Abstract
In cases where device numbers are limited, large statistical studies to verify reliability are impractical. Instead, an approach incorporating a solid base of modelling, simulation, and material science into a standard reliability methodology makes more sense and leads to a science-based reliability methodology. The basic reliability method is (a) design, model and fabricate, (b) test structures and devices, (c) identify failure modes and mechanisms, (d) develop predictive reliability models (accelerated aging), and (e) develop qualification methods. At various points in these steps technical data is required on MEMS material properties (residual stress, fracture strength, fatigue, etc.), MEMS surface characterization (stiction, friction, adhesion, role of coatings, etc.) or MEMS modelling and simulation (finite element, analysis, uncertainty analysis, etc.). This methodology is discussed as it relates to reliability testing of a micro-mirror array consisting of 144-piston mirrors. In this case, 140 mirrors were cycled full stroke (1.5 μm) 26 billion times with no failure. Using our technical science base, fatigue of the springs was eliminated as a mechanism of concern. Eliminating this wear-out mechanism allowed use of the exponential statistical model to predict lower bound confidence levels for failure rate in a “no-fail” condition.
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