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...

Full description

Bibliographic Details
Main Authors: Yu-Hsien Peng, 彭裕賢
Other Authors: Miao-Lin Wang
Format: Others
Language:zh-TW
Published: 2008
Online Access:http://ndltd.ncl.edu.tw/handle/44510243255701027318
id ndltd-TW-096MHIT5031014
record_format oai_dc
spelling 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
collection NDLTD
language zh-TW
format Others
sources NDLTD
description 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.
author2 Miao-Lin Wang
author_facet 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
work_keys_str_mv AT yuhsienpeng optimizationforhighspeedmachiningdesignusingantcolonyoptimization
AT péngyùxián optimizationforhighspeedmachiningdesignusingantcolonyoptimization
AT yuhsienpeng yǐqúnzuìjiāhuàyǎnsuànfǎyīngyòngyúgāosùgōngjùjīzuìjiāhuàshèjì
AT péngyùxián yǐqúnzuìjiāhuàyǎnsuànfǎyīngyòngyúgāosùgōngjùjīzuìjiāhuàshèjì
_version_ 1717741637564628992