Optimization for High-Speed Machining Design Using Ant Colony Optimization
碩士 === 明新科技大學 === 工程管理研究所 === 96 === Nowadays the enterprise in order to strives for the survival under the global steep competition, they must pursue the best efficiency regarding each work or the duty, and the production satisfies the product or the service which the customer needs in the shortest...
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ndltd-TW-096MHIT50310142015-10-13T13:43:47Z http://ndltd.ncl.edu.tw/handle/44510243255701027318 Optimization for High-Speed Machining Design Using Ant Colony Optimization 蟻群最佳化演算法應用於高速工具機最佳化設計 Yu-Hsien Peng 彭裕賢 碩士 明新科技大學 工程管理研究所 96 Nowadays the enterprise in order to strives for the survival under the global steep competition, they must pursue the best efficiency regarding each work or the duty, and the production satisfies the product or the service which the customer needs in the shortest time. The high-speed cutting machine industry in order to maintain the competitive ability must shorten time of products design phase look for optimum design parameter, This research develops the algorithm by the ant colony optimization to take the acceleration search best solution. The Ant Colony Optimization algorithm solves some difficult combinatorial optimization problems having a suitable effect already. After being applied ACO algorithm successfully to traveling salesperson problem by such scholars as Dorigo,etc. on the 1991 year, more scholars quote and use this method getting the pretty good performance on different difficulty combinatorial optimization problems. Research perform by ant colony optimization algorithm as project construction, and analyse bearing position of high-speed motorized spindle systems influence in first mode natural frequency, and search the first mode natural frequency by the way of searching in the random area, the starting value which hands over has the best solution treats as which based on each next time, achieved the acceleration optimization design variable the production then reduces the product development time. This research numerical analysis result discovery, MACO algorithms of this research performs in the combinatorial optimization problem of searching four design parameters, and discusses five patterns searches for first mode nature frequency and total time, and obtained the best design data in order is 162.93, 286.16, 552.21 and 568.21 mm, and the best solution is 1009.860 Hz. And the bearing position nearly does not have the correlation regarding FMNF the production. Demonstrated according to the sensitivity analysis result that increase initial preload might enhance FMNF’s value. Miao-Lin Wang 王妙伶 2008 學位論文 ; thesis 71 zh-TW |
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碩士 === 明新科技大學 === 工程管理研究所 === 96 === Nowadays the enterprise in order to strives for the survival under the global steep competition, they must pursue the best efficiency regarding each work or the duty, and the production satisfies the product or the service which the customer needs in the shortest time. The high-speed cutting machine industry in order to maintain the competitive ability must shorten time of products design phase look for optimum design parameter, This research develops the algorithm by the ant colony optimization to take the acceleration search best solution.
The Ant Colony Optimization algorithm solves some difficult combinatorial optimization problems having a suitable effect already. After being applied ACO algorithm successfully to traveling salesperson problem by such scholars as Dorigo,etc. on the 1991 year, more scholars quote and use this method getting the pretty good performance on different difficulty combinatorial optimization problems.
Research perform by ant colony optimization algorithm as project construction, and analyse bearing position of high-speed motorized spindle systems influence in first mode natural frequency, and search the first mode natural frequency by the way of searching in the random area, the starting value which hands over has the best solution treats as which based on each next time, achieved the acceleration optimization design variable the production then reduces the product development time.
This research numerical analysis result discovery, MACO algorithms of this research performs in the combinatorial optimization problem of searching four design parameters, and discusses five patterns searches for first mode nature frequency and total time, and obtained the best design data in order is 162.93, 286.16, 552.21 and 568.21 mm, and the best solution is 1009.860 Hz. And the bearing position nearly does not have the correlation regarding FMNF the production. Demonstrated according to the sensitivity analysis result that increase initial preload might enhance FMNF’s value.
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Miao-Lin Wang |
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Miao-Lin Wang Yu-Hsien Peng 彭裕賢 |
author |
Yu-Hsien Peng 彭裕賢 |
spellingShingle |
Yu-Hsien Peng 彭裕賢 Optimization for High-Speed Machining Design Using Ant Colony Optimization |
author_sort |
Yu-Hsien Peng |
title |
Optimization for High-Speed Machining Design Using Ant Colony Optimization |
title_short |
Optimization for High-Speed Machining Design Using Ant Colony Optimization |
title_full |
Optimization for High-Speed Machining Design Using Ant Colony Optimization |
title_fullStr |
Optimization for High-Speed Machining Design Using Ant Colony Optimization |
title_full_unstemmed |
Optimization for High-Speed Machining Design Using Ant Colony Optimization |
title_sort |
optimization for high-speed machining design using ant colony optimization |
publishDate |
2008 |
url |
http://ndltd.ncl.edu.tw/handle/44510243255701027318 |
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