| DC 欄位 |
值 |
語言 |
| DC.contributor | 機械工程學系在職專班 | zh_TW |
| DC.creator | 林忠毅 | zh_TW |
| DC.creator | Jhong-Yi Lin | en_US |
| dc.date.accessioned | 2020-1-21T07:39:07Z | |
| dc.date.available | 2020-1-21T07:39:07Z | |
| dc.date.issued | 2020 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=105353006 | |
| dc.contributor.department | 機械工程學系在職專班 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 公差分析為產品開發階段重要的一環，本論文探討公差分析的方法進一步找出最佳解。在過去，公差分析須進行多次人力的測試和花費大量樣品以達到產品功能性及外觀要求，過於費時又費力，且組裝時是否亦須避免零件產生干涉的問題，加上全球化的競爭之下，產品製造時間必須加快。 | zh_TW |
| dc.description.abstract | Tolerance analysis is an important process during the product development stage. This thesis explores the method of tolerance analysis and further, finds out the best solution. In the past, tolerance analysis needed to do many manual tests and spend quite a number of samples to meet product functionality and appearance requirements. It was too time-consuming and labor-intensive. Besides, there could have problems of interference between parts during assembly processes. Furthermore, considering the global competition, product manufacturing turnover time has to be expedited. | en_US |
| DC.subject | 良率 | zh_TW |
| DC.subject | Yield | en_US |
| DC.title | 蒙地卡羅法及類神經網路應用於公差配置之研究 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | Study on Tolerance Allocation using Monte-Carlo simulation and Neural Network | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |