scholarly journals The maximum order statistic of doubly truncated Inverted Gamma distribution

2021 ◽  
Vol 1999 (1) ◽  
pp. 012094
Author(s):  
Salah H. Abid ◽  
Fadhl J. Kadhim
2018 ◽  
Vol 12 (1) ◽  
pp. 71-77 ◽  
Author(s):  
Anis Iranmanesh ◽  
Kianoosh Fathi Vajargah ◽  
Maryam Hasanzadeh

2019 ◽  
Vol 67 (9) ◽  
pp. 6512-6526 ◽  
Author(s):  
Athira Subhash ◽  
Muralikrishnan Srinivasan ◽  
Sheetal Kalyani

2014 ◽  
Vol 31 (8) ◽  
pp. 950-962 ◽  
Author(s):  
Loganathan Appaia ◽  
Padmanaban Muthu Krishnan ◽  
Sankaran Kalaiselvi

Purpose – The purpose of this paper is the determination of reliability sampling plans in the Bayesian approach assuming that the lifetime distribution is exponential. Design/methodology/approach – Sampling plans are used in manufacturing companies as a tool for carrying out sampling inspections, in order to make decisions about the disposition of many finished products. If the quality characteristic is considered as the lifetime of the products, the plan is known as a reliability sampling plan. In life testing, censoring schemes are adopted in order to save time and cost of life test. The inverted gamma distribution is employed as the natural conjugate prior to the average lifetime of the products. The sampling plans are developed assuming various probability distributions to the lifetime of the products. Findings – The optimum plans n and c are obtained for some sets of values of (p1, a, p2, ß). The selection of sampling plans is illustrated through numerical examples. Originality/value – Results obtained in this paper are original and the study has been done for the first time in this regard. Reliability sampling plans are essential for making decisions either to accept or reject based on the inspection of the sample.


2010 ◽  
Vol 118-120 ◽  
pp. 354-358
Author(s):  
Ying Wu ◽  
Li Yang Xie ◽  
De Cheng Wang ◽  
Ji Zhang Gao

A reliability analysis method for the shiplift gear according to the system-level load-strength interference model is presented. The gear is regarded as a series system with dependent failure and multiple failure models. Its reliability is obtained by calculating the probability that the minimum order statistic of the strengths exceeds the maximum order statistic of repeated random loads. The load probability distribution of gear is then obtained using Monte Carlo on the basis of load information. The contact strength and bending strength are calculated. On the basis of system-level load-strength interference analysis, system reliability of a gear is straightforward built up. Finally, system reliability of a gear is worked out, which shows a high reliability.


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