A genetic algorithm-based fixture locating positions and clamping schemes optimization

2003 ◽  
Vol 217 (8) ◽  
pp. 1075-1083 ◽  
Author(s):  
Y G Liao
Keyword(s):  
Genetic Algorithm ◽  
Sheet Metal ◽  
Optimization Method ◽  
Form Accuracy ◽  
Dimensional Variation ◽  
Stationary Set ◽  
Machining Fixtures ◽  
Sheet Metal Assembly ◽  
Industrial Part ◽  
Selection Of

Optimizing the locator positions and clamping schemes of a fixture was proven to improve the dimensional and form accuracy of a workpiece significantly. A number of approaches have been developed to optimize the designs of sheet-metal assembly fixtures and machining fixtures. However, in these previous works, the optimal selection of the positions of locators and clamps were based on a stationary set of locator and clamp conditions; i.e. the numbers of the locators and clamps were fixed during optimization. This paper proposes a genetic algorithm (GA)-based optimization method to select automatically the optimal numbers of locators and clamps as well as their optimal positions in sheet-metal assembly fixtures, such that the workpiece deformation due to the gravity effect and resulting variation due to part dimensional variation are simultaneously minimized. The application result of a real industrial part demonstrated that the proposed algorithm effectively achieves the objective.

A Genetic Algorithm Approach to Weld Pattern Optimization in Sheet Metal Assembly

2003 ◽  
Author(s):  
Gene Y. Liao
Keyword(s):  
Genetic Algorithm ◽  
Sheet Metal ◽  
Optimization Method ◽  
Structural Deformation ◽  
Assembly Process ◽  
Sheet Metal Parts ◽  
Final Assembly ◽  
Welding Operation ◽  
Genetic Algorithm Approach ◽  
Sheet Metal Assembly

In sheet metal assembly process, welding operation joins two or more sheet metal parts together. Since sheet metals are subject to dimensional variation resulted from manufacturing randomness, gap may be generated at each weld pair prior to welding. These gaps are forced to close during a welding operation and accordingly undesirable structural deformation results. Optimizing the welding pattern (the number and locations of weld pairs) of an assembly process was proven to significantly improve the quality of final assembly. This paper presents a Genetic Algorithm (GA)-based optimization method to automatically search for the optimal weld pattern so that the assembly deformation is minimized. Application result of a real industrial part demonstrated that the proposed algorithm effectively achieve the objective.

Variation Analysis for Compliant Assembly

2000 ◽  
Author(s):  
S. Jack Hu ◽  
Yufeng Long ◽  
Jaime Camelio
Keyword(s):  
Sheet Metal ◽  
Assembly Line ◽  
Assembly Process ◽  
Variation Analysis ◽  
Assembly Lines ◽  
Compliant Assembly ◽  
Single Station ◽  
Dimensional Variation ◽  
Sheet Metal Assembly

Abstract Assembly processes for compliant non-rigid parts are widely used in manufacturing automobiles, furniture, and electronic appliances. One of the major issues in the sheet metal assembly process is to control the dimensional variation of assemblies throughout the assembly line. This paper provides an overview of the recent development in variation analysis for compliant assembly. First, the unique characteristics of compliant assemblies are discussed. Then, various approaches to variation modeling for compliant assemblies are presented for single station and multi-station assembly lines. Finally, examples are given to demonstrate the applications of compliant assembly variation models.

scholarly journals Developing Induction Motor State Observers with Increased Robustness

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5487
Author(s):  
Tadeusz Białoń ◽  
Marian Pasko ◽  
Roman Niestrój
Keyword(s):  
Genetic Algorithm ◽  
Control Theory ◽  
Induction Motor ◽  
Optimization Method ◽  
Practical Application ◽  
Proportional Integral ◽  
State Observers ◽  
Simulation Results ◽  
Selection Of

This paper presents the results of recently conducted research on Luenberger observers with non-proportional feedbacks. The observers are applied for the reconstruction of magnetic fluxes of an induction motor. Structures of the observers known from the control theory are presented. These are a proportional observer, a proportional-integral observer, a modified integral observer, and an observer with additional integrators. The practical application of some of these observers requires modifications to their structures. In the paper, the simulation results for all mentioned types of observers are presented. The simulations are performed with a Scilab-Xcos model which is attached to this paper. The problem of gains selection of the observers is discussed. Gains are selected with the described optimization method based on a genetic algorithm. A Scilab file launching the genetic algorithm also is attached to this paper.

Fixture Layout Design and Optimization of Sheet Metal Assembly Based on Genetic Algorithm for Optimization Toolbox

2016 ◽  
Author(s):  
Yanfeng Xing ◽  
Fang Wang ◽  
Qing Ji
Keyword(s):  
Genetic Algorithm ◽  
Finite Element ◽  
Sheet Metal ◽  
Layout Optimization ◽  
Finite Element Analyses ◽  
Design And Optimization ◽  
Fixture Layout ◽  
Fixture Layout Optimization ◽  
Dimensional Variation

Fixture layout can affect deformation and dimensional variation of sheet metal assemblies. Conventionally, the assembly dimensions are simulated using a large number of finite element analyses, and fixture layout optimization needs significant user intervention and unaffordable iterations of finite element analyses. This paper therefore proposes a fully automated and efficient method of fixture layout optimization based on the combination of 3DCS simulation (for dimensional analyses) and GAOT, a genetic algorithm in optimization toolbox in MATLAB. The locating points, the key elements of a fixture layout, are selected from a much smaller candidate pool thanks to our proposed manufacturing constraints based filtering methods and thus the computational efficiency is greatly improved. Since MATLAB macro commands of 3DCS have been developed to calculate assembly dimensions, the optimization process is fully automated. A case study of inner hood is applied to demonstrate the proposed method. The results show that the proposed method is suitable for generating the optimal fixture layout with excellent efficiency for engineering applications.

Optimization of Fixture and Joint Positions in Sheet Metal Assembly: The Effect of Fixture Numbers and Constraints

2011 ◽  
Author(s):  
Kambiz Haji Hajikolaei ◽  
G. Gary Wang
Keyword(s):  
Sheet Metal ◽  
Metal Forming ◽  
Optimization Method ◽  
Stochastic Methods ◽  
Objective Functions ◽  
Variation Analysis ◽  
Spring Back ◽  
Final Assembly ◽  
Deterministic Methods ◽  
Sheet Metal Assembly

Assembly process is widely used in the manufacturing processes. Fabrication processes such as machining, casting and metal forming are not perfect and introduce variation in the components. Variations of components and tools accumulate and cause the assembly variation. In this paper, after reviewing the literature and presenting sheet metal assembly variation analysis, an optimization method is used to minimize the assembly variation by optimizing the location of joints and fixtures. The model is constructed in ANSYS with three fixtures and two joints. When a black-box function calculated numerically in software is used as the objective function, using deterministic methods for optimization is not suitable because the deterministic methods need knowledge of the objective functions. Also, using stochastic methods such as genetic algorithm is not suitable because of the large number of function evaluations they normally need. In this paper, an optimization algorithm based on mode-pursuing sampling (MPS) method is used to minimize the assembly variation. The optimization method is explained and after implementing the method, results are presented. It is learned that, in addition to the number of fixtures, the constraints on neighboring fixture locations also affect the optimal fixture layout, as well as the final assembly stiffness and spring-back.

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