Assessing the lifetime performance indices of products with the Burr XII and Extreme Value distributions based on doubly type II censored samples
碩士 === 淡江大學 === 統計學系碩士班 === 100 === In recent years, many process capability indices (PCIs) have been widely used in qality monitoring by many manufacturing industries.In practice, the lifetime performance index CL is utilized to measure lifetime performance for products with some lifetime distr...
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ndltd-TW-100TKU053370142015-10-13T21:27:34Z http://ndltd.ncl.edu.tw/handle/33518545117871472939 Assessing the lifetime performance indices of products with the Burr XII and Extreme Value distributions based on doubly type II censored samples 利用雙型二設限樣本評估具有Burr XII分配與極值分配之產品的壽命績效指標 I-Jou Chang 張逸柔 碩士 淡江大學 統計學系碩士班 100 In recent years, many process capability indices (PCIs) have been widely used in qality monitoring by many manufacturing industries.In practice, the lifetime performance index CL is utilized to measure lifetime performance for products with some lifetime distributions, where L is the lower specification limit. In lifetime testing experiments, we may not be able to obtain a complete sample due to time limitation or other restrictions. Therefore, censored samples arise in practice. This research constructs an unbiased estimator of CL based on the doubly type II censored sample from Burr XII and Extreme value distribution,respectively.The unbiased estimator of CL is then utilized to develop a hypothesis testing procedure and the confidence interval in the condition of known L. The purchasers can then employ the new hypothesis and the confidence interval to determine whether the lifetime performance of products adhere to the required level. Chin-Chuan Wu 吳錦全 2012 學位論文 ; thesis 98 zh-TW |
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碩士 === 淡江大學 === 統計學系碩士班 === 100 === In recent years, many process capability indices (PCIs) have been widely used in qality monitoring by many manufacturing industries.In practice, the lifetime performance index CL is utilized to measure lifetime performance for products with some lifetime distributions, where L is the lower specification limit. In lifetime testing experiments, we may not be able to obtain a complete sample due to time limitation or other restrictions. Therefore, censored samples arise in practice.
This research constructs an unbiased estimator of CL based on the doubly type II censored sample from Burr XII and Extreme value distribution,respectively.The unbiased estimator of CL is then utilized to develop a hypothesis testing procedure and the confidence interval in the condition of known L. The purchasers can then employ the new hypothesis and the confidence interval to determine whether the lifetime performance of products adhere to the required level.
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author2 |
Chin-Chuan Wu |
author_facet |
Chin-Chuan Wu I-Jou Chang 張逸柔 |
author |
I-Jou Chang 張逸柔 |
spellingShingle |
I-Jou Chang 張逸柔 Assessing the lifetime performance indices of products with the Burr XII and Extreme Value distributions based on doubly type II censored samples |
author_sort |
I-Jou Chang |
title |
Assessing the lifetime performance indices of products with the Burr XII and Extreme Value distributions based on doubly type II censored samples |
title_short |
Assessing the lifetime performance indices of products with the Burr XII and Extreme Value distributions based on doubly type II censored samples |
title_full |
Assessing the lifetime performance indices of products with the Burr XII and Extreme Value distributions based on doubly type II censored samples |
title_fullStr |
Assessing the lifetime performance indices of products with the Burr XII and Extreme Value distributions based on doubly type II censored samples |
title_full_unstemmed |
Assessing the lifetime performance indices of products with the Burr XII and Extreme Value distributions based on doubly type II censored samples |
title_sort |
assessing the lifetime performance indices of products with the burr xii and extreme value distributions based on doubly type ii censored samples |
publishDate |
2012 |
url |
http://ndltd.ncl.edu.tw/handle/33518545117871472939 |
work_keys_str_mv |
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