邱志洲952221E027072MY3(第1å&sup

邱志洲952221E027072MY3(第1å&sup

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Unformatted text preview: 1 運用類神經網路與層級貝氏法在建構可靠度預估模式上之應用 (1/3) Construction of a Reliability Prediction Model Using Neural Network and Hierarchical Bayesian Approach (1/3) 計劃編號: NSC 95-2221-E-027-072MY3 執行期限: 95 年 8 月 1 日 至 96 年 7 月 31 日 主持人:邱志洲 執行機構及單位名稱:商業自動化與管理研究所 , 台北科技大學 摘 要 隨著現今科技的快速發展,顧客 對產品品質的要求亦隨之不斷的提 升,生產者必須在有限的時間內,評 估並改善產品的可靠度,是以如何選 擇一個適當的可靠度量測方法,對業 界而言,是一個相當重要的問題。截 至目前為止不管是業界或學界在進行 資料分析時,大多採用傳統的統計分 析技術,在本研究中,我們嘗試提出 一個更一般化的資料分析技術-- 層級 貝 氏 模 式 (Hierarchical Bayesian Model)-- 來量測產品衰退的過程。而在 模式建構的過程中,我們利用 Markov Chain Monte Carlo (MCMC) 來進行模 式中參數的估計。此外,論文中亦將 針對可靠度模式的失效時間分配型態 進行建構並驗證該分配之適合度及其 產品壽命預測值的準確性。 關鍵字 :層級貝氏模式、衰退過程、 失效時間、 Markov Chain Monte Carlo Abstract The reliability for some devices with few or no failures in their life tests becomes very hard to access if a traditional life test which records only time-to-failure was utilized. To solve this problem, the analysis of the over time degradation processes is always considered in the practical cases. The realization of the degradation processes is expected to be represented by the constructed degradation model. Based on the developed models, the failure times for devices and the time-to-failure distribution can be estimated. In this paper, a hierarchical Bayesian model (HBM) with autocorrelated residuals is proposed to construct a broad class of degradation models. For finding the appropriate estimates of model ’s parameters, the Markov Chain Monte Carlo (MCMC) algorithm is applied. A fatigue crack growth data is used as an example for illustrating the modeling procedure of HBM. By specifying the coefficients in the HBM, we successfully identify the heterogeneity varying across individual products. In additions, the prediction intervals of future degradation processes for evaluating the prediction accuracy are provided. Moreover, the time-to-failure distribution is further estimated and the reliability bounds have been constructed. Keywords : Hierarchical Bayesian Model, Degradation Process, Failure Time, Markov Chain Monte Carlo 壹、緒論 隨著產品品質的不斷提昇,消費 者對各部份的零組件要求亦日趨嚴 格,再加上面對全球化的競爭壓力 下,今日的廠商已逐步的針對如何生 產出具有高可靠度的產品進行研發。 只是在進行產品可靠度的研究當中, 如何準確的取得產品可靠度資訊是一...
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邱志洲952221E027072MY3(第1å&sup

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