Evolutionary design optimization of MEMS: a review of its history and state-of-the-art

As an important part of the internet of things (IoTs) and cyber-physical systems (CPS), Micro-Electro-Mechanical-Systems (MEMS) is playing more and more irreplaceable role in current industrial community and the forthcoming era of the Industry 4.0. The limitations of some frequently used design methods for MEMS design optimization are analyzed in this review. In order to overcome these difficulties, a recent trend in design optimization of MEMS is inspired by the natural evolution mechanism. Many powerful techniques, especially the evolutionary computation (EC), have been used for the design optimization of MEMS. This paper presents a review of the achievements in this promising research area which utilizes EC methods for the design optimization of MEMS and also proposes three open issues that it is facing.

[1]  Katsuyuki Machida,et al.  A mixed-design technique for integrated MEMS using a circuit simulator with HDL , 2013, Proceedings of the 20th International Conference Mixed Design of Integrated Circuits and Systems - MIXDES 2013.

[2]  Zheng Jin-hu,et al.  A Study on How to Use Angle Information to Include Decision Maker's Preferences , 2014 .

[3]  Erik D. Goodman,et al.  An evolutionary approach for robust layout synthesis of MEMS , 2005, Proceedings, 2005 IEEE/ASME International Conference on Advanced Intelligent Mechatronics..

[4]  Zhun Fan,et al.  Multi-criteria layout synthesis of MEMS devices using memetic computing , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

[5]  Ying Zhang,et al.  Interactive hybrid evolutionary computation for MEMS design synthesis , 2012, Math. Comput. Simul..

[6]  Julien Bourgeois,et al.  Distributed Intelligent MEMS: Progresses and Perspectives , 2011, IEEE Systems Journal.

[7]  Hui Li,et al.  EVOLUTIONARY TECHNIQUES IN MEMS SYNTHESIS , 1998 .

[8]  Yang Dong,et al.  Research on Evolutionary Multi-Objective Optimization Algorithms , 2009 .

[9]  Giovanni Seni,et al.  Ensemble Methods in Data Mining: Improving Accuracy Through Combining Predictions , 2010, Ensemble Methods in Data Mining.

[10]  Alice M. Agogino,et al.  A COMPARISON OF MEMS SYNTHESIS TECHNIQUES , 2002 .

[11]  Ashutosh Tiwari,et al.  Evolutionary multi-objective design optimisation of energy harvesting MEMS: The case of a Piezoelectric , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

[12]  David Lin,et al.  Robust MEMS gyroscope for oil and gas exploration , 2014, Sensing Technologies + Applications.

[13]  Erik K. Antonsson.  Robust Mask-Layout Synthesis for MEMS 1 , 2001 .

[14]  Hong Yun Yang,et al.  Genetic Algorithm Based Multidisciplinary Design Optimization of MEMS Accelerometer , 2011 .

[15]  Erik K. Antonsson,et al.  Robust Mask-Layout Synthesis for MEMS , 2000 .

[16]  Michael Kraft,et al.  Parameter optimization for a high-order band-pass continuous-time sigma-delta modulator MEMS gyroscope using a genetic algorithm approach , 2012 .

[17]  W. Crossland,et al.  Demonstration of Multi-Casting in a 1 × 9 LCOS Wavelength Selective Switch , 2014, Journal of Lightwave Technology.

[18]  Jason D. Lohn,et al.  Evolving MEMS Resonator Designs for Fabrication , 2008, ICES.

[19]  Marco Balucani,et al.  Kinetostatic optimization of a MEMS-based compliant 3 DOF plane parallel platform , 2013, 2013 IEEE 9th International Conference on Computational Cybernetics (ICCC).

[20]  Alice M. Agogino,et al.  Mems design synthesis based on hybrid evolutionary computation , 2006 .

[21]  Ying Zhang,et al.  Hierarchical component-based representations for evolving microelectromechanical systems designs , 2010, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[22]  Maoguo Gong,et al.  Research on Evolutionary Multi-Objective Optimization Algorithms: Research on Evolutionary Multi-Objective Optimization Algorithms , 2009 .

[23]  Zhun Fan,et al.  Improved Differential Evolution Based on Stochastic Ranking for Robust Layout Synthesis of MEMS Components , 2009, IEEE Transactions on Industrial Electronics.

[24]  Kalyanmoy Deb,et al.  An interactive evolutionary multi-objective optimization and decision making procedure , 2010, Appl. Soft Comput..

[25]  Jianjun Hu,et al.  Hierarchical evolutionary synthesis of MEMS , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[26]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[27]  E. Antonsson,et al.  Mask-Layout Synthesis Through an Evolutionary Algorithm , 1999 .

[28]  Alice M. Agogino,et al.  AUTOMATED DESIGN SYNTHESIS FOR MICRO-ELECTRO-MECHANICAL SYSTEMS (MEMS) , 2002, DAC 2002.

[29]  Ashwin Seshia,et al.  An analytical formulation for phase noise in MEMS oscillators , 2014, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.

[30]  E K Antonsson,et al.  Automated Mask-Layout and Process Synthesis for MEMS , 2000 .

[31]  Pan Wang,et al.  Evolutionary design optimization of MEMS: A brief review , 2010, 2010 IEEE International Conference on Industrial Technology.

[32]  Ling Li,et al.  Determination of Weights for Multiobjective Decision Making or Machine Learning , 2014, IEEE Systems Journal.

[33]  Eckart Uhlmann,et al.  Intelligentes Elektroniksystem für Condition Monitoring in Industrie 4.0 , 2016 .

[34]  K. Masu,et al.  A Single-Platform Simulation and Design Technique for CMOS-MEMS Based on a Circuit Simulator With Hardware Description Language , 2013, Journal of Microelectromechanical Systems.

[35]  Hong Wang,et al.  How to measure adaptation complexity in evolvable systems - A new synthetic approach of constructing fitness functions , 2011, Expert Syst. Appl..

[36]  Tao Li,et al.  Distributed Intelligent MEMS , 2016, ACM Comput. Surv..

[37]  S. Senturia.  Microsystem Design , 2000 .

[38]  Ashutosh Tiwari,et al.  An efficient evolutionary multi-objective framework for MEMS design optimisation: validation, comparison and analysis , 2011, Memetic Comput..

[39]  Corie Lynn Cobb,et al.  MEMS design synthesis: integrating case-based reasoning and multi-objective genetic algorithms , 2007, SPIE Micro + Nano Materials, Devices, and Applications.

[40]  Corie Lynn Cobb,et al.  Case-Based Reasoning for Evolutionary MEMS Design , 2010, J. Comput. Inf. Sci. Eng..

[41]  Alice M. Agogino,et al.  Optimized Design of MEMS by Evolutionary Multi-objective Optimization with Interactive Evolutionary Computation , 2004, GECCO.

[42]  Jianjun Hu,et al.  System-Level Synthesis of MEMS via Genetic Programming and Bond Graphs , 2003, GECCO.

[43]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[44]  Sihai Guo,et al.  Application of an evolutionary algorithm in the optimal design of micro-sensor. , 2015, Bio-medical materials and engineering.

[45]  Jason D. Lohn,et al.  Automated design of a MEMS resonator , 2007, 2007 IEEE Congress on Evolutionary Computation.

[46]  Gang-Won Jang,et al.  Topology optimization of MEMS considering etching uncertainties using the level‐set method , 2012 .

[47]  Erik D. Goodman,et al.  Structured synthesis of MEMS using evolutionary approaches , 2008, Appl. Soft Comput..

[48]  Tadeusz Uhl,et al.  Reliability- and performance-based robust design optimization of MEMS structures considering technological uncertainties , 2012 .

[49]  Erik D. Goodman,et al.  Knowledge interaction with genetic programming in mechatronic systems design using bond graphs , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).