Early-Stage Analysis for MEMS Structural Optimization I: Concept

2005 ◽  
Author(s):  
Takahiro Miki ◽  
Koji Ishikawa ◽  
Hiroki Mamiya ◽  
Qiang Yu
Keyword(s):  
Optimal Design ◽  
Early Stage ◽  
Design Method ◽  
Design Stage ◽  
Design Parameters ◽  
Total System ◽  
Trade Offs ◽  
Optimal Design Method ◽  
Stage Analysis ◽  
System Characteristics

We report on the development of a new micro-electro-mechanical systems (MEMS) optimal design method called MEMS Early-Stage Analysis (MESA), which supports the total system evaluation of MEMS devices before the design stage. Recently total system simulation and design using Computer Aided Engineering (CAE) analyses have become important in MEMS device development due to their fabrication and design complexity. Although a lot of CAE methods that can be applied to MEMS have been demonstrated, time-consuming trial-and-error processes are inevitable at the design stage in order to obtain an optimal structure. In our design method, we can clarify and simplify the relation between design parameters and the system characteristics using a MESA weighted orthogonal array. In the MESA array, the sensitivity of each design factor for the system performance shows numerically how the design parameter influences the system characteristics. The existent trade-offs between design parameters can be minimized by both modifying the design concept and adjusting the sensitivities. Therefore MEMS designers are able to optimize the total system based on the information from the MESA array. Moreover, particular system characteristics can be enhanced in order to meet the system requirement through the adjustment of weight values for the sensitivities. The MESA makes the evaluation of system validity possible at the concept design stage. To conduct the informative optimal design method at the beginning of development leads the reduction of the total MEMS design time and cost.

Prediction of the Life of CVJ Boot in Design Stage and Establishment of an Optimal Design Method with FEA

1998 ◽  
Author(s):  
Kuniyasu Ito ◽  
Yukio Aono ◽  
Nobuhiko Ikano ◽  
Takashi Matsuda ◽  
Masaru Takeda
Keyword(s):  
Optimal Design ◽  
Design Method ◽  
Design Stage ◽  
Optimal Design Method

An Optimal Design Method for Radar Brackets

2011 ◽  
Vol 328-330 ◽  
pp. 232-236
Author(s):  
Lian Zhong Guo ◽  
Ding Yang ◽  
Zi Teng Huang
Keyword(s):  
Optimal Design ◽  
Conceptual Design ◽  
Phased Array ◽  
Design Method ◽  
Optimization Method ◽  
Design Stage ◽  
Evolutionary Structural Optimization ◽  
Excessive Weight ◽  
Optimal Design Method ◽  
Implementation Method

The purpose of this work is to present an optimal design method for radar brackets to get the lightest structure with stiffness constraint. Current radar brackets usually have conservative strength and excessive weight which influences the mobility of radar greatly as they are not optimized in the conceptual design stage. In this paper the well-known ESO (Evolutionary Structural Optimization) method based on ANSYS is studied and used as the method to optimize them. To begin with the criteria of ESO method and its implementation method are studied. Then a case of optimization for a phased array radar bracket is studied and at last the optimization result is compared to the result by using WORKBENCH (a commercial CAE software) and the comparison shows that this method has its unique superiority.

scholarly journals An Optimal Design Method for Compliant Mechanisms

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Ngoc Le Chau ◽  
Ngoc Thoai Tran ◽  
Thanh-Phong Dao
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Optimal Design ◽  
Compliant Mechanisms ◽  
Design Method ◽  
Fitness Function ◽  
Current Method ◽  
Design Parameters ◽  
Optimal Design Method ◽  
Element Method

Compliant mechanisms are crucial parts in precise engineering but modeling techniques are restricted by a high complexity of their mechanical behaviors. Therefore, this paper devotes an optimal design method for compliant mechanisms. The integration method is a hybridization of statistics, finite element method, artificial intelligence, and metaheuristics. In order to demonstrate the superiority of the method, one degree of freedom is considered as a study object. Firstly, numerical datasets are achieved by the finite element method. Subsequently, the main design parameters of the mechanism are identified via analysis of variance. Desirability of both displacement and frequency of the mechanism is determined, and then, they are embedded inside a fuzzy logic system to combine into a single fitness function. Then, the relationship between the fine design variables and the fitness function is modeled using the adaptive network-based fuzzy inference system. Next, the single fitness function is maximized via moth-flame optimization algorithm. The optimal results determined that the frequency is 79.517 Hz and displacement is 1.897 mm. In terms of determining the global optimum solution, the current method is compared with the Taguchi, desirability, and Taguchi-integrated fuzzy methods. The results showed that the current method is better than those methods. Additionally, the devoted method outperforms the other metaheuristic algorithms such as TLBO, Jaya, PSOGSA, SCA, ALO, and LAPO in terms of faster convergence. The result of this study will be considered to apply for multiple-degrees-of-freedom compliant mechanisms in future work.

Early-Stage Analysis for MEMS Structural Optimization II: Its Application to Microrelay Reliability

2005 ◽  
Author(s):  
Koji Ishikawa ◽  
Takahiro Miki ◽  
Hiroki Mamiya ◽  
Q. Yu
Keyword(s):  
Structural Optimization ◽  
Mechanical Performance ◽  
Early Stage ◽  
Design Stage ◽  
Design Parameters ◽  
Total System ◽  
Concept Design ◽  
Restoring Force ◽  
Electrostatic Actuators ◽  
The Impact

This paper discusses a new structural optimization methodology for MEMS and its application to reliability evaluation of micro relays. Clarifying the relationship between system characteristics and design factors, our new design optimization method (called MESA) enables numerical evaluation of MEMS structures at the concept design stage. The relation is defined as sensitivity, which is calculated based on the system governing equations with an experimental method technique and a FEM analysis. The sensitivities show not only the effect of design parameters for the system performances but also the system tradeoffs. The MESA allows designers to obtain “rough” total system performance and create a new concept. The MESA is successfully applied to evaluate an electrostatic microrelay for DC/RF signal switching. With the aid of the MESA, we define existing problems of current cantilever-shape MEMS switches and propose new mechanical approaches in order to enhance the mechanical reliability. The MESA clearly shows us that there are tradeoffs in the switching phenomenon of cantilever microrelay. Based on the MESA information, a new switching concept, which has tri-state multi-finger lateral contacts, is established and the MEMS structure is designed and fabricated. The tri-state switching concept reduces the number of contacts and also disperses the impact energy, which aggravates adhesion. In addition, bi-electrostatic actuators increase the adverse force to prevent stiction without the increase of restoring force, which causes degradation or cracks of the contact surfaces. Furthermore, a new push-pull switching structure is designed as a second generation by means of the MESA. The MESA shows that the second concept will provide superior mechanical performance with keeping the high RF isolation.

scholarly journals Development of Optimal Design Method for Steel Double-Beam Floor System Considering Rotational Constraints

2021 ◽  
Vol 11 (7) ◽  
pp. 3266
Author(s):  
Insub Choi ◽  
Dongwon Kim ◽  
Junhee Kim
Keyword(s):  
Optimal Design ◽  
Design Process ◽  
Design Method ◽  
Steel Beams ◽  
High Gravity ◽  
Double Beam ◽  
Iterative Analysis ◽  
Floor Systems ◽  
Optimal Design Method ◽  
Floor System

Under high gravity loads, steel double-beam floor systems need to be reinforced by beam-end concrete panels to reduce the material quantity since rotational constraints from the concrete panel can decrease the moment demand by inducing a negative moment at the ends of the beams. However, the optimal design process for the material quantity of steel beams requires a time-consuming iterative analysis for the entire floor system while especially keeping in consideration the rotational constraints in composite connections between the concrete panel and steel beams. This study aimed to develop an optimal design method with the LM (Length-Moment) index for the steel double-beam floor system to minimize material quantity without the iterative design process. The LM index is an indicator that can select a minimum cross-section of the steel beams in consideration of the flexural strength by lateral-torsional buckling. To verify the proposed design method, the material quantities between the proposed and code-based design methods were compared at various gravity loads. The proposed design method successfully optimized the material quantity of the steel double-beam floor systems without the iterative analysis by simply choosing the LM index of the steel beams that can minimize objective function while satisfying the safety-related constraint conditions. In particular, under the high gravity loads, the proposed design method was superb at providing a quantity-optimized design option. Thus, the proposed optimal design method can be an alternative for designing the steel double-beam floor system.

scholarly journals A Two-Round Optimization Design Method for Aerostatic Spindles Considering the Fluid–Structure Interaction Effect

2021 ◽  
Vol 11 (7) ◽  
pp. 3017
Author(s):  
Qiang Gao ◽  
Siyu Gao ◽  
Lihua Lu ◽  
Min Zhu ◽  
Feihu Zhang
Keyword(s):  
Optimal Design ◽  
Optimization Design ◽  
Design Method ◽  
Fluid Structure Interaction ◽  
Design Procedure ◽  
Design Parameters ◽  
Geometrical Parameters ◽  
Fluid Structure ◽  
Structure Interaction ◽  
Aerostatic Spindle

The fluid–structure interaction (FSI) effect has a significant impact on the static and dynamic performance of aerostatic spindles, which should be fully considered when developing a new product. To enhance the overall performance of aerostatic spindles, a two-round optimization design method for aerostatic spindles considering the FSI effect is proposed in this article. An aerostatic spindle is optimized to elaborate the design procedure of the proposed method. In the first-round design, the geometrical parameters of the aerostatic bearing were optimized to improve its stiffness. Then, the key structural dimension of the aerostatic spindle is optimized in the second-round design to improve the natural frequency of the spindle. Finally, optimal design parameters are acquired and experimentally verified. This research guides the optimal design of aerostatic spindles considering the FSI effect.

Research on the Optimal Design Method of the Main Components for the Wheelchair Pickup

2013 ◽  
Vol 791-793 ◽  
pp. 799-802
Author(s):  
Ya Ping Wang ◽  
H.R. Shi ◽  
L. Gao ◽  
Z. Wang ◽  
X.Y. Jia ◽  
...  
Keyword(s):  
Parametric Design ◽  
Design Method ◽  
Basic Function ◽  
Design Parameters ◽  
Algorithm Optimization ◽  
Optimization Analysis ◽  
Research Designs ◽  
Optimal Design Method ◽  
Main Components

With the increasing of the aging of population all over the world, and With the inconvenience coming from diseases and damage, there will be more and more people using the wheelchair as a tool for transport. When it cant be short of the wheelchair in the daily life, the addition of the function will bring the elevation of the quality of life for the unfortunate. Staring with this purpose, the research designs a pickup with planetary bevel gear for the wheelchair. After determining the basic function of the wheelchair aids, the study determines the design parameters by using the knowledge of parametric design and completes the model for the system with Pro/E, on the other hand, it completes key components optimization analysis which is based on genetic algorithm optimization.

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