Accelerating aging failures in MEMS devices

Tanner, Darren; Walraven, Jeremy A.; Dugger, Michael Thomas; Parson, Ted B.; Candelaria, S.A.; Jenkins, Mark W.; Corwin, Alex D.; Ohlhausen, James Anthony; Huffman, Elizabeth M.

doi:10.1109/relphy.2005.1493105

Cited by 8 publications

(9 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Note 5: The degradation of MEMS fabricated with the same micro-fabrication process does not evolve in the same way. This supports the idea of applying the PHM of MEMS rather than the predictive reliability (see the works of [8] and [9] about the predictive reliability for MEMS devices). summarizes the values of the displacement at the beginning and at the end of each campaign of test.…”

Section: Notesupporting

confidence: 75%

Experimental monitoring data for prognostics and health management of MEMS

Skima¹,

Medjaher

Varnier³

et al. 2017

2017 4th International Conference on Control, Decision and Information Technologies (CoDIT)

View full text Add to dashboard Cite

This paper presents the data acquisition step of a Prognostics and Health Management (PHM) of Micro-Electro-Mechanical Systems (MEMS) application. The targeted MEMS device is an electro-thermally actuated MEMS valve. The data acquisition is performed during the accelerated lifetime tests. To perform tests, an experimental test bed is designed and built. Several test campaigns are performed where MEMS valves operated continuously and data acquired regularly. The obtained experimental results show that MEMS fabricated with the same micro-fabrication process and tested in the same conditions do not have the same behavior and the same evolution of degradation in time. Therefore, this supports the importance of applying PHM of MEMS rather than the predictive reliability.

show abstract

Section: Notesupporting

confidence: 75%

Experimental monitoring data for prognostics and health management of MEMS

Skima¹,

Medjaher

Varnier³

et al. 2017

2017 4th International Conference on Control, Decision and Information Technologies (CoDIT)

View full text Add to dashboard Cite

show abstract

“…Despite the fact that lower temperatures and lower humidity levels result in longer life of MEMS [22], some authors question the reliability of accelerated testing in the case of MEMS, pointing only to humidity as the major factor accelerating the most of mechanical and electrical failures [23]. Such point of view can be proved by the results of a natural aging simulated by storing MEMS accelerometers at higher temperatures, when only small changes in their performance were reported in [24,25].…”

Section: Introductionmentioning

confidence: 99%

Selected Aging Effects in Triaxial MEMS Accelerometers

2019

View full text Add to dashboard Cite

Natural aging of commercial triaxial low-g MEMS accelerometers, manufactured by surface micromachining, was evaluated in terms of changes of their offset voltages and scale factors, assigned to each sensitive axis. Two pieces of two models of triaxial accelerometers (ADXL 330 and ADXL 327 by Analog Devices Inc.) with analog outputs were tested within a period of ca. 4.5 years. Two different computer-controlled test rigs were used for performing relevant experimental studies, employing tilt angles as the reference source. Methodology of determining the proposed indicators of aging was based on cyclic repetition of the calibration procedure for each accelerometer. Changes of the output signals of the tested accelerometers were observed, resulting in respective indication errors of ca. 0.8% or even 2.2% while related to determining tilt. Since the accelerometers were operated under mild conditions while tested, much bigger errors are to be expected in the case of harsh conditions. Both pieces of ADXL 330 accelerometers ceased to operate properly within the testing period, approximately at the same time, for no apparent reason; thus, it is recommended to introduce redundancy in relevant reliable measuring circuits by doubling the number of the applied accelerometers.

show abstract

“…The most successful Class III device has been the Texas Instrument DLP TM technology with micro-mirror arrays. Although the Class IV devices have considerable reliability issues with rubbing surfaces [3,4], there are many possibilities for interesting applications.…”

Section: Introductionmentioning

confidence: 99%

Science-based MEMS reliability methodology

Tanner

Parson

Corwin

et al. 2007

Microelectronics Reliability

Self Cite

View full text Add to dashboard Cite

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 lm) 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.

show abstract

Accelerating aging failures in MEMS devices

Cited by 8 publications

References 10 publications

Experimental monitoring data for prognostics and health management of MEMS

Experimental monitoring data for prognostics and health management of MEMS

Selected Aging Effects in Triaxial MEMS Accelerometers

Science-based MEMS reliability methodology

Contact Info

Product

Resources

About