Int. J. Simul. Multidisci. Des. Optim.
Volume 13, 2022
Simulation and Optimization for Industry 4.0
|Number of page(s)||15|
|Published online||23 December 2022|
Multi objective design optimization of graphene piezoresistive MEMS pressure sensor using design of experiment
School of Engineering and Technology, Poornima University Jaipur, Jaipur, India
2 Department of Mechanical Engineering, Poornima Institute of Engineering and Technology − Jaipur, Jaipur, India
3 Department of Mechatronics Engineering, Manipal University Jaipur, Jaipur, India
* e-mail: email@example.com
Accepted: 18 November 2022
This paper investigates the effect of diaphragm thickness, dimensions of piezoresistors, doping profile and temperature compatibility on sensitivity and non-linearity of graphene MEMS pressure sensor. Taguchi method is used for maximizing the sensitivity and minimizing the nonlinearity of the designed pressure sensor. L27 orthogonal array is utilized for five input factors with three levels. Output voltage is obtained from simulation in COMSOL for different combinations of the input parameters as per L27 orthogonal array. It was found that diaphragm thickness and length of the sensing element shows maximum contribution in increasing the sensitivity of the pressure sensor. Similarly, interaction of diaphragm thickness with piezoresistors thickness and doping concentration shows a major contribution in reducing the non-linearity of the pressure sensor. Other factors such as operating temperature affects both sensitivity and nonlinearity of the pressure sensor with a very low contributing percentage of 0.40% and 2.16%, respectively. Pareto Analysis of variance (ANOVA) was employed to validate the predicated results of the designed pressure sensor. The result indicated that the optimum design shows a sensitivity of 4.10 mV/psi with very low non linearity of 0.1%.
Key words: Optimization / piezoresistive / pressure sensor / taguchi / pareto analysis / sensitivity / graphene
© M. Nag et al., Published by EDP Sciences, 2022
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