Wear Mechanisms in a Reliability Methodology

Abstract

The main thrust in any reliability work is identifying failure modes and mechanisms. This is especially true for the new technology of MicroElectroMechanical Systems (MEMS). The methods are sometimes just as important as the results achieved. This paper will review some of the methods developed specifically for MEMS. Our methodology uses statistical characterization and testing of complex MEMS devices to help us identify dominant failure modes. We strive to determine the root cause of each failure mode and to gain a fundamental understanding of that mechanism. Test structures designed to be sensitive to a particular failure mechanism are typically used to gain understanding. The development of predictive models follows from this basic understanding. This paper will focus on the failure mechanism of wear and how our methodology was exercised to provide a predictive model. The MEMS device stressed in these studies was a Sandia-developed microengine with orthogonal electrostatic linear actuators connected to a gear on a hub. The dominant failure mechanism was wear in the sliding/contacting regions. A sliding beam-on-post test structure was also used to measure friction coefficients and wear morphology for different surface coatings and environments. Results show that a predictive model of failure-time as a function of drive frequency based on wear fits the functional form of the reliability data quite well, and demonstrates the benefit of a fundamental understanding of wear. The results also show that while debris of similar chemistry and morphology was created in the two types of devices, the dependence of debris generation on the operating environment was entirely different. The differences are discussed in terms of wear maps for ceramics, and the mechanical and thermal contact conditions in each device.