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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/94098

    Title: 逐步設限資料下可靠度與保固之研究
    Other Titles: Reliability and warranty based on progressively censored data
    Authors: 黃炫融;Huang, Syuan-Rong
    Contributors: 淡江大學管理科學學系博士班
    吳碩傑;Wu, Shuo-Jye
    Keywords: 期望實驗時間;最大概似法;後驗預測分配;可靠度抽樣計畫;效用函數;韋伯分配;Expected test time;Maximum likelihood method;Posterior predictive distribution;Reliability sampling plan;Utility function;Weibull distribution
    Date: 2013
    Issue Date: 2014-01-23 14:00:06 (UTC+8)
    Abstract: 傳統設限方法中,型一設限與型二設限常在壽命試驗中被使用,透過僅觀察設限時間前的故障元件來達到縮短實驗時間與降低實驗成本的目的。許多時候我們無法避免從實驗中提早移除部分的存活元件,這種允許元件在實驗尚未結束前即被移除的實驗方式,我們稱之為逐步設限。本篇論文我們以逐步設限方法收集受測元件壽命服從韋伯分配的壽命資料,並根據此類型的設限資料討論以下兩個在實務上重要的問題:(1)保固時間長度與(2)可靠度抽樣計畫。


    In traditional censoring schemes, type-I and type-II censoring are often used in life-testing. To shorten experiment time and reduce experiment cost, failures are collected only before the censoring time. There are many scenarios that we cannot avoid removing some surviving units early from the life test. Such a life test that allows units removed before the termination of the experiment is called progressive censoring. In this dissertation, we consider the progressive censoring and assume the lifetime data are from a Weibull distribution. Based on this type of censored data, we discuss two important optimal design problems in practice: length of warranty and reliability sampling plan.

    In an intensely competitive market, one way by which manufacturers attract consumers to their products is to provide warranties on the products. Consumers are willing to purchase a high-priced product only if they can be assured about the product''s reliability. A longer warranty period
    usually indicates better reliability. However, offering an unlimited warranty is unrealistic because maintaining such a policy needs very high cost. We first derive the maximum likelihood estimator and Bayes estimator for the parameters of the Weibull distribution and then obtain the one-sample and two-sample prediction interval. For the optimal design problem, we consider a combined warranty which is a combination of free-replacement and pro-rata policies. We propose a utility function to determine the optimal warranty length which maximizes the expected value of the utility function. Two examples are discussed to illustrate the
    application of the proposed method.

    For the second problem, we combine the progressive censoring and first-failure censoring to develop a progressive first-failure censoring. Under the progressive first-failure censoring, we propose an approach to establish reliability sampling plans which minimize three different objective
    functions under the constraint of total cost of experiment and given consumer''s and producer''s risks. Some numerical examples, Monte Carlo simulation and the sensitivity analysis are performed to demonstrate the proposed approach.
    Appears in Collections:[管理科學學系暨研究所] 學位論文

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