The appearance of White Etching Cracks (WEC), not covered by the ISO 281 modified failure rate calculation, leads to difficulties in predicting bearing reliability. This uncertainty in bearing applications leads to a worldwide activity in order to understand and prevent this situation since the WEC failure mode deviates from the traditional Rolling Contact Fatigue (RCF) mode. Plenty of factors have been found to influence this phenomenon over the years, however the precise initiation of the WEC is still under debate. In order to understand the initiation and analyze the temporal evolution, interrupted tests on the same material were performed under conditions that were known to lead to WEC formation and RCF. To avoid the added complexity of boundary lubrication, a Deep Groove Ball Bearing (DGBB) test rig under full lubrication (Elastohydrodynamic Lubrication, EHL) was chosen. Within a standard operating mode, named Mode 1 (RCF), the bearings are solely subjected to a radial load. By suspending the tests at different time steps, a continuous progress of changes in the subsurface material structure seen as equiaxed grains with low dislocation densities, identified as ferrite, is observed. The bearings did not fail up to load cycles of 10⁹. In contrast, a Mode 2 Electrical Charged Contact Fatigue (ECCF) test provoked the early formation of cracks and crack networks, first without WEA, then later with WEA. It became obvious when comparing Mode 1 (RCF) with Mode 2 (ECCF) that Mode 2 (ECCF) achieves far fewer load cycles until failure occurs.

An investigation on the White Etching Crack (WEC) phenomenon as a severe damage mode in bearing applications led to the observation that in a latent pre-damage state period, visible alterations appear on the surface of the raceway. A detailed inspection of the microstructure underneath the alterations reveals the existence of plenty of nano-sized pores in a depth range of 80 µm to 200 µm. The depth of the maximum Hertzian stress is calculated to be at 127 µm subsurface. The present study investigates the effect of these nanopores on the fatigue crack initiation in SAE 52100 martensitic hardened bearing steel. In this sense, two micro-models by means of the Finite Element Method (FEM) are developed for both a sample with and a sample without pores. The number of cycles required for the crack initiation for both samples is calculated, using the physical-based Tanaka–Mura model. It is shown that pores reduce the number of cycles in bearing application to come to an earlier transition from microstructural short cracks (MSC) to long crack (LC) propagation significantly.

The reliability of rolling bearings is affected by white etching crack (WEC) or white structure flaking (WSF) failures, causing tremendous commercial burdens for bearing manufacturers and operators. The research for the underlying failure mechanism has attracted interest from a large scientific community over decades. Despite the significant amount of efforts, a root cause of white etching cracking is still missing. Amongst other factors, lubricant chemistry is considered to be essential in WEC formation. The authors aim to elucidate this key parameter by provoking white etching crack formation on a FE8 bearing test rig using a well-described set of chemicals in high- and low-reference lubricants. Scanning electron microscopy and energy dispersive X-ray analysis prove the presence of a patchy tribofilm on the surface of bearing washers, leading most likely to a higher frictional torque at the early stages of operation when the low reference oil is used. Secondary neutral mass spectrometry (SNMS) shows a hydrogen containing tribofilm in the shallow subsurface of about 30 nm depth, suggesting that hydrogen proliferating into bearing material may subsequently facilitate crack propagation via dislocation pileups, leading to premature bearing failure.

White Etching Cracks (WEC) have become a subject of extensive research in material science, chemistry and lubrication, and even operational mathematics by AI learning. Initially reported in the 1960s and considered an exotic anomaly, the failures gained importance with the global rise of wind energy power and the automotive industry. Unexpectedly high failure rates in various bearing applications have led to the need for a deeper understanding and prevention of WEC. It has come a long way from materials inspection, to parametrically studying WECs on test rigs, to the understanding that WEC is a stand-alone phenomenon and sparingly related to common failures in bearing technology. It has been commonly accepted that WEC drivers have multiple dimensions, e.g., material, contact mechanics, chemistry, and electricity. The impact of these factors on WEC failures is frequently studied using test rigs at the component level, such as the FE8 test rig. The FE8 has been utilized in numerous investigations due to its ability to replicate WEC failures without requiring artificial electricity or hydrogen charging by using specific lubricant chemistry and operating conditions. However, through intensive testing, it was observed in this study that a standard material in an FE8 rig component demonstrated a profound influence on WEC formation. This paper presents the details of the testing and analysis, aiming to investigate the mechanisms of interactions between the hose material and the low reference lubricant. The results demonstrate that the chemistry of the component material plays an important role in WEC formation. This finding may have significant impact in WEC studies, especially when the FE8 rig is used.

Novel aspects in drive train lubrication are coming into the focus of future technologies covering new materials, accompagnied by digital and ecological aspects. Cradle to cradle (C2C) and waste to cradle (W2C) are offering broad sources of chemicals derived from greens out of the bio-cycle, obtained by decentralized farming. This leads to the fact, that valuable raw materials are accessible from everywhere. Chemicals derived from the bio-life cycle are in tendence rich in oxygen (nitrogen) and as such polar with a general affinity to water with high degree of sustainability and superior CO2 footprint. Lubricants as been used today in contrast are derivatives of fossils with low oxygen content and low affinity to water, poor in sustainability and CO2 footprint. As all life cycle assessments are based on the current lubrication technology, the efforts are high (low technical readiness level) for assessing bio-life cycle based lubricants with respect to their suitability in the technical life cycle, based on test rigs. However, machine learning (ML) techniques could reveal the relevant chemical predictors that are needed to pass a life cycle test rig. Such predictors are available from numerous test rig results assessing traditional lubricants and could be taken for the prediction of the novel bio-life based chemicals. Such concepts have been published recently (Literature). Novel sensor concepts could assist by early predicting failures. As such, the use of ML is inevitable to predict their usefulness in drive train. Coatings may serve as adjuvants for novel C2C (W2C) based lubrication. So far, to open the gate for bio-life based C2C (W2C) chemistry brings up a stringent need for novel sensor concepts in junction with ML. The upcoming EV drive train technology is reaching out for non water based fluids with high heat capacity and thermal conductivity for the electrical segment on one side and low viscous lubricants for the mechanical part on the other. Novel, ML based technologies in C2C (W2C) chemistry could couple both parts into one, as a vision for decentralized sustainable and low CO2 footprint technologies.