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BioMed Research International
Volume 2016, Article ID 8927156, 8 pages
Research Article

Long-Term Fatigue and Its Probability of Failure Applied to Dental Implants

1Department of Medicine and Surgery (Stomatology Area), Rey Juan Carlos University, C/ Tulipán s/n, Móstoles, 28933 Madrid, Spain
2Applied Modelling and Instrumentation Group, Aragón Institute of Engineering Research, University of Zaragoza, C/ Mariano Esquillor s/n, 50018 Zaragoza, Spain
3Biotecnos Research Center, Rua Dr. Bozano 571, 97015-001 Santa Maria, RS, Brazil
4University Catholic San Antonio de Murcia (UCAM), Guadalupe, 30107 Murcia, Spain
5Oral Medicine, University of Murcia, 30001 Murcia, Spain
6International Dental Research Cathedra, Faculty of Medicine and Dentistry, University Catholic San Antonio de Murcia (UCAM), Guadalupe, 30107 Murcia, Spain

Received 13 April 2016; Revised 16 June 2016; Accepted 22 June 2016

Academic Editor: Christiane Kunert-Keil

Copyright © 2016 María Prados-Privado et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


It is well known that dental implants have a high success rate but even so, there are a lot of factors that can cause dental implants failure. Fatigue is very sensitive to many variables involved in this phenomenon. This paper takes a close look at fatigue analysis and explains a new method to study fatigue from a probabilistic point of view, based on a cumulative damage model and probabilistic finite elements, with the goal of obtaining the expected life and the probability of failure. Two different dental implants were analysed. The model simulated a load of 178 N applied with an angle of 0°, 15°, and 20° and a force of 489 N with the same angles. Von Mises stress distribution was evaluated and once the methodology proposed here was used, the statistic of the fatigue life and the probability cumulative function were obtained. This function allows us to relate each cycle life with its probability of failure. Cylindrical implant has a worst behaviour under the same loading force compared to the conical implant analysed here. Methodology employed in the present study provides very accuracy results because all possible uncertainties have been taken in mind from the beginning.