2024-03-29T05:13:04Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/2303332022-08-20T04:30:45Zcom_10261_90com_10261_4col_10261_343
2021-02-22T12:51:21Z
urn:hdl:10261/230333
Yield-aware multi-objective optimization of a MEMS accelerometer system using QMC-based methodologies
Pak, Murat
Fernández, Francisco V.
Dundar, Gunhan
This paper proposes a novel yield-aware optimization methodology that can be used for mixed-domain synthesis of robust micro-electro-mechanical systems (MEMS). The robust Pareto front optimization of a MEMS accelerometer system, which includes a capacitive MEMS sensor and an analog read-out circuitry, is realized by co-optimization of the mixed-domain system where the sensor performances are evaluated using highly accurate analytical models and the circuit level simulations are carried out by an electrical simulator. Two different approaches for yield-aware optimization have been implemented in the synthesis loop. The Quasi Monte Carlo (QMC) technique has been used to embed the variation effects into the optimization loop. The results for both two- and three-dimensional yield-aware optimization are quite promising for robust MEMS accelerometer synthesis.
2021-02-22T12:51:21Z
2021-02-22T12:51:21Z
2020
2021-02-22T12:51:22Z
artículo
MICROELECTRONICS JOURNAL 103 (2020)
http://hdl.handle.net/10261/230333
10.1016/j.mejo.2020.104876
Postprint
http://dx.doi.org/10.1016/j.mejo.2020.104876
Sí
openAccess
Elsevier