The needs of understanding stochastic fatigue failure for the automobile crankshaft: A review. (October 2017)

• Record Type: Journal Article
• Authors: Singh, S.S.K.; Abdullah, S.; Nikabdullah, N.
• Is Part Of: Engineering failure analysis. Volume 80(2017)
• Page Start: 464
• Page End: 471
• Publication Date: 2017-10
• Subjects: Failure -- Fatigue -- Stochastic -- Crankshaft -- Durability; System failures (Engineering) -- Periodicals; Fracture mechanics -- Periodicals; Reliability (Engineering) -- Periodicals; Pannes -- Périodiques; Rupture, Mécanique de la -- Périodiques; Fiabilité -- Périodiques; Fracture mechanics; Reliability (Engineering); System failures (Engineering); Periodicals; Electronic journals; 620.112
• DOI: 10.1016/j.engfailanal.2017.06.023
• Languages: English
• ISSNs: 1350-6307

Abstract

Abstract: This paper reviews the fatigue failure mechanisms for the automobile crankshaft under service loading through the stochastic point of view. Fatigue failure of crankshafts are reviewed in general, as it is a major concern due to the uncertainties that arise i.e. randomness in structural materials, the geometric shape of the component and randomness of service loads. There has been very little research carried out in assessing the fatigue failure using the stochastic process in predicting the fatigue life of crankshafts. This review paper discusses the durability aspects of the component and is followed by a review of the characteristics of loading and the stochastic fatigue failure effect on the components. In addition, the stochastic approach from empirical model aspect using a safe-life approach from the more recent advances in computational methods to assess stochastic fatigue failure was discussed and reviewed in the context of this paper. The integration between the empirical and probabilistic methods can be quantified using statistical models, which evaluate the damage that leads to fatigue and eventually fatigue failure. Hence, this review provides a platform for understanding the stochastic fatigue failure for an accurate predictive prediction on the structural integrity of components, especially in the automobile industry. Highlights: The characteristics of loading and the stochastic fatigue failure are discussed in this paper. The strain-life methods were used for durability assessment. Combination of probabilistic and statistical with based assessment offer an accurate result.