Why a small number of controllable causes drives most downtime — and how to prioritise effectively
The Pareto principle in lubrication management
In most industrial plants, large or small, a recurring pattern can be observed: a limited number of causes tend to dominate failures and downtime. This phenomenon is commonly described by the Pareto principle (often referred to as the 80/20 rule) and is highly relevant to lubrication management.
The exact ratio varies per plant, industry and dataset, but the underlying principle remains the same: a small number of dominant causes typically drives a disproportionate share of failures, downtime and maintenance effort.
By understanding which failure modes have the greatest impact, maintenance teams can improve reliability, reduce labour hours and move closer to the ideal maintenance condition in which assets operate at peak performance: the Optimum Reference State (ORS).
Pareto principle in practice
- A limited number of failure causes typically drives the majority of failure events.
- A relatively small group of machines often accounts for a disproportionate share of total downtime.
These distributions are rarely exactly 80/20, but they are consistently skewed enough to justify focused prioritisation.
The 3 dominant controllable causes of failure in lubricated assets
- Contamination
Analyses of premature bearing failures consistently show that contamination is a significant cause of early failure. Similar mechanisms apply to other lubricated components such as chains and gearboxes.
Dirt, moisture and cleaning agents or the wrong lubricant can enter the contact zone and degrade the lubricant film. Even microscopic particles are sufficient to cause abrasive wear, surface damage and accelerated fatigue.
Because contamination is an external disturbance, it requires specific preventive measures such as effective sealing, cleanliness and controlled lubrication practices.
- Incorrect or insufficient lubrication
In addition to contamination, incorrect lubrication is a dominant and largely controllable cause of premature failure. Industry failure analyses of premature bearing failures indicate that lubrication-related causes account for approximately 40–50% of cases, depending on application and operating conditions.
Incorrect lubrication—whether due to an unsuitable lubricant, incorrect viscosity, over-lubrication or under-lubrication—disrupts the lubrication regime. A lubricant film that is too thin leads to boundary lubrication and adhesive wear, while excessive viscosity increases friction, generates additional heat and accelerates lubricant degradation.
These failures are to a large extent manageable through correct product selection, proper dosing and consistent execution of lubrication tasks.
- Assembly and alignment errors
Assembly and alignment errors occur less frequently than lubrication-related issues but often have a disproportionate impact on component life. Small deviations in bearing fits, shaft alignment or gear meshing increase local contact stresses, reduce effective film thickness and accelerate premature failure.
Pareto perspective on controllable failure mechanisms
Taken together, contamination, lubrication-related issues and assembly/alignment errors represent the largest group of controllable contributors to failures in lubricated assets. This clustering clearly illustrates the practical relevance of Pareto thinking in maintenance and reliability engineering.
Fatigue remains a significant failure mechanism, but it is typically the end result of underlying lubrication, contamination or loading issues. For this reason, fatigue is treated here primarily as an outcome rather than a direct maintenance lever.
By focusing on the limited number of dominant, controllable failure mechanisms, maintenance teams can address a disproportionate share of reliability problems—an applied and realistic interpretation of the Pareto principle in lubrication management.
How to identify the 20% in your plant
Recognising the few causes that create most of the problems is the real power of the Pareto principle. In practice, this can be done without complex condition monitoring. Maintenance teams can take a structured approach based on:
- Analyse maintenance logs and downtime records
– Which assets fail more often than average or cause disproportionate downtime?
– Recurring issues (e.g. chains stretching quickly, gearboxes leaking, or bearings failing too early) usually point to the critical few. - Use (or apply) an asset criticality classification
– Many plants already have a criticality ranking in place. Use it to quickly shortlist the “vital few” assets that are most critical to safety, production reliability and cost.
– If no classification exists, a simple ABC ranking (high/medium/low criticality) is often enough to identify the initial 20%. - Cluster failure modes
– Group failures into categories: contamination, lubrication issues, assembly/alignment, overload, corrosion, etc.
– In most plants, two or three categories explain the majority of failures. - Conduct a baseline assessment
– A structured review of lubrication practices, product selection and routes creates an objective picture of risks.
– A baseline assessment quickly shows where lubrication points are over- or under-serviced, which products are unsuitable, and where contamination risks are highest. - Use ILAC™ lubrication management software to manage priorities
– Once the baseline is established, ILAC™ could help visualise which lubrication points consume the most time, pose the highest risk or are critical to production reliability.
Applied to different components
| Components | Main risks | Approach |
|---|---|---|
| Bearings | Contamination and boundary lubrication | Seal integrity, condition monitoring (vibration, oil analysis), lubricants that maintain a stable film |
| Chains | Contamination, Prevent over- or under-lubrication | Minimal Quantity Lubrication (MQL) with penetrating lubricants |
| Gearboxes | Oil oxidation**, leakage, particle contamination | Semi-fluid greases to prevent leakage and extend service life |
* How to prevent over- or under-lubrication
** Oxidation vs thermal degradation in lubricants, causes, effects and how to control them
Why targeted lubrication pays off
The Pareto principle shows that maintenance teams do not need to do more, but smarter. Key to this is:
- Standardisation and control → lubrication points, tagging, routes, frequencies and responsibilities are defined, documented and maintained in lubrication management software such as ILAC®, creating consistency, traceability and control, supported on the shop floor by 6S principles.
- Precision lubrication → MicPol® technology strengthens the lubricant film and bonds to surfaces, supporting reliable performance under load, moisture and cleaning
- Strategic maintenance → LaaS®(Lubrication as a Service) aligns lubrication with ORS
- Structured lubrication management → in line with ICML 55 principles
Impact on labour time, energy and costs
With staff shortages, every hour counts. By addressing the critical causes:
- emergency interventions decrease
- teams gain back dozens of hours per month
- more capacity becomes available for planned work
In addition, precision lubrication often delivers 3–8% energy savings on selected drives, directly measurable in kWh and CO₂ reduction.
Conclusion
The Pareto principle shows that a limited number of dominant, controllable causes—most notably contamination, lubrication-related issues and assembly errors—drive a disproportionate share of failures in bearings, chains and gearboxes.
By focusing on these and working in line with the principles of the Optimum Reference State (ORS), maintenance teams achieve greater reliability, lower costs and more effective use of scarce labour capacity.
Want to know where the 80/20 opportunities lie in your plant?
Contact us and book an appointment with one of our technical advisors.
Sources:
Based on industry failure analyses and established reliability engineering practice, including SKF bearing failure classifications and lubrication reliability literature. Percentages are indicative and vary by application and conditions.
Author: Janneke van der Pol, MLT1
Frequently Asked Questions
Yes. Identifying the dominant causes of downtime typically reduces workload rather than increasing it. The Pareto principle helps maintenance teams focus on issues with the highest impact, instead of spreading effort across many low-impact tasks.
In practice, identifying the critical 20% is often straightforward when existing data such as maintenance logs, failure history or downtime records is used. A structured baseline assessment can accelerate this process. The result is fewer emergency interventions, lower reactive workload and more capacity for planned maintenance. An initial time investment usually pays back quickly.
The dominant causes are usually visible in recurring failure patterns. Typical indicators include bearings failing earlier than expected, chains requiring frequent adjustment or replacement, or gearboxes repeatedly leaking or overheating.
By reviewing maintenance logs, failure reports and oil analysis data together, assets and failure modes that consume disproportionate time and attention become clear. Grouping these issues into failure categories (such as contamination, lubrication issues or alignment errors) helps confirm priorities. A baseline assessment can validate these findings and provide objective data for action.
The Optimum Reference State (ORS) describes the target maintenance condition in which an asset operates as reliably and efficiently as possible. It represents a practical benchmark rather than a theoretical ideal.
In the ORS, the correct lubricant is selected, applied in the correct quantity and manner, and protected from contamination. Proper assembly, alignment and process control are also in place. For maintenance teams, ORS provides a clear reference point: fewer failures, longer component life and greater control over time, costs and reliability.