The state of the art

Published:  10 September, 2015

The way bearings are used, designed and manufactured is changing. PWE takes a look at SKF’s have new Generalised Bearing Life Model. The new model uses the same statistical approach as its standard model, and predicts sub-surface fatigue in the same way, but it also includes separate consideration for surface failure modes.

For the past 30 years, engineers have used a mathematical model to calculate the expected life of bearings in different applications. Originally developed by SKF, and subsequently standardised in ISO 281:2007, the normal Bearing Life Model predicts the likely lifetime of bearings based on the applied loads, operating speeds and working conditions.

The standard bearing life rating model was built on decades of research into metal fatigue under cyclic loads. It uses estimates of the accumulation of fatigue damage in the body of the bearing (known as sub-surface fatigue) and translates those estimates into a likely survival time for the bearing as a whole. As sub-microscopic differences in the composition and structure of their materials mean no two bearings are exactly the same, the model takes a probabilistic approach, using an asymmetric distribution known as the Weibull function to estimate the time at which 90% of the bearings in a sample could expect to remain intact.

The standard bearing life model has proved simple, reliable and effective, but changes in the way machinery is designed and the way bearings are made, are revealing limits to the approach. To understand why, you need to look at how bearings actually fail.

Surface detail

Bearings can lead tough and varied lives. They can be exposed to high temperatures, deprived of lubrication, contaminated with water or grit, shocked, and shaken. All those factors will contribute to damage and wear, ultimately determining the life of the bearing, but that damage accumulates in different ways.

While sub-surface fatigue – the main effect considered in the standard bearing life model – affects a relatively large volume within the body of the bearing, other factors, such as contamination or inadequate lubrication, tend to affect a much thinner area comprising the microscopic irregularities at the surface of the bearing and the material up to 20m below that surface. When engineers and materials scientists look at the different sorts of failure occurring in real life applications and laboratory tests, they find that surface and sub-surface damage occur largely independently of one another. The relative importance of each varies depending on the precise combination of operating conditions to which a bearing is exposed.

While the standard model does attempt to take account of some surface-related issues, by incorporating a ‘stress concentration’ factor to represent the effects of poor lubrication or contamination, this approach is insufficient to represent the subtle and varied sources of damage at the surface.

Moreover, a combination of factors means that surface damage is becoming an increasingly important factor in determining the service life of modern bearings. On the one hand, that’s because bearings themselves have improved so much. Understanding the role of sub-surface fatigue, manufacturers such as SKF have improved the cleanliness and consistency of their bearing steels over the years, greatly reducing the occurrence of impurities that can contribute to fatigue and extending the fatigue life of their products significantly. On the other hand, the drive for reduced costs, increased efficiency, less maintenance and greater productivity has led the designers of machinery to increasingly specify smaller, faster running bearings in their applications – and operate them under precisely the conditions that are hardest on the bearing surface.


Those changes matter, for two different reasons. First, machinery designers and operators are more likely to find that bearings fail due to surface problems, so the standard model is less useful in predicting the actual life of the bearings they specify. Second, bearing manufacturers understand the changing nature of bearing failure and have invested significant R&D effort in strategies to cope, including material formulations and surface treatments designed to improve the performance and longevity of their products in poorly lubricated or contaminated environments. The challenge for them is that, because these changes don’t specifically address the fatigue performance of the bearing, the benefits they offer aren’t predicted by the standard bearing life model, making those advantages harder to sell.


Materials scientists at SKF have developed a brand new model, called the Generalised Bearing Life Model. The new model uses the same statistical approach as the standard model, and predicts sub-surface fatigue in the same way, but it also includes separate consideration for surface failure modes. To do this, the generalised model includes two new groups of performance parameters. The first of these are stress modifiers, to account for effects like poor lubrication, contamination, vibration or acceleration. The second group of parameters is strength modifiers, which account for a range of issues, including material quality, hardness and microstructure design, the effects of corrosion and temperature, and for deliberate attempts to improve surface performance, such as coatings or chemical additives.

SKF’s engineers have developed the current version of the new model using tribological models of bearing surface behaviour under different operating conditions, and validated their models through extensive laboratory testing with large groups of bearings. Today’s most advanced tribological models only consider some of the possible stress and strength modifiers, however, and further research and experimentation will be required before others are fully understood. In respect of this, the generalised model has extensibility built into its design. The construction of the model allows new parameters to be incorporated as necessary, allowing life prediction to keep up with advances in bearing technology and materials science.

Use of weapons

To see how the generalised model works in practice, look at its application to a specific bearing, an SKF Explorer self-aligning roller bearing that has been upgraded to cope with difficult surface conditions. Comparing the expected life of this bearing with that of a conventional SKF bearing in conditions of poor lubrication and high contamination, the standard model predicts they will have nearly the same service life. The generalised model on the other hand, which accounts for the specific changes in the design of the bearing surface, suggests that the user might actually expect a service life about 1.4 times longer (see table, below). The Sr (Surface Risk) number of 0.99 in these results indicates that damage is almost exclusively to the surface in this operating condition.

For comparison, if the model inputs are adjusted to represent a clean, well-lubricated environment, the two models suggest a very similar service life. In addition, the improved Explorer bearing offers less advantage over a standard unit in these conditions, where its improved surface characteristics are less important (Sr=0.03).

To make their work available to the wider engineering community, a team of SKF materials scientists and engineers has published full details of the new Generalised Bearing Life Model in the journal Tribology Transactions . SKF told PWE that while the publication of the new model represents the culmination of many years of work, this is only the start of a new journey for the approach. Bearing design and materials science will continue to evolve, and engineers finally have a life prediction model that can evolve alongside them.


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