Evolutionary Synthesis of MEMS


An evolutionary synthesis framework for Microelectrical Mechanical System (MEMS) design is presented. MEMS based technologies promise to bring a revolution to the world we live in just as the integrated circuit has done in recent decades; better design tools are critical to this revolution. More complex design objectives and constraints demand automation to generate successful devices. Genetic algorithms and other stochastic evolutionary synthesis approaches are used to design surface micromachined MEMS using flexural suspensions and electrostatic actuation. A general MEMS synthesis approach is presented, as well as data-structures for describing designs and applying synthesis algorithms. Synthesis is based on the use of reduced order modeling to simulate design performance. The application of the concept of shape grammars for MEMS synthesis is discussed and applied to the generation of viable initial resonator designs. Human Interactive Evolution Computation (IEC) is applied to MEMS to improve synthesis performance; user studies show an increase in output quality through the use of human interaction compared to our non-interactive synthesis tool. The applicability of our approach, design encoding, objectives and constraints are discussed for several MEMS examples, including resonating masses, accelerometers and gyroscopes. We validate of our approach through fabrication and characterization, successfully generating MEMS devices with measured performance that matches simulation. The results of the characterization are studied to further improve our method for more accurate synthesis.