Saltar al contenido
PTI LATAMExplorar Portal
Mantenimiento

Oil Analysis

A predictive maintenance technique that examines samples of lubricating oil from operating machinery to detect: (1) Wear metals — iron, copper, chromium, aluminum, lead particles indicate component wear (spectrometric analysis, particle counting per ISO 4406). (2) Contamination — water content (Karl Fischer titration, max 200 ppm for most systems), dirt/silica (silicon content), fuel dilution, and coolant contamination. (3) Oil condition — viscosity change (ASTM D445), Total Acid Number TAN (oxidation indicator), Total Base Number TBN (depletion of additive package), oxidation, and nitration by FTIR spectroscopy. Trending oil analysis results over time reveals developing problems 2-6 months before failure, allowing planned corrective action rather than emergency repair. Sample correctly: from a turbulent flow point (not the drain), at operating temperature, using clean sample bottles, and at consistent intervals. Standards: ISO 4406 (particle counting), ASTM D6224 (in-service monitoring), and ASTM D7647 (trending). Laboratories: Polaris, TestOil, Wearcheck, Noria. Typical cost: $15-40 per sample — trivial compared to a bearing failure costing $5,000-50,000+ including downtime.

What you need to know

  • A predictive maintenance technique that examines samples of lubricating oil from operating machinery to detect: (1) Wear metals — iron, copper, chromium, aluminum, lead particles indicate component wear (spectrometric analysis, particle counting per ISO 4406).
  • (2) Contamination — water content (Karl Fischer titration, max 200 ppm for most systems), dirt/silica (silicon content), fuel dilution, and coolant contamination.
  • (3) Oil condition — viscosity change (ASTM D445), Total Acid Number TAN (oxidation indicator), Total Base Number TBN (depletion of additive package), oxidation, and nitration by FTIR spectroscopy.
  • Trending oil analysis results over time reveals developing problems 2-6 months before failure, allowing planned corrective action rather than emergency repair.
  • Sample correctly: from a turbulent flow point (not the drain), at operating temperature, using clean sample bottles, and at consistent intervals.

Full definition

Oil analysis is a crucial predictive maintenance technique that involves examining lubricating oil samples from machinery to identify potential issues before they lead to catastrophic failures. This method focuses on three primary areas: wear metals, contamination, and oil condition. Wear metals, such as iron, copper, chromium, aluminum, and lead, are detected through spectrometric analysis and particle counting, following the ISO 4406 standard. The presence of these metals indicates wear and tear of components, providing insights into the health of the machinery. For instance, elevated levels of copper might suggest bearing wear, while high iron levels could indicate gear wear. By monitoring these particles, operators can effectively assess the operational state of machinery and schedule maintenance accordingly.

Contamination is another critical aspect of oil analysis. It encompasses various factors such as water content, dirt, fuel dilution, and coolant contamination. Water contamination is typically measured using Karl Fischer titration, with a maximum acceptable level of 200 ppm for most systems. Dirt and silica can be assessed by analyzing silicon content. Fuel dilution and coolant contamination are also assessed to ensure the integrity of the lubricant. For example, the presence of glycol in the oil could indicate coolant leaks, which may lead to overheating and subsequent component failure if not addressed.

The condition of the oil itself is evaluated through changes in viscosity, Total Acid Number (TAN), and Total Base Number (TBN). Viscosity changes are determined using ASTM D445, while TAN and TBN indicate the state of the oil’s additives and its oxidative stability. An increase in TAN suggests oxidation and a breakdown of the oil, while a decrease in TBN indicates depletion of the additive package. Techniques like FTIR spectroscopy are employed to measure oxidation and nitration levels. By trending these oil analysis results over time, maintenance teams can identify developing problems 2-6 months before they lead to failures, allowing for planned interventions rather than emergency repairs. This proactive approach significantly reduces the risk of costly downtime and repair expenses.

Proper sampling is crucial for accurate oil analysis. Samples should be taken from a turbulent flow point rather than the drain to avoid sediment disturbance. Additionally, samples should be collected at the operating temperature and in clean sample bottles to prevent contamination. Consistent sampling intervals also help in establishing reliable trends. Standards such as ISO 4406 for particle counting, ASTM D6224 for in-service monitoring, and ASTM D7647 for trending provide a framework for effective oil analysis. The typical cost for oil analysis ranges from $15 to $40 per sample, which is minor compared to the potential loss incurred from a single bearing failure, which can exceed $50,000 including downtime.

What you need to know

  • What you need to know: Oil analysis detects wear metals, contaminants, and oil condition to predict machinery failures.
  • Wear metals like iron and copper are measured via spectrometric analysis, indicating component wear.
  • Water contamination should not exceed 200 ppm, assessed using Karl Fischer titration.
  • Oil condition is evaluated through viscosity, TAN, and TBN, following ASTM standards.
  • Trends from oil analysis can reveal issues 2-6 months before actual failures occur.
  • Proper sampling techniques are critical for accurate results; samples should be taken at turbulent flow points.

Industrial applications

  • 1Oil analysis is used in manufacturing plants to monitor the health of hydraulic systems and prevent breakdowns.
  • 2In the automotive industry, it assesses engine oil to detect wear and contamination, thus extending service intervals.
  • 3Power generation facilities utilize oil analysis to maintain the reliability of turbines and generators.
  • 4Marine vessels employ oil analysis to ensure the longevity of propulsion systems and reduce unexpected failures.
  • 5Mining equipment relies on oil analysis to monitor lubricants in harsh operating conditions, preventing costly downtime.

Common mistakes

  • Sampling from the drain rather than a turbulent flow point can lead to inaccurate results.
  • Failing to maintain a consistent sampling interval can obscure trends and delay problem detection.
  • Using unclean sample bottles can contaminate oil samples, skewing analysis results.
  • Neglecting to analyze oil condition metrics such as TAN and TBN may overlook critical oil degradation.
💡

Pro tip

Always label samples with the date, time, and equipment identification to ensure accurate tracking and analysis.

Technical standards

  • ISO 4406 - Standard for the cleanliness of industrial fluids, specifically particle counting.
  • ASTM D6224 - Standard guide for oil analysis and in-service monitoring.
  • ASTM D7647 - Standard guide for trending results in oil analysis.

Suppliers of industrial maintenance in Mexico

Applicable standards

ISO 4406ASTM D445ASTM D6224ASTM D7647