. This integrated visibility catches degradation early and optimizes oil change timing based on actual condition.

What other oil analysis parameters should we track alongside TAN with Tractian?

Tractian enables the tracking of viscosity (revealing oil thickening or thinning), particle counts (quantifying wear debris and contamination), wear metals (indicating active equipment wear), water content (revealing moisture that accelerates acid formation), and FTIR oxidation indices (measuring oxidation byproducts). The platform displays these parameters together on unified dashboards, automatically correlates trends, and triggers multi-parameter alerts when combinations signal specific failure modes.