Journal Article10.1007/S00170-014-6700-Z
Multi-objective optimization design method for the machine tool’s structural parts based on computer-aided engineering
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TL;DR: In this paper, a multi-objective optimization design method was proposed to improve the static and dynamic performance of the machine tool's structural parts and achieve lightweight design at the same time, while a modified particle swarm optimization algorithm and grey relational analysis method were adapted to solve the model.
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Abstract: In order to improve the static and dynamic performance of the machine tool’s structural parts and achieve lightweight design at the same time, a multi-objective optimization design method is proposed. The orthogonal experimental design method and response surface method are adapted to establish the optimization model, while a modified particle swarm optimization algorithm and grey relational analysis method are adapted to solve the model. The proposed method was used to conduct multi-objective optimization design for a gantry machine tool’s slide-seat. Based on the computer-aided engineering analysis, the response surface optimization model was established. After verifying the accuracy of response surface optimization model, five groups of non-inferior solutions are obtained by using the particle swarm optimization algorithm. The optimal design scheme was selected from the non-inferior solution set through using the grey relational analysis method, which reduces slide-seat’s mass and improves its static and dynamic performance considerably. After conducting static and dynamic experimental study on the slide-seats before and after multi-objective optimization design, the rationality and feasibility of the multi-objective optimization design method for the machine tool’s structural parts were verified.
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Citations
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A CAD/CAE-integrated structural design framework for machine tools
TL;DR: In this article, an integrated framework for design and optimization of a machine tool structure is presented, which can greatly improve the design quality and efficiency by combining knowledge-based design and multi-stage optimization with the CAD/CAE integration technique.
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Structural dynamic design optimization and experimental verification of a machine tool
TL;DR: The Adaptive Growth Method which is based on the growth mechanism of natural branch systems is adopted to design the inner stiffener layout of structures, and an optimization strategy for the holistic machine tool utilizing dynamic sensitivity analysis is studied.
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Study on lightweight structural optimization design system for gantry machine tool
Shihao Liu,Yanbin Du,Mao Lin +2 more
TL;DR: The research results show that the constructed lightweight structural optimization design system of the gantry machine tool has high engineering practicality and beneficial to save the manufacturing cost.
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A novel Lap-MRF method for large aperture mirrors
Feng Guan,Feng Guan,Hao Hu,Hao Hu,Shengyi Li,Shengyi Li,Zhongyan Liu,Xiaoqiang Peng,Xiaoqiang Peng,Feng Shi,Feng Shi +10 more
TL;DR: In this paper, a novel magnetorheological finishing (MRF) method, which is named Lap-MRF, is proposed in which a lap instead of a large polishing wheel is used to expand the polishing area, which improves the material removal rate largely.
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Global sensitivity analysis and multi-objective optimisation of loading path in tube hydroforming process based on metamodelling techniques
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Loading path optimization of a hydroformed part using multilevel response surface method
TL;DR: In this article, a multilevel response surface method (MLRSM) has been used to model the responses from the finite element analysis, and then, the obtained model is used to optimize the process.
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•Journal Article
Multi-objective particle swarm optimization algorithm based on crowding distance sorting and its application
TL;DR: Comparison results illustrated that this algorithm outperformed Strength Pareto Evolutionary Algorithm 2(SPEA2) in the convergence and diversity characteristics of Pare to optimal front with shorter computation time, higher efficiency and robustness.
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