Multi-response optimization of electrothermal micromirror using desirability function-based response surface methodology

7Citations
Citations of this article
14Readers
Mendeley users who have this article in their library.

Abstract

The design of a micromirror for biomedical applications requires multiple output responses to be optimized, given a set of performance parameters and constraints. This paper presents the parametric design optimization of an electrothermally actuated micromirror for the deflection angle, input power, and micromirror temperature rise from the ambient for Optical Coherence Tomography (OCT) system. Initially, a screening design matrix based on the Design of Experiments (DOE) technique is developed and the corresponding output responses are obtained using coupled structural-thermal-electric Finite Element Modeling (FEM). The interaction between the significant design factors is analyzed by developing Response Surface Models (RSM) for the output responses. The output responses are optimized by combining the individual responses into a composite function using desirability function approach. A downhill simplex method, based on the heuristic search algorithm, is implemented on the RSM models to find the optimal levels of the design factors. The predicted values of output responses obtained using multi-response optimization are verified by the FEM simulations.

References Powered by Scopus

A Test of Goodness of Fit

1751Citations
533Readers
Get full text
Get full text
458Citations
114Readers
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Saleem, M. M., Farooq, U., Izhar, U., & Khan, U. S. (2017). Multi-response optimization of electrothermal micromirror using desirability function-based response surface methodology. Micromachines, 8(4). https://doi.org/10.3390/mi8040107

Readers over time

‘17‘18‘19‘20‘21‘22‘2301234

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 4

44%

Lecturer / Post doc 2

22%

Researcher 2

22%

Professor / Associate Prof. 1

11%

Readers' Discipline

Tooltip

Engineering 6

67%

Decision Sciences 1

11%

Design 1

11%

Computer Science 1

11%

Save time finding and organizing research with Mendeley

Sign up for free
0