With the development of the Generalized Bearing Life Model (GBLM), SKF customers and distributors can be sure they choose the right bearing for the right application, every time.
Until now, it has been difficult for engineers to predict whether a hybrid bearing will outperform a steel one in an application, or whether the possible performance benefits that hybrid bearings enable are worth the extra investment required. The conventional equations engineers use to calculate the rating life of a bearing don’t reflect the real-world performance of hybrid designs.
To address this issue, in 2012 engineers at SKF started to develop what would become GBLM. A primary version of the model was presented at Hannover Messe in 2015, but at this stage the model was not ready to perform calculations for hybrid bearings. Four additional years were needed by scientists and technicians at SKF’s facilities in the Netherlands and Austria to incorporate this feature into GBLM.
Using GBLM, SKF engineers have been able to determine the real-world benefits hybrid bearings can have. In the case of a poorly lubricated pump bearing, for instance, the rating life of a hybrid bearing can be up to 8x that of a steel equivalent. For a screw compressor bearing running with contaminated lubricant, meanwhile, the hybrid offers a rating lifetime 100x greater than a conventional steel bearing.
"SKF has always been at the forefront of developing new methods for calculating bearing life," says Guillermo Morales-Espejel, principal scientist at SKF Research and Technology Development. "GBLM is a giant leap for bearing science and will enable better choices to be made when selecting bearings for a wide variety of applications."
Through SKF Bearing Select, this capability is available to SKF customers and distributers. SKF Bearing Select can be used to model hybrid deep-groove ball bearings, and hybrid cylindrical roller bearings.
More advanced calculations are available in SKF internal calculation tools to support application engineers in customer projects.