423 Reliability Model for a Dental Glass-Ceramic with Multiple Flaw Populations

Thursday, March 22, 2012: 3:30 p.m. - 4:45 p.m.
Presentation Type: Poster Discussion Session
G.V. JOSHI1, Y. DUAN1, K. ST. JOHN1, T. HILL2, A. DELLA BONA3, and J. GRIGGS1, 1Dept. of Biomedical Materials Science, University of Mississippi Medical Center, Jackson, MS, 2Ivoclar Vivadent, Inc, Amherst, NY, 3University of Passo Fundo, Passo Fundo, RS, Brazil

Dental ceramics suffer from intrinsic, processing, and service flaws. It is desirable to predict the lifetimes of all-ceramic prostheses when multiple flaw types present. Objective: To determine a statistical model for fitting fatigue lifetime data with multiple flaw populations. Method: Rectangular beam specimens of a fluorapatite glass-ceramic (IPS e.max ZirPress, Ivoclar-Vivadent) were fabricated by pressing. The polished specimens (15 μm diamond) were subjected to cyclic loading between 4.5 and 45 MPa at 2 Hz and 10 Hz (N=30 each). Tests were performed using a fully articulating four-point flexure fixture in deionized water at 37˚C. Fractographic techniques were used to identify initial flaw types. The lifetime data were fit to a partially concurrent model (Johnson, 1979). Weibull++ software was used to estimate the parameters of the mixed Weibull model. A power analysis was performed by Monte Carlo simulations using the Simumatic tool of Weibull++ to estimate the appropriate sample size. Results: Fractographic examination revealed that failure originated from surface porosity and grinding flaws. The Weibull moduli for surface porosity and grinding flaw populations are denoted by mp and mg, respectively, while the characteristic lifetimes of surface porosity and grinding flaw populations are denoted by ηp and ηg, respectively. A sample size of 500 specimens per group was estimated to be necessary for tight confidence intervals for a five-parameter Weibull model. The parameters of the mixed Weibull model are summarized as follows:


Fatigue 2 Hz

Fatigue 10 Hz

Weibull modulus





Characteristic lifetime (s)










Conclusion: The fatigue lifetime distribution was dependent on the flaw distribution, and it fit well (KS=0.58%) to a partially concurrent model. The effect of frequency on the model parameters could not be determined due to unfeasible sample size. NIH grants DE013358 and DE017991.


This abstract is based on research that was funded entirely or partially by an outside source: NIH grants DE013358 and DE017991

Keywords: Ceramics and Fatigue, Fractography
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