... Abstract Selection of optimal machining parameters is a difficult process due to the large number of variables and their complex interdependencies. In this study, a genetic algorithm-based method is presented to determine the optimal machining parameters for machining pockets using multi-pass...

... first order analysis (FOA) genetic algorithms Proceedings of 2001 ASME International Mechanical Engineering Congress and Exposition November 11-16, 2001, New York, NY DE-Vol. 112 IMECE2001 /DE-23265 MODULAR STRUCTURAL COMPONENT DESIGN USING THE FIRST ORDER ANALYSIS AND DECOMPOSITION-BASED ASSEMBLY...

... for transit buses, such that this method can be easily implemented for simulation and control design purposes. Based on the analysis of robustness, as well as accuracy and efficiency of optimization techniques, a parameter estimation method that integrates Genetic Algorithms and the Maximum Likelihood...

... level. In this work, a methodology will be presented to solve the NP-Hard problem of process planning through evolutionary optimization using Genetic Algorithms (GA) to generate and then find the optimized process plan for a part or a part family. For the creation of initial population without violating...

... of design parameter changes, in order to minimize contact forces, accelerations, and power requirements due to the existence of joint clearance. Revolute joint clearance contact forces multibody dynamics Kriging meta-model genetic algorithms 1 Copyright © 2013 by ASME A DOE- and Kriging-based...

... to determine optimum arc welding process control parameters is proposed. It is a coupled Genetic Algorithms (GA) and Finite Element (FE) based optimization method where GA directly utilizes output responses of FE based welding simulations for iterative optimization. Effectiveness of the method has been...

... to economically optimise the generation schedule of gas turbine power plants and end-users interconnected through a mini-grid. A hybrid genetic algorithm adapted priority list was developed to solve the multi unit generation schedule optimisation problem. The algorithm developed in this study leads...

... 02 08 2012 Authors of the study propose the method aiming at determination of design properties of a multi-edge grinder. This method is based on a genetic algorithm and its purpose is to optimise the geometric shape of the cutting edges. The input data include population of individuals...

..., provided proper tool design and operating conditions are adopted. In this paper, A genetic algorithm (GA) based optimization procedure has been developed to optimize two factors, material removal rate; and delamination factor, using multi-objective function model with a weighted approach...

... slab configurations (i.e., different cooling tubes arrangements). A multi-objective genetic algorithm (MOGA II) is then used to optimize the slab thermal performance starting from the initial family set. The results confirm that Constructal Theory correctly predicts the “nearly-optimal” tube...

..., the surface roughness prediction model has been optimized by using genetic algorithms (GA). The genetic algorithm program gives minimum values of surface roughness and their respective optimal machining conditions (cutting conditions and tool geometry). Hard turning Surface Roughness Tool Geometry...

... that the proposed controller can track the desired fin angle control under various operating conditions. 26 05 2009 Fuzzy Logic Control Piezoelectric bimorph Smart Fin Genetic Algorithms Model Identification Proceedings of IMECE2007 2007 ASME International Mechanical Engineering Congress...

... Stream of Variation methodologies Multi-station machining Measurement scheme synthesis Successive removal of measurements Genetic algorithms The selection of measurements in multi-station machining systems is currently not a systematic process and it involves expert human intervention...

... behavior for higher shear rates. Determination of model parameters is a complex problem due to the non-linearity of the model of the large amount of scatter in the experimentally observed data. To estimate the rheological parameters, we used a genetic algorithm and carried out a global optimization...

... the difference between the heat flux measured at the exposed surfaces and the heat flux predicted by the BEM under the current strength distribution of the singularities. A genetic algorithm iteratively alters the strength distribution of the singularities until the measuring surfaces heat fluxes are matched...

... Fuzzy Logic Control Piezoelectric Actuator Smart Fin Genetic Algorithms Fin of a subsonic projectile produce maneuvering force and moment that control the rotation angle of a projectile fin during flight. The objective of this paper is to study the feasibility of using piezoelectric...

... of CBR to improve assembly part design. Similarity measures and the weight of different features are crucial in determining the accuracy of retrieving cases from the case base. To develop the weight of part features and retrieve a similar part design, the research proposes using Genetic Algorithms (GAs...

... 25 01 2008 This paper describes the optimization of the parallel hybrid electric vehicle (HEV) component sizing using a genetic algorithm approach. The optimization process is performed over three different driving cycles including the European ECE-EUDC, American FTP and TEH-CAR cycles...

... This paper deals with a hybrid optimization of the degree of cure and temperature field into the work piece during the pultrusion manufacturing process. The procedure is based on the consecutive application of a heuristic technique (Genetic Algorithms), with an analytical method (simplex...