• Title/Summary/Keyword: mixed Weibull distribution

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고장 보고율을 이용한 현장 수명자료 분포의 모수추정

  • Park, Tae-Ung;Kim, Yeong-Bok;Lee, Chang-Hun
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2005.05a
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    • pp.678-685
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    • 2005
  • Estimating parameters of the lifetime distribution is investigated when field failure data are not completely reported. To take into account the reality and the accuracy of the estimates in such a case, the failure reporting probability is incorporated in estimating parameters. Firstly, method of maximum likelihood estimate(MLE) is used to estimate parameters of the lifetime distribution when failure reporting probability is known. Secondly, Expectation and Maximization(EM) algorithm is used to estimate the failure reporting probability and parameters of the lifetime distribution simultaneously when failure reporting probability is unknown. For both case, procedures of estimation are illustrated for single Weibull distribution and mixed Weibull distribution. Simulation results show that MLE obtained by the proposed method is more accurate than the conventional MLE.

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A Study on the Application of Weibull Survivor Curves to Estimate Mortality Characteristics of Industrial Property (산업설비의 내용년수 추정을 위한 Weibull 생존곡선의 적용)

  • 오현승
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.23 no.57
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    • pp.113-122
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    • 2000
  • A mixture of two distributions, each belonging to the same known Weibull distributions, is proposed and a simple graphical method for estimating the parameters of the Weibull distribution is applied. It appears from the results of this study that the mixed Weibull distribution is an appropriate expression for describing industrial property mortality characteristics.

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Estimating Parameters of Field Lifetime Data Distribution Using the Failure Reporting Probability (고장 보고율을 이용한 현장 수명자료 분포의 모수추정)

  • Kim, Young Bok;Lie, Chang Hoon
    • Journal of Korean Institute of Industrial Engineers
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    • v.33 no.1
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    • pp.52-60
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    • 2007
  • Estimating parameters of the lifetime distribution is investigated when field failure data are not completelyreported. To take into account the reality and the accuracy of the estimates in such a case, the failure reportingprobability is incorporated in estimating parameters, Firstly, method of maximum likelihood estimate (MLE) isused to estimate parameters of the lifetime distribution when failure reporting probability is known, Secondly,Expectation and Maximization (EM) algorithm is used to estimate the failure reporting probability and parame-ters of the lifetime distribution simultaneously when failure reporting probability is unknown. For both cases,procedures of estimation are illustrated for single Weibull distribution and mixed Weibull distribution. Simula-tion results show that MLE obtained by the proposed method is more accurate than the conventional MLE.

Development of Mixed Reliability Demonstration Test Plans (혼합형 신뢰성 실증시험계획의 개발)

  • Seo, Sun-Keun
    • Journal of Applied Reliability
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    • v.15 no.3
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    • pp.170-175
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    • 2015
  • Reliability demonstration tests (RDT's) are widely employed in design verification and process validation stages of industry. New mixed attribute-variable RDT plans that compromise demerits of the corresponding zero and zero or one failure plans which are common in practice are developed for the exponential distribution. The proposed mixed plans are compared with the typical RDT plans in terms of probability of acceptance and expected test termination time. A numerical example is provided to illustrate the mixed plans and a procedure to extend these plans to the Weibull distribution with known shape parameter is also presented.

Optimal Burn-In under Warranty

  • Kim, Kuinam-J;Park, Chi-Yeon
    • Journal of the Korea Safety Management & Science
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    • v.1 no.1
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    • pp.135-143
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    • 1999
  • This paper discusses an optimal burn-in procedure to minimize total costs based on the assumption that the failure rate pattern follows a bimodal mixed Weibull distribution. The procedure will consider warranty period as a factor of the total expected bum-in cost. A cost model is formulated to find the optimal burn-in time that minimizes the expected burn-in cost. Conditional reliability for warranty period will be discussed. An illustrative example is included to show how to use the cost model in practice.

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A Piecewise Weibull Distribution in Reliability and its Estimation (신뢰성이론에서의 피스와이즈 와이블분포와 그 추정)

  • Jeong, Hai-Sung
    • Journal of Korean Society for Quality Management
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    • v.24 no.2
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    • pp.65-76
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    • 1996
  • In general, most industrial products exhibit bath-tub shaped curve for their failure rate functions. This distributional life model can be obtained by the Piecewise Weibull distribution. The least squares, maximum likelihood, and mixed methods of estimating the parameters of the Piecewise Weibull distribution are compared. The comparison is made by using the empirical mean squared errors of (a) the parameter estimates and (b) the estimated change-points, to summarize the results of 1000 simulated samples of three sizes - each 100, 150 and 200. The results are that the mixed method estimation comes to be the best as the sample sizes increase.

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Sensitivity Analysis of Burn-in Model considering Bimodal-Mixed Weibull Distribution under Free Warranty Policy (무료보증정책하에서 이봉-혼합 와이블 분포를 고려한 Burn-in 모형의 민감도 분석)

  • Song Suh-Ill;Jo Young-Chan;Park Hyun-Kyu;Shon Han-Deak
    • Proceedings of the Korean Society for Quality Management Conference
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    • 1998.11a
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    • pp.544-555
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    • 1998
  • Although the bimodal mixed weibull distribution is used to developing burn-in model widely, the failure times for a component or a system is often truncated at some time, T, due to the obsolescence in the electronics industry. In this paper, we will determine minimum total cost and burn-in time by using the bimodal mixed weibull distribution and the truncated bimodal mixed weibull distribution under the free warranty policy. The results of this study are summarized as follows. First, when products or system is not repairable, the width of the change of burn-in time can be larger by ${\beta}_1,\;{\beta}_2$ Second, if burn-in time become longer, it will be impossible to consider the bum-in in a long time, and in this case, the burn-in time should be shorten by the acceleration burn-in. Third, in case that opportunity loss cost or repair cost is exceed the warranty cost, or the total cost of considering burn-in is larger than that of not considering burn-in, it is not existed burn-in time which makes total cost to minimize. Forth, the shorter life-cycle of product, the more burn-in times will be decreased and the cost in considering burn-in will be increased

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Estimation of Weibull Lifetimes in Mixed Replacement Model (와이블분포를 따르는 수명시간의 추정)

  • 이태섭
    • Journal of the military operations research society of Korea
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    • v.22 no.2
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    • pp.215-226
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    • 1996
  • The estimation of lifetimes are examined when the distribution of lifetimes are Weibull. It is assumed that, due to physical restrictions and/or economic requirements, the lifetimes are investigated only at certain time intervals during the test period with 'mixed replacement' experiment, even though it is well known that 'with replacement' experiment produces better accuracy than 'without replacement' one. The maximum likelihood estimators are derived through the iterative method like as Lawless(1982). Also Cramer-Rao lower bounds are found as the asymptotic variances of the estimates.

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Optimal Burn-In under Warranty

  • Kim, Kui-Nam J.;Park, Chi-Yeon;Hong, Chan-Geui
    • Proceedings of the Safety Management and Science Conference
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    • 1999.11a
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    • pp.147-155
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    • 1999
  • This paper discusses an optimal burn-in procedure to minimize total costs based on the assumption that the failure rate pattern follows a bimodal mixed Weibull distribution. The procedure will consider warranty period as a factor of the total expected burn-in cost. A cost model is formulated to find the optimal burn-in time that minimizes the expected burn-in cost. Conditional reliability for warranty period will be discussed. An illustrative example is included to show how to use the cost model in practice.

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