Oil analysis for more accurate predictive maintenance

Oil analysis enables technical teams and industrial operations to identify wear, contamination and changes in lubricant condition, supporting more confident maintenance decisions.

Reduce unplanned failures

Move beyond fixed oil change intervals

Receive clear, actionable technical reports

When preventive maintenance is no longer enough

Many operations still rely on:

Oil changes scheduled by routine rather than actual condition

Limited use of available technical data

Difficulty in anticipating failures with greater accuracy

Corrective maintenance still affecting critical assets

Limited integration between diagnostics and decision-making

Unnecessary oil waste due to routine-based changes

The result: less predictability and greater reliance on corrective maintenance.

What oil analysis reveals about equipment condition

Condition of the lubricant in use

Contamination by particles, water or other agents

Signs of internal wear

Oil
degradation

Trends in asset behaviour over time

How oil analysis strengthens predictive maintenance

Predictive maintenance relies on the ability to identify changes before they turn into failures, performance losses or operational disruptions. In this context, oil analysis serves as a valuable source of data, enabling more technical and reliable decision-making.

A technical foundation for more confident decisions

International standards

Consistent technical methodology

Clear, actionable reports

Specialist support

Analytical depth for demanding industrial environments

Types of oil analysis

Lubricant condition

Contamination

Metal wear

Oil degradation

Trend analysis

Greater technical depth to support decisions based on the actual condition of the asset.

With oil analysis, your operation gains:

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Greater predictability

Plan interventions with greater confidence.

Fewer unplanned failures

Identify deviations before downtime occurs.

Less corrective maintenance

Act before issues escalate.

Better use of lubricants

Move beyond fixed change intervals.

Longer asset lifespan

Protect components and reduce premature wear.

Measurable ESG impact

Reduce your environmental footprint by minimizing waste disposal

Where oil analysis delivers the most value

Automotive

Metallurgy and machining

Energy and utilities

Logistics and heavy transport

Chemical industry

Why ALS is a trusted partner in oil analysis

Why ALS is a trusted partner in oil analysis

The difference lies in the ability to deliver analytical depth, methodological consistency, and results that genuinely support industrial decision-making.

ALS supports companies that need:

Global expertise in fluid analysis

  • Technical and actionable reports
  • Specialist support for complex industrial environments
  • Practical insight into reliability and performance
  • A data-driven approach focused on predictability and decision-making

Sustainability as an operational result

Turn maintenance efficiency into measurable environmental gains.

Minimize waste by safely extending oil change intervals based on actual condition.

Prevent environmental risks through early detection of failures and potential leaks.

Support ESG targets with documented technical reports for environmental compliance.

Improve energy efficiency and reduce your carbon footprint with optimized lubrication.

Case Study

Early diagnosis prevented critical failure in a Komatsu 930E engine

Through predictive monitoring, it was possible to detect the passage of diesel to the crankcase. Through fluid analysis, ALS promotes predictive maintenance to prevent damage and inconvenience to your equipment.

Cost avoided:

80%

Savings:

€ 158.472

Issue detected before failure

Monitoring identified diesel ingress into the crankcase.

Want to achieve similar savings in your operation?

Greater predictability, more control and more precise technical decisions

If your company is looking for greater analytical depth, improved predictability and better use of maintenance data, oil analysis could be the next step.

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