Parametric Design and Multi-Objective Optimization of LCD Packaging Cushion Foams

2012 ◽  
Vol 200 ◽  
pp. 32-36 ◽  
Author(s):  
Guo Qiang Zhang ◽  
Yu Fang Du ◽  
Xing Zhou Li ◽  
Xian Xiang Che
Keyword(s):  
Optimal Design ◽  
Optimization Design ◽  
Parametric Design ◽  
Model Parameters ◽  
Multi Objective Optimization ◽  
Ansys Software ◽  
Design Exploration ◽  
Multi Objective ◽  
Simulation Results ◽  
Design Defects

Compression simulation of package in ANSYS software will find design defects. Based on the simulation results, DOE(Design Exploration Module) generates the optimization design in accordance with the response surface analysis. The packaging cushion foams size parametric design and multi-objective optimization were carried out. Optimal design points were obtained. The foams size parameters were generated by Goal Driven Optimization. The new cushion model parameters will be adjusted automatically according to optimization results. The compression simulation of the new design model was performed to identify the reliability.

Multi-Objective Optimization Design of Vibration Screener Support Spring Parameters with Vibration Mechanics

2012 ◽  
Vol 252 ◽  
pp. 144-148
Author(s):  
Ling Qin Meng ◽  
Zhi Wei Wang
Keyword(s):  
Optimal Design ◽  
Optimization Design ◽  
Building Materials ◽  
Design Method ◽  
Optimization Theory ◽  
Penalty Function Method ◽  
Multi Objective Optimization ◽  
Vertical Stiffness ◽  
Multi Objective ◽  
Future Design

Vibration screener is an important mechanism which is widely applied to metallurgy, building materials, chemical industry, grain, mine, etc. On the basis of deeply studying work principle and support structure of vibration screener, the paper conducts ZKB Linear vibration screener as study object. According to mass of vibration, vertical stiffness, horizontal stiffness, vertical amplitude, horizontal amplitude, and free high of vibration screener support spring, the paper conducts the lightest weight of support spring and the biggest fatigue safety factor as the objective function of multi-objective optimization design to establish a series of constraints. Then using of the penalty function method of optimization theory , the paper gets the optimal design results of support spring and gives the optimal design dimensions, which provides a reliable design method of support spring for the future design of vibration screener and reduce the blindness of the design .

Multi-Objective Optimization of the FOFAS Based on the Workbench/Exploration

2014 ◽  
Vol 889-890 ◽  
pp. 101-106
Author(s):  
Liang Xiao ◽  
Ming Feng ◽  
Yang Ge ◽  
Wei Wang
Keyword(s):  
Optimization Design ◽  
Parametric Design ◽  
Focal Point ◽  
Equivalent Stress ◽  
Minimum Mass ◽  
Multi Objective Optimization ◽  
Pareto Solutions ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Optimization Simulation

A certain FOFAS (framework of feeding ammunition system) has extremely important function such as fixing, supporting and leading orientation, etc. Optimization design for FOFAS is the focal point under meeting such criterions as stiffness, strength and safety. Using Workbench, this article mainly carried out parametric design to optimize feeding ammunition box under Multi-objective Genetic Algorithm (MOGA). Pareto solutions from optimization simulation showed that minimum mass of ammunition box was decreased by 6.17%, displacement deformation had little influence on the FOFAS and equivalent stress was increased by 0.35%. The optimizing results satisfied the strength, stiffness and polynomial response requirements.

Design and Optimization of Packaging Cushion Foams for Liquid Crystal Display

2011 ◽  
Vol 101-102 ◽  
pp. 383-386
Author(s):  
Xing Zhou Li ◽  
Guo Qiang Zhang ◽  
Ji Qiang Zhai ◽  
Wen Juan Wang
Keyword(s):  
Optimization Design ◽  
Parametric Design ◽  
Liquid Crystal Display ◽  
Parametric Model ◽  
Compression Force ◽  
Compression Process ◽  
Design Problems ◽  
Design And Optimization ◽  
Simulation Results ◽  
Design Defects

The compression simulation of LCD package indicates some potential design problems. Under large compression force the package will slope due to asymmetric deformation. The 3-D whole package parametric model was built in Pro/Engineer. Compression process simulation of package in Ansys will find design defects. Based on the simulation results, Ansys Design Exploration module generates the optimization design in accordance with the response surface analysis result. The compression simulation was performed to identify the reliability of the new design. In addition, some guidance on the cushion packaging parametric design and optimization was put forward.

scholarly journals A New Approach to Group Multi-Objective Optimization under Imperfect Information and Its Application to Project Portfolio Optimization

2021 ◽  
Vol 11 (10) ◽  
pp. 4575
Author(s):  
Eduardo Fernández ◽  
Nelson Rangel-Valdez ◽  
Laura Cruz-Reyes ◽  
Claudia Gomez-Santillan
Keyword(s):  
Portfolio Optimization ◽  
Imperfect Information ◽  
Model Parameters ◽  
Final Decision ◽  
Project Portfolio ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
New Approach ◽  
Multi Objective ◽  
Group Member

This paper addresses group multi-objective optimization under a new perspective. For each point in the feasible decision set, satisfaction or dissatisfaction from each group member is determined by a multi-criteria ordinal classification approach, based on comparing solutions with a limiting boundary between classes “unsatisfactory” and “satisfactory”. The whole group satisfaction can be maximized, finding solutions as close as possible to the ideal consensus. The group moderator is in charge of making the final decision, finding the best compromise between the collective satisfaction and dissatisfaction. Imperfect information on values of objective functions, required and available resources, and decision model parameters are handled by using interval numbers. Two different kinds of multi-criteria decision models are considered: (i) an interval outranking approach and (ii) an interval weighted-sum value function. The proposal is more general than other approaches to group multi-objective optimization since (a) some (even all) objective values may be not the same for different DMs; (b) each group member may consider their own set of objective functions and constraints; (c) objective values may be imprecise or uncertain; (d) imperfect information on resources availability and requirements may be handled; (e) each group member may have their own perception about the availability of resources and the requirement of resources per activity. An important application of the new approach is collective multi-objective project portfolio optimization. This is illustrated by solving a real size group many-objective project portfolio optimization problem using evolutionary computation tools.

scholarly journals Research on Blank Optimization Design Based on Low-Carbon and Low-Cost Blank Process Route Optimization Model

2021 ◽  
Vol 13 (4) ◽  
pp. 1929
Author(s):  
Yongmao Xiao ◽  
Wei Yan ◽  
Ruping Wang ◽  
Zhigang Jiang ◽  
Ying Liu
Keyword(s):  
Optimization Model ◽  
Optimization Design ◽  
Design Method ◽  
Low Cost ◽  
Route Optimization ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Blank Design ◽  
Process Route

The optimization of blank design is the key to the implementation of a green innovation strategy. The process of blank design determines more than 80% of resource consumption and environmental emissions during the blank processing. Unfortunately, the traditional blank design method based on function and quality is not suitable for today’s sustainable development concept. In order to solve this problem, a research method of blank design optimization based on a low-carbon and low-cost process route optimization is proposed. Aiming at the processing characteristics of complex box type blank parts, the concept of the workstep element is proposed to represent the characteristics of machining parts, a low-carbon and low-cost multi-objective optimization model is established, and relevant constraints are set up. In addition, an intelligent generation algorithm of a working step chain is proposed, and combined with a particle swarm optimization algorithm to solve the optimization model. Finally, the feasibility and practicability of the method are verified by taking the processing of the blank of an emulsion box as an example. The data comparison shows that the comprehensive performance of the low-carbon and low-cost multi-objective optimization is the best, which meets the requirements of low-carbon processing, low-cost, and sustainable production.

Multi-objective optimization of squirrel cage fan for range hood based on Kriging model

2021 ◽  
pp. 095440622199586
Author(s):  
Qianhao Xiao ◽  
Jun Wang ◽  
Boyan Jiang ◽  
Weigang Yang ◽  
Xiaopei Yang
Keyword(s):  
Flow Rate ◽  
Optimization Design ◽  
Volume Flow Rate ◽  
Kriging Model ◽  
Volume Flow ◽  
Design Parameters ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Squirrel Cage

In view of the multi-objective optimization design of the squirrel cage fan for the range hood, a blade parameterization method based on the quadratic non-uniform B-spline (NUBS) determined by four control points was proposed to control the outlet angle, chord length and maximum camber of the blade. Morris-Mitchell criteria were used to obtain the optimal Latin hypercube sample based on the evolutionary operation, and different subsets of sample numbers were created to study the influence of sample numbers on the multi-objective optimization results. The Kriging model, which can accurately reflect the response relationship between design variables and optimization objectives, was established. The second-generation Non-dominated Sorting Genetic algorithm (NSGA-II) was used to optimize the volume flow rate at the best efficiency point (BEP) and the maximum volume flow rate point (MVP). The results show that the design parameters corresponding to the optimization results under different sample numbers are not the same, and the fluctuation range of the optimal design parameters is related to the influence of the design parameters on the optimization objectives. Compared with the prototype, the optimized impeller increases the radial velocity of the impeller outlet, reduces the flow loss in the volute, and increases the diffusion capacity, which improves the volume flow rate, and efficiency of the range hood system under multiple working conditions.

Applications of Multiple Objective Genetic Algorithms in the Optimization Design of Tracked Self-Moving Power’s Layout

2013 ◽  
Vol 307 ◽  
pp. 161-165
Author(s):  
Hai Jin ◽  
Jin Fa Xie
Keyword(s):  
Optimization Design ◽  
Pareto Front ◽  
Layout Optimization ◽  
Multiple Objective ◽  
Multi Objective Optimization ◽  
Layout Problem ◽  
Basic Principles ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Set Up

A multi-objective genetic algorithm is applied into the layout optimization of tracked self-moving power. The layout optimization mathematical model was set up. Then introduced the basic principles of NSGA-Ⅱ, which is a Pareto multi-objective optimization algorithm. Finally, NSGA-Ⅱwas presented to solve the layout problem. The algorithm was proved to be effective by some practical examples. The results showed that the algorithm can spread toward the whole Pareto front, and provide many reasonable solutions once for all.

Sign in / Sign up

Export Citation Format

Share Document