A Case Study in Intelligent Shoes Pattern Development Technique

碩士 === 朝陽科技大學 === 工業工程與管理系碩士班 === 100 === Shoes pattern development has been an important process for bridging design intentions and production steps. Most designers would prefer hand sketching draft than prototyping a 3D shoe model, and thus making pattern development a time consuming bottleneck. C...

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Main Authors: Li-An Huang, 黃立安
Other Authors: Peng-Cheng Sung
Format: Others
Language:zh-TW
Published: 2012
Online Access:http://ndltd.ncl.edu.tw/handle/95756784425290096837
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spelling ndltd-TW-100CYUT50310442015-10-13T21:17:24Z http://ndltd.ncl.edu.tw/handle/95756784425290096837 A Case Study in Intelligent Shoes Pattern Development Technique 鞋面展開之人工智慧逆向學習技術研究 Li-An Huang 黃立安 碩士 朝陽科技大學 工業工程與管理系碩士班 100 Shoes pattern development has been an important process for bridging design intentions and production steps. Most designers would prefer hand sketching draft than prototyping a 3D shoe model, and thus making pattern development a time consuming bottleneck. Current shoe development process requires three steps, transferring design sketches into a 2D forme, rearranging curve segments on the forme into pieces of shoe patterns, and revising forme segments by test makings. All of the steps are performed by hands with experiences. However on the production side, all processes can be driven and carried out by computer data. It will be profitable to create an automatic procedure that transfers design intentions into usable 2D patterns, for it will save lots of human efforts. This research will apply reverse engineering to scan a 3D shoe example, and acquire a 3D shoe model. An artificial neural network is then created to learn the relationships between the 3D shoe segments and the 2D corresponding pattern segments. A well trained neural network should be able to map the 3D and 2D based on one shoe last size, and will deliver more mappings for the designs of the same shoe last. The results show promising mapping ability on two pairs of shoe examples. Peng-Cheng Sung Tzong-Ming Cheng 宋鵬程 鄭宗明 2012 學位論文 ; thesis 74 zh-TW
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description 碩士 === 朝陽科技大學 === 工業工程與管理系碩士班 === 100 === Shoes pattern development has been an important process for bridging design intentions and production steps. Most designers would prefer hand sketching draft than prototyping a 3D shoe model, and thus making pattern development a time consuming bottleneck. Current shoe development process requires three steps, transferring design sketches into a 2D forme, rearranging curve segments on the forme into pieces of shoe patterns, and revising forme segments by test makings. All of the steps are performed by hands with experiences. However on the production side, all processes can be driven and carried out by computer data. It will be profitable to create an automatic procedure that transfers design intentions into usable 2D patterns, for it will save lots of human efforts. This research will apply reverse engineering to scan a 3D shoe example, and acquire a 3D shoe model. An artificial neural network is then created to learn the relationships between the 3D shoe segments and the 2D corresponding pattern segments. A well trained neural network should be able to map the 3D and 2D based on one shoe last size, and will deliver more mappings for the designs of the same shoe last. The results show promising mapping ability on two pairs of shoe examples.
author2 Peng-Cheng Sung
author_facet Peng-Cheng Sung
Li-An Huang
黃立安
author Li-An Huang
黃立安
spellingShingle Li-An Huang
黃立安
A Case Study in Intelligent Shoes Pattern Development Technique
author_sort Li-An Huang
title A Case Study in Intelligent Shoes Pattern Development Technique
title_short A Case Study in Intelligent Shoes Pattern Development Technique
title_full A Case Study in Intelligent Shoes Pattern Development Technique
title_fullStr A Case Study in Intelligent Shoes Pattern Development Technique
title_full_unstemmed A Case Study in Intelligent Shoes Pattern Development Technique
title_sort case study in intelligent shoes pattern development technique
publishDate 2012
url http://ndltd.ncl.edu.tw/handle/95756784425290096837
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