DC 欄位 |
值 |
語言 |
DC.contributor | 統計研究所 | zh_TW |
DC.creator | 劉哲融 | zh_TW |
DC.creator | Jhe-rong Liou | en_US |
dc.date.accessioned | 2018-8-24T07:39:07Z | |
dc.date.available | 2018-8-24T07:39:07Z | |
dc.date.issued | 2018 | |
dc.identifier.uri | http://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=105225004 | |
dc.contributor.department | 統計研究所 | zh_TW |
DC.description | 國立中央大學 | zh_TW |
DC.description | National Central University | en_US |
dc.description.abstract | 破壞性加速衰變試驗用以評估一次性產品之相關可靠度資訊,其試驗中若欲測量與產品壽命相關品質特徵值,需將產品予以破壞,各測試產品僅有一筆衰變數據。本文考慮具量測誤差混合效應破壞性衰變模型之貝氏可靠度分析,並在貝氏的架構下提出估計虛擬失效時間的方法。以近似衰變分析方法驗證破壞性加速衰變模型所得產品壽命分配之適合性,同時也考慮貝氏適合度檢定下之模型適合度。最後分析五組實際資料,檢視資料中所配適模型之適合度及推論相關可靠度資訊。 | zh_TW |
dc.description.abstract | The accelerated destructive degradation tests are used to assess the reliability information of one-shot products. To measured the quality characteristics related to product lifetime, the product needs to be destroyed during the measurement process, and each test unit has only one degradation data. In this thesis, we consider the Bayesian reliability analysis of the destructive degradation model which is mixed-effect model include measurement errors, and propose a method to estimate the pseudo failure time under the Bayesian framework. The approximate degradation analysis method is used to assess goodness-of-fit of the product life distribution which induced by destructive accelerated degradation model, and also consider the model checking under the Bayesian goodness-of-fit test. Finally, five data set are analyzed, Evaluate the adequacy of the model fitted in the data. and infer relevant reliability information. | en_US |
DC.subject | 破壞性加速衰變試驗 | zh_TW |
DC.subject | 適合度檢定 | zh_TW |
DC.subject | 虛擬失效時間 | zh_TW |
DC.subject | 貝氏方法 | zh_TW |
DC.title | 加速破壞性衰變模型之貝氏適合度檢定 | zh_TW |
dc.language.iso | zh-TW | zh-TW |
DC.title | Bayesian Goodness-of-Fit Tests for Accelerated Destructive Degradation Models | en_US |
DC.type | 博碩士論文 | zh_TW |
DC.type | thesis | en_US |
DC.publisher | National Central University | en_US |