Mechanical design of MEMS requires the ability to predict the strength of load-carrying components with stress concentrations. The majority of these microdevices are made of brittle materials such as polysilicon, which exhibit higher fracture strengths when smaller volumes or areas are involved. A review of the literature shows that the fracture strength of polysilicon increases as tensile specimens get smaller. Very limited results show that fracture strengths at stress concentrations are larger. This paper examines the capability of Weibull statistics to predict such localized strengths and proposes a methodology for design. Fracture loads were measured for three shapes of polysilicon tensile specimens - with uniform cross-section, with a central hole, and with symmetric double notches. All specimens were 3.5 mu m thick with gross widths of either 20 or 50 mu m. A total of 226 measurements were made to generate statistically significant information. Local stresses were computed at the stress concentrations, and the fracture strengths there were approximately 90% larger than would be predicted if there were no size effect (2600 MPa versus 1400 MPa). Predictions based on mean values are inadequate, but Weibull statistics are quite successful. One can predict the fracture strength of the four shapes with stress concentrations to within +or-10% from the fracture strengths of the smooth uniaxial specimens. The specimens and test methods are described and the Weibull approach is reviewed and summarized. The CARES/Life probabilistic reliability program developed by NASA and a finite element analysis of the stress concentrations are required for complete analysis. Incorporating all this into a design methodology shows that one can take "baseline" material properties from uniaxial tensile tests and predict the overall strength of complicated components. This is commensurate with traditional mechanical design, but with the addition of Weibull statistics

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The use of Hertzian indentation to measure ring crack initiation force (RCIF) distributions in four hot‐pressed silicon carbide (SiC) ceramics is described. Three diamond indenter diameters were used with each SiC; the RCIF in each test was identified with the aid of an acoustic emission system; and two‐parameter Weibull RCIF distributions were determined for all 12 combinations. RCIF testing was found to be an effective discriminator of contact damage initiation and response. It consistently produced the same ranking of RCIF between the four SiCs, with all three different indenter diameters, which is noteworthy because Knoop hardness and fracture toughness measurements were only subtly different or equivalent for the four SiCs. However, because RCIF, like hardness, is a characteristic response of a target material to an applied indentation condition (e.g., a function of indenter diameter) and not a material property, the implications and possible limitations should be acknowledged when using RCIF to discriminate the target material response.

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A methodology is shown for predicting the time-dependent reliability (probability of survival) of ceramic components against catastrophic rupture when subjected to thermal and mechanical cyclic loads. This methodology is based on the Weibull distribution to model stochastic strength and a power law that models subcritical crack growth. Changes in material response that can occur with temperature or time (i.e. changing fatigue and Weibull parameters with temperature or time) are accommodated by segmenting a cycle into discrete time increments. Material properties are assumed to be constant within an increment, but can vary between increments. This capability has been added to the NASA CARES/Life (Ceramic Analysis and Reliability Evaluation of Structures/Life) code. The code has been modified to have the ability to interface with commercially available finite element analysis codes such as ANSYS executed for transient load histories. Examples are provided to demonstrate the features of the methodology as implemented in the CARES/Life program.

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