Internal Component Layout Optimization Method for Aircraft Safety Design

2009 ◽  
Author(s):  
Pei Yang ◽  
Bifeng Song
Keyword(s):  
Optimization Method ◽  
Layout Optimization ◽  
Component Layout ◽  
Safety Design ◽  
Internal Component

Assignment and layout integration optimization for simplified satellite re-entry module component layout

2017 ◽  
Vol 233 (12) ◽  
pp. 4287-4301 ◽  
Author(s):  
Zhi-Zheng Xu ◽  
Chong-Quan Zhong ◽  
Hong-Fei Teng
Keyword(s):  
Evolutionary Algorithm ◽  
Optimization Model ◽  
Optimization Problem ◽  
Optimization Method ◽  
Layout Design ◽  
Layout Optimization ◽  
Optimization Process ◽  
Supporting Surface ◽  
Computational Performance ◽  
Component Layout

Previous studies of satellite module component (equipment) layout optimization usually initialized a component assignment in the initialization stage, which kept constant in following optimization process. The invariable component assignment will restrict the further improvement in layout optimization. To overcome this deficiency, an assignment and layout integration optimization method is presented for multi-module or supporting surface satellite module component layout design. The assignment and layout integration optimization model and the component reassignment model are built. The component reassignment model is solved by algorithms with new heuristic rule, and the integration optimization model itself is solved by evolutionary algorithm. The purpose of this article is to improve the computational performance of algorithms for multi-module or supporting surface satellite module component layout optimization. The proposed method is applied to a simplified satellite re-entry module component layout optimization problem to illustrate its effectiveness.

Particle Swarm Optimization for Integrated Fixture Layout

2015 ◽  
Vol 787 ◽  
pp. 285-290
Author(s):  
D. Elilraja ◽  
Sundaravel Vijayan
Keyword(s):  
Particle Swarm Optimization ◽  
Manufacturing Industry ◽  
Particle Swarm ◽  
Optimization Method ◽  
Layout Optimization ◽  
Work Piece ◽  
Swarm Optimization ◽  
Fixture Layout ◽  
Fixture Layout Optimization ◽  
Supporting Device

Fixture is a work-holding or supporting device used in the manufacturing industry to hold the workpiece. Fixtures are used to securely locate (position in a specific location or orientation) and support the work, ensuring that all parts produced using the fixture will maintain conformity and interchangeability. The location of fixture elements is called as fixture layout. The fixture layout plays major role in the work piece deformation during the machining operation. Hence optimization of fixture layout to minimize the work piece deformation is one of the critical aspects in the fixture design process. Minimization the workpiece deformation which is the objective function in the present work is calculated using Finite Element Method (FEM) and the fixture layout is optimized using Discrete fixture layout optimization method (DFLOM), Continuous fixture layout optimization method (CFLOM) and Integrated fixture layout optimization method (IFLOM).The workpiece deformation is minimum in Particle Swarm Optimization (PSO) based IFLOM is reported for the selected fixture. In this paper the PSO is used as an optimization tool to optimize the workpiece deformation.

A Memetic Algorithm for multi-objective fixture layout optimization

2014 ◽  
Vol 229 (16) ◽  
pp. 3047-3058 ◽  
Author(s):  
Xue Bai ◽  
Fei Hu ◽  
Gaiyun He ◽  
Bohui Ding
Keyword(s):  
Memetic Algorithm ◽  
Fitness Function ◽  
Optimization Method ◽  
Layout Optimization ◽  
Accurate Solution ◽  
Entropy Method ◽  
Objective Functions ◽  
Multi Objective ◽  
Fixture Layout ◽  
Fixture Layout Optimization

A proper scheme of fixture layout can reduce locating errors of a workpiece. However, a multi-objective fixture layout optimization, involving multiple conflicting objective functions, will lead to much more accurate solution and complex computation. This paper describes a new approach based on Memetic Algorithm (MA) to multi-objective fixture layout optimization, considering both location accuracy and stability. This approach uses an entropy method to obtain the weights of each objective functions, and establishes a fitness function. Then, a MA is developed to properly select the positions of locators to minimize the fitness function. An example illustrates that the new optimization method based on MA can improve the locating precision of a workpiece effectively and efficiently. This method is also suitable for solving a multi-objective fixture layout optimization problem with more objective functions.

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