The Theoretical and Experimental Research on Accelerated Life Test of Collapsible Fabric Tank Storage Life Based on Reliability

2013 ◽  
Vol 853 ◽  
pp. 590-595
Author(s):  
Shi Fu Zhang ◽  
Tian Min Liu ◽  
Qi Xin Zhang ◽  
Xiu Mei Shu ◽  
Shi Qiang Song ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Evaluation Method ◽  
Storage Temperature ◽  
Hypothesis Test ◽  
Likelihood Estimation ◽  
Storage Life ◽  
Accelerated Life Test ◽  
Model Parameters ◽  
Failure Data ◽  
Tank Storage

Collapsible fabric tank which is an important part of oil equipment equips army with large reserves. The evaluation of collapsible fabric tank storage life, lacking of corresponding test data support, is on the conservative side, which causes manage and storage uncertainty to army. Based on reliability theory, storage life evaluation method of collapsible fabric tank is established. Failure data of collapsible fabric tank under several accelerated stress levels is obtained. According to probability distribution hypothesis test, Weibull distribution has better goodness of fit and life prediction model is obtained. A new maximum likelihood estimation is proposed as statistical analysis method and model parameters are evaluated. Storage life and reliability index of collapsible fabric tank under normal storage temperature are evaluated which brings collapsible fabric tank storage life potential into play and improves use economy.

scholarly journals Statistical Reliability Assessment for Small Sample of Failure Data of Dumper Diesel Engines Based on Power Law Process and Maximum Likelihood Estimation

2021 ◽  
Vol 11 (12) ◽  
pp. 5387
Author(s):  
Brajeshkumar Kishorilal Dinkar ◽  
Alok Kumar Mukhopadhyay ◽  
Somnath Chattopadhyaya ◽  
Shubham Sharma ◽  
Firoz Alam ◽  
...  
Keyword(s):  
Diesel Engines ◽  
Hypothesis Test ◽  
Meta Analysis ◽  
Likelihood Estimation ◽  
Small Sample ◽  
Trend Test ◽  
Failure Data ◽  
Subsystem Level ◽  
Dump Trucks ◽  
Engine Failure

Dumpers or dump trucks are used all over the world to move overburden from many opencast mines. Diesel engines are the main driving force behind the trucks. The frequency of damage due to the failure of diesel engines is enormous. Therefore, efforts are necessary to analyze failure to reduce the downtime periods. A detailed analysis of engine failure at the subsystem level needs to be done. Reliability analysis and maintenance planning remain the norm in this regard. The obstacle faced while analysing the reliability of dumpers was the availability of a large number of data failures. In this paper, this issue is addressed by using Common Beta Hypothesis test and Meta-analysis test. The engine is divided into five subsystems. The result shows that all five subsystems pass the CBH test and Meta-analysis test. Accordingly, the failure data is grouped. The trend test of grouped failure data shows that the Failure data of two subsystems follows the independent and identically distributed characteristics while the remaining three do not follow it. The reliability is estimated for all five subsystems. Finally, fuel supply subsystems show the highest reliability while the lowest value is seen for self-starting subsystems.

scholarly journals The ArcTan Lomax Distribution with Properties and Applications

2021 ◽  
pp. 117-125
Author(s):  
Arun Kumar Chaudhary ◽  
Vijay Kumar
Keyword(s):  
Survival Analysis ◽  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Goodness Of Fit ◽  
Continuous Distribution ◽  
Likelihood Estimation ◽  
Model Parameters ◽  
Lomax Distribution ◽  
And Mathematics

Here, in this paper, a continuous distribution called ArcTan Lomax distribution with three-parameter has been introduced along with some relevant properties of statistics and mathematics pertaining to the distribution. With the help of three established estimations methods including maximum likelihood estimation (MLE), estimation of the presented distribution’s model parameters is done. Also with the help of a real set of data, the distribution’s goodness-of-fit is examined in contrast to some established models in survival analysis.

scholarly journals Modified generalized marshall-olkin family of distributions

2019 ◽  
Vol 7 (1) ◽  
pp. 18
Author(s):  
Muhammad Aslam ◽  
Zawar Hussain ◽  
Zahid Asghar
Keyword(s):  
Maximum Likelihood ◽  
Goodness Of Fit ◽  
Maximum Likelihood Method ◽  
Likelihood Estimation ◽  
Likelihood Method ◽  
Model Parameters ◽  
Data Sets ◽  
Goodness Of Fit Tests ◽  
New Family ◽  
Family Of Distributions

In this article, we propose a new family of distributions using the T-X family named as modified generalized Marshall-Olkin family of distributions. Comprehensive mathematical and statistical properties of this family of distributions are provided. The model parameters are estimated by maximum likelihood method. The maximum likelihood estimation under Type-II censoring is also discussed. Two lifetime data sets are used to show the suitability and applicability of the new family of distributions. For comparison purposes, different goodness of fit tests are used.  

Estimation and Inference Are Missing Data Problems: Unifying Social Science Statistics via Bayesian Simulation

2000 ◽  
Vol 8 (4) ◽  
pp. 307-332 ◽  
Author(s):  
Simon Jackman
Keyword(s):  
Missing Data ◽  
Social Science ◽  
Goodness Of Fit ◽  
Linear Models ◽  
Likelihood Estimation ◽  
Model Parameters ◽  
Data Sampling ◽  
Fit Statistics ◽  
Bill Cosponsorship ◽  
Bayesian Simulation

Bayesian simulation is increasingly exploited in the social sciences for estimation and inference of model parameters. But an especially useful (if often overlooked) feature of Bayesian simulation is that it can be used to estimate any function of model parameters, including “auxiliary” quantities such as goodness-of-fit statistics, predicted values, and residuals. Bayesian simulation treats these quantities as if they were missing data, sampling from their implied posterior densities. Exploiting this principle also lets researchers estimate models via Bayesian simulation where maximum-likelihood estimation would be intractable. Bayesian simulation thus provides a unified solution for quantitative social science. I elaborate these ideas in a variety of contexts: these include generalized linear models for binary responses using data on bill cosponsorship recently reanalyzed in Political Analysis, item—response models for the measurement of respondent's levels of political information in public opinion surveys, the estimation and analysis of legislators' ideal points from roll-call data, and outlier-resistant regression estimates of incumbency advantage in U.S. Congressional elections

scholarly journals Half Logistic Exponential Extension Distribution with Properties and Applications

2020 ◽  
Vol 9 (3) ◽  
pp. 506-512
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Hazard Rate ◽  
Goodness Of Fit ◽  
Likelihood Estimation ◽  
Real Data ◽  
Model Parameters ◽  
Type I ◽  
Proposed Model ◽  
New Distribution

In this article, we have introduced a new distribution based on type I half logistic-G family and exponential extension as a base distribution known as Half Logistic Exponential Extension (HLEE) distribution. The statistical properties of this model are also explored, such as the behavior of probability density, hazard rate, and quantile functions are investigated. The Maximum likelihood estimation (MLE) method is used to estimate model parameters. For the potentiality of the proposed model we have compared the goodness of fit with some others models. We have proven the importance and flexibility of the new distribution in modeling with real data applications empirically.

scholarly journals Assessment of Homodyned K Distribution Modeling Ultrasonic Speckles from Scatterers with Varying Spatial Organizations

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Xiao Hu ◽  
Yufeng Zhang ◽  
Li Deng ◽  
Guanghui Cai ◽  
Qinghui Zhang ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Goodness Of Fit ◽  
Human Subjects ◽  
Likelihood Estimation ◽  
Model Parameters ◽  
Practical Applications ◽  
Distribution Modeling ◽  
Gamma Distributions ◽  
Carotid Arterial

Objective. This paper presents an assessment of physical meanings of parameter and goodness of fit for homodyned K (HK) distribution modeling ultrasonic speckles from scatterer distributions with wide-varying spatial organizations. Methods. A set of 3D scatterer phantoms based on gamma distributions is built to be implemented from the clustered to random to uniform scatterer distributions continuously. The model parameters are obtained by maximum likelihood estimation (MLE) from statistical histograms of the ultrasonic envelope data and then compared with those by the optimally fitting models chosen from three single distributions. Results show that the parameters of the HK distribution still present their respective physical meanings of independent contributions in the scatterer distributions. Moreover, the HK distribution presents better goodness of fit with a maximum relative MLE difference of 6.23% for random or clustered scatterers with a well-organized periodic structure. Experiments based on ultrasonic envelope data from common carotid arterial B-mode images of human subjects validate the modeling performance of HK distribution. Conclusion. We conclude that the HK model for ultrasonic speckles is a better choice for characterizing tissue with a wide variety of spatial organizations, especially the emphasis on the goodness of fit for the tissue in practical applications.

NBR’s Storage Life Prediction Based on the Accelerated Life Test

2012 ◽  
Vol 476-478 ◽  
pp. 2260-2265
Author(s):  
Li Zhao ◽  
Wei Fang Zhang ◽  
Yu Chen ◽  
Mei Li Ding ◽  
Ming Yuan Yang
Keyword(s):  
Stress Relaxation ◽  
Storage Temperature ◽  
Storage Life ◽  
Accelerated Life Test ◽  
Relaxation Coefficient ◽  
Accelerated Life Tests ◽  
Accelerated Life ◽  
Life Tests ◽  
The Relationship ◽  
And Storage

Based on the nitrile rubber accelerated life tests, using the stress relaxation coefficient changes as the aging performance indicators, the relationship between NBR’s stress relaxation and aging time was given ,and also the NBR’s aging dynamic equation was established to predict of the material’s storage life in the normal storage temperature and storage time ,which can be used as reference to predicte NBR’s storage life .

scholarly journals A new modified Lehmann type – II G class of distributions: exponential distribution with theory, simulation, and applications to engineering sector

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 483
Author(s):  
Oluwafemi Samson Balogun ◽  
Muhammad Zeshan Arshad ◽  
Muhammad Zafar Iqbal ◽  
Madiha Ghamkhar
Keyword(s):  
Exponential Distribution ◽  
Goodness Of Fit ◽  
Likelihood Estimation ◽  
Quantile Function ◽  
Model Parameters ◽  
Type Ii ◽  
Reliability Engineering ◽  
New Members ◽  
Anderson Darling ◽  
Von Mises

Background: Modeling against non-normal data a challenge for theoretical and applied scientists to choose a lifetime model and expect to perform optimally against experimental, reliability engineering, hydrology, ecology, and agriculture sciences, phenomena. Method: We have introduced a new G class that generates relatively more flexible models to its baseline and we refer to it as the new modified Lehmann Type – II (ML–II) G class of distributions. A list of new members of ML–II-G class is developed and as a sub-model the exponential distribution, known as the ML-II-Exp distribution is considered for further discussion. Several mathematical and reliability characters along with explicit expressions for moments, quantile function, and order statistics are derived and discussed in detail. Furthermore, plots of density and hazard rate functions are sketched out over the certain choices of the parametric values. For the estimation of the model parameters, we utilized the method of maximum likelihood estimation. Results: The applicability of the ML–II–G class is evaluated via ML–II–Exp distribution. ML–II–Exp distribution is modeled to four suitable lifetime datasets and the results are compared with the well-known competing models. Some well recognized goodness–of–fit including -Log-likelihood (-LL), Anderson-Darling (A*), Cramer-Von Mises (W*), and Kolmogorov-Smirnov (K-S) test statistics are considered for the selection of a better fit model. Conclusion: The minimum value of the goodness–of–fit is the criteria of a better fit model that the ML–II–Exp distribution perfectly satisfies. Hence, we affirm that the ML–II–Exp distribution is a better fit model than its competitors.

scholarly journals Accelerated Life Test Method for the Doubly Truncated Burr Type XII Distribution

Mathematics ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 162
Author(s):  
Hua Xin ◽  
Zhifang Liu ◽  
Yuhlong Lio ◽  
Tzong-Ru Tsai
Keyword(s):  
Bayesian Estimation ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Estimation Procedure ◽  
Accelerated Life Test ◽  
Model Parameters ◽  
Life Test ◽  
Accelerated Life ◽  
Estimation Procedures ◽  
Maximum Likelihood Estimation Method

The Burr type XII (BurrXII) distribution is very flexible for modeling and has earned much attention in the past few decades. In this study, the maximum likelihood estimation method and two Bayesian estimation procedures are investigated based on constant-stress accelerated life test (ALT) samples, which are obtained from the doubly truncated three-parameter BurrXII distribution. Because computational difficulty occurs for maximum likelihood estimation method, two Bayesian procedures are suggested to estimate model parameters and lifetime quantiles under the normal use condition. A Markov Chain Monte Carlo approach using the Metropolis–Hastings algorithm via Gibbs sampling is built to obtain Bayes estimators of the model parameters and to construct credible intervals. The proposed Bayesian estimation procedures are simple for practical use, and the obtained Bayes estimates are reliable for evaluating the reliability of lifetime products based on ALT samples. Monte Carlo simulations were conducted to evaluate the performance of these two Bayesian estimation procedures. Simulation results show that the second Bayesian estimation procedure outperforms the first Bayesian estimation procedure in terms of bias and mean squared error when users do not have sufficient knowledge to set up hyperparameters in the prior distributions. Finally, a numerical example about oil-well pumps is used for illustration.

scholarly journals A generalized Gompertz growth model with applications and related birth-death processes

2020 ◽  
Author(s):  
Majid Asadi ◽  
Antonio Di Crescenzo ◽  
Farkhondeh A. Sajadi ◽  
Serena Spina
Keyword(s):  
Growth Model ◽  
Growth Curve ◽  
Goodness Of Fit ◽  
Gompertz Model ◽  
Death Process ◽  
Birth Process ◽  
Failure Data ◽  
First Case ◽  
Gompertz Growth Model ◽  
Birth Death

AbstractIn this paper, we propose a flexible growth model that constitutes a suitable generalization of the well-known Gompertz model. We perform an analysis of various features of interest, including a sensitivity analysis of the initial value and the three parameters of the model. We show that the considered model provides a good fit to some real datasets concerning the growth of the number of individuals infected during the COVID-19 outbreak, and software failure data. The goodness of fit is established on the ground of the ISRP metric and the $$d_2$$ d 2 -distance. We also analyze two time-inhomogeneous stochastic processes, namely a birth-death process and a birth process, whose means are equal to the proposed growth curve. In the first case we obtain the probability of ultimate extinction, being 0 an absorbing endpoint. We also deal with a threshold crossing problem both for the proposed growth curve and the corresponding birth process. A simulation procedure for the latter process is also exploited.

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