scholarly journals RELIABILITY ANALYSIS IN CEMENT MILLS OF BERBER CEMENT FACTORY

2021 ◽  
Vol 6 (4) ◽  
Author(s):  
Engineer Nafea Mostafa Muki Nafea ◽  
Dr. Osama Mohammed Elmardi Suleiman
Keyword(s):  
Shape Parameter ◽  
Probability Distributions ◽  
Operating Time ◽  
Heating System ◽  
Product System ◽  
Daily Production ◽  
Cement Factory ◽  
Data Measurement ◽  
Daily Report ◽  
Distribution Parameters

Reliability is the probability that a product, system, or service will perform its intended function adequately for a specified period, or will operate in a defined environment without failure. In this research, the reliability of Berber cement mill studied. The data collected from the information section of Berber cement factory related to the milling section. It includes the daily production reports, the breakdown and the operating time. The operating time between two failures (TTF) was calculated from the daily report of the mill and then a match was made for the data with the probability distributions to find out what is the probability distribution corresponding to the distribution of these data. The best distribution is the Weibull distribution. the Minitab software was applied and then the distribution parameters for the data (measurement parameters c and the shape parameter d) were obtained and then the reliability of each part of the mill were calculated for each hour and the reliability of the system was calculated as a whole. The study found that the reliability of the system is 75% at the first hour of operation. It decreased during continuous operation to 58% due to the poor reliability of the heating system, which has a reliability of 72% and the reliability of the conveying and feeding belts of the clinker, which have a reliability of 75%.

Utilizarea teoriei valorilor extreme în climatologie

2019 ◽  
Author(s):  
Valentin Raileanu ◽  
Keyword(s):  
Maximum Likelihood ◽  
Extreme Values ◽  
Probability Distributions ◽  
Simulated Data ◽  
Likelihood Estimation ◽  
R Software ◽  
Data Set ◽  
Data Format ◽  
Generalized Pareto ◽  
Distribution Parameters

The article briefly describes the history and fields of application of the theory of extreme values, including climatology. The data format, the Generalized Extreme Value (GEV) probability distributions with Bock Maxima, the Generalized Pareto (GP) distributions with Point of Threshold (POT) and the analysis methods are presented. Estimating the distribution parameters is done using the Maximum Likelihood Estimation (MLE) method. Free R software installation, the minimum set of required commands and the GUI in2extRemes graphical package are described. As an example, the results of the GEV analysis of a simulated data set in in2extRemes are presented.

scholarly journals Moment based Estimation for the Shape Parameters, Effect it on Some Probability Statistical Distributions Using the Moment Method and Maximum Likelihood Method

2020 ◽  
Vol 5 (6) ◽  
pp. 979-986
Author(s):  
Hassan Tawakol A. Fadol
Keyword(s):  
Maximum Likelihood ◽  
Shape Parameter ◽  
Maximum Likelihood Method ◽  
Probability Distributions ◽  
Estimation Method ◽  
Simulation Method ◽  
Likelihood Method ◽  
Inductive Method ◽  
Binomial Distributions ◽  
Best Estimate

The purpose of this paper was to identify the values of the parameters of the shape of the binomial, bias one and natural distributions. Using the estimation method and maximum likelihood Method, the criterion of differentiation was used to estimate the shape parameter between the probability distributions and to arrive at the best estimate of the parameter of the shape when the sample sizes are small, medium, The problem was to find the best estimate of the characteristics of the society to be estimated so that they are close to the estimated average of the mean error squares and also the effect of the estimation method on estimating the shape parameter of the distributions at the sizes of different samples In the values of the different shape parameter, the descriptive and inductive method was selected in the analysis of the data by generating 1000 random numbers of different sizes using the simulation method through the MATLAB program. A number of results were reached, 10) to estimate the small shape parameter (0.3) for binomial distributions and Poisson and natural and they can use the Poisson distribution because it is the best among the distributions, and to estimate the parameter of figure (0.5), (0.7), (0.9) Because it is better for binomial binomial distributions, when the size of a sample (70) for a teacher estimate The small figure (0.3) of the binomial and boson distributions and natural distributions can be used for normal distribution because it is the best among the distributions.

scholarly journals A comparison of three parameter estimation methods of the gamma distribution of annual maximum low flow duration and deficit in the Upper Vistula catchment (Poland)

2018 ◽  
Vol 23 ◽  
pp. 00001
Author(s):  
Katarzyna Baran-Gurgul
Keyword(s):  
Gamma Distribution ◽  
Goodness Of Fit ◽  
Probability Distributions ◽  
Low Flow ◽  
Estimation Methods ◽  
Goodness Of Fit Test ◽  
Flow Duration ◽  
Distribution Parameters ◽  
Anderson Darling ◽  
Parameter Estimation Methods

Based on 30-year 24-hour flow sequences at 69 water gauging stations in the Upper Vistula catchment, it was determined that the probability distributions of the low flow duration and its maximum annual deficit can be described by the gamma distribution with the estimated parameters by the methods: MOM, the method of moments, LMOM, the method of linear moments, and MLE, the method of maximum likelihood. The stationarity of the time series was tested by the Mann-Kendall correlation using the Hamed and Rao variance correction. The low flows were defined by the SPA method, with the limit flow Q70%. The quality of the match was tested by the Anderson-Darling goodness of fit test. This test allowed accepting the gamma distribution in all analysed cases, regardless of the method used to estimate the distribution parameters, since the pv (p-values) values were greater than 5% (over 18% for Tmax and 7.5% for Vmax). The highest pv values for individual water gauging stations, as well as the highest 90% Tmax and Vmax quantiles were noted using LMOM to estimate the gamma distribution parameters. The highest 90% Tmax and Vmax quantiles were observed in the uppermost part of the studied area.

scholarly journals Reliability Analysis of the New Exponential Inverted Topp–Leone Distribution with Applications

Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1662
Author(s):  
Ahmed Sayed M. Metwally ◽  
Amal S. Hassan ◽  
Ehab M. Almetwally ◽  
B M Golam Kibria ◽  
Hisham M. Almongy
Keyword(s):  
Reliability Analysis ◽  
Confidence Intervals ◽  
Hazard Rate ◽  
Shape Parameter ◽  
Quantile Function ◽  
Proposed Model ◽  
Distribution Parameters ◽  
Rate Functions ◽  
New Distribution ◽  
Skewness And Kurtosis

The inverted Topp–Leone distribution is a new, appealing model for reliability analysis. In this paper, a new distribution, named new exponential inverted Topp–Leone (NEITL) is presented, which adds an extra shape parameter to the inverted Topp–Leone distribution. The graphical representations of its density, survival, and hazard rate functions are provided. The following properties are explored: quantile function, mixture representation, entropies, moments, and stress–strength reliability. We plotted the skewness and kurtosis measures of the proposed model based on the quantiles. Three different estimation procedures are suggested to estimate the distribution parameters, reliability, and hazard rate functions, along with their confidence intervals. Additionally, stress–strength reliability estimators for the NEITL model were obtained. To illustrate the findings of the paper, two real datasets on engineering and medical fields have been analyzed.

scholarly journals Spectral Probability Distribution of Closed Connected Water and Remote Sensing Statistical Inference for Yellow Substance

2021 ◽  
Vol 87 (11) ◽  
pp. 807-819
Author(s):  
Weining Zhu ◽  
Zeliang Zhang ◽  
Zaiqiao Yang ◽  
Shuna Pang ◽  
Jiang Chen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Probability Distribution ◽  
Statistical Inference ◽  
Probability Distributions ◽  
Landsat 8 ◽  
Inference Models ◽  
Yellow Substance ◽  
Water Classification ◽  
Distribution Scheme ◽  
Distribution Parameters

Unlike traditional remote sensing inversion, this study proposes a new distribution–distribution scheme, which uses statistical inferences to estimate the probability distribution of in-water components based on the probability distribution of the observed spectra. The distribution–distribution scheme has the advantages that it rapidly gives the statistical information of the water of interest, assists the traditional scheme in improving models, and provides more valuable information for water classification and aquatic environment analysis. In this study, based on Landsat-8 images, we analyzed the spectral probability distributions of 688 global waters and found that many of them were normal, log normal, and exponential distributions with diverse patterns in distribution parameters such as the mean, standard deviation, skewness, and kurtosis. Using simulated and field-measured data, we propose a bootstrap-based distribution–distribution scheme and develop some simple remote sensing statistical inference models to estimate the distribution parameters of yellow substance in water.

Productivity of Ontario initial-attack fire crews: results of an expert-judgement elicitation study

2004 ◽  
Vol 34 (3) ◽  
pp. 705-715 ◽  
Author(s):  
Kelvin G Hirsch ◽  
Justin J Podur ◽  
Robert F Janser ◽  
Robert S McAlpine ◽  
David L Martell
Keyword(s):  
Fire Management ◽  
Fire Suppression ◽  
Probability Distributions ◽  
Management Program ◽  
Expert Judgement ◽  
Fire Intensity ◽  
Initial Attack ◽  
Time Estimates ◽  
Elicitation Study ◽  
Distribution Parameters

A structured expert-judgement elicitation technique was used to develop probability distributions for fireline production rates for Ontario's three- and four-person initial-attack crews for seven common fuel types and two distinct levels of fire intensity (i.e., low, 500 kW/m; moderate, 1500 kW/m). A total of 141 crew leaders provided 900 estimates of the minimum, maximum, and most likely (mode) time to construct 610 m (2000 ft) of fireline. This information was used to estimate parameters for beta probability distributions for each individual and scenario. Analysis of variance (ANOVA) of the beta-distribution parameters (α and β) and the three time estimates indicated that fuel type, intensity, crew size, and crew-leader experience all have a statistically significant (p < 0.05) influence on estimated crew productivity. The 28 scenario-specific and 7 aggregated distributions and expected values can be used in many operational fire-management activities (e.g., presuppression planning, initial-attack dispatching, initial-fire assessments) and incorporated into initial-attack containment models. These results also provide baseline data on crew productivity that can be used in larger strategic analyses to gauge the benefits of new fire-suppression equipment and techniques for the entire fire-management program.

Bayes Inference for Drilling Mud Pump Piston Life

2013 ◽  
Vol 295-298 ◽  
pp. 3142-3147 ◽  
Author(s):  
Zi Mei Su ◽  
Yong Quan Sun ◽  
Hui Juan Yuan ◽  
Jian Ying Guo
Keyword(s):  
Confidence Limit ◽  
Shape Parameter ◽  
Likelihood Estimation ◽  
Point Estimation ◽  
Oil Field ◽  
Drilling Mud ◽  
Life Distribution ◽  
Bayes Inference ◽  
Daqing Oil Field ◽  
Distribution Parameters

Bayes confidence limit for domestic drilling mud pump piston life was given. Maximum likelihood estimation of mud pump piston life was discussed under Weibull life distribution. For further, failure mechanism of the same batch mud pump piston was studied, the shape parameter of Weibull distribution was considered to be constant. Bayes point estimation and confidence limit of distribution parameters and mud pump piston life were given, according to field life data collected from Daqing oil field, under non-information priori and conjugate prior information for scale parameter. Example shows the effectiveness of the proposed method.

scholarly journals PerformanceAnalysisof a StandbySystemusing Exponential-Rayleigh-Weibull Distributions

2021 ◽  
Vol 12 (2) ◽  
pp. 2881-2892
Author(s):  
R.K. Bhardwaj, Et. al.
Keyword(s):  
Life Cycle ◽  
Probability Distributions ◽  
Operating Time ◽  
Operation Time ◽  
Performance Indices ◽  
Discrete State ◽  
Time Threshold ◽  
Long Run ◽  
Standby System ◽  
Standby Mode

Abstract: All through the life-cycle of a standby system, it is verychallenging to keep a standby unit workable.It may be fatalif the standby found non-workablewhen needed.This paper evaluates the performance of a standby systemworking under two primary constraintsby underlining the condition of the spare unit in standby mode. The first constraint is the maximum redundancy time for the standby and the second is maximum operation time for the operating unit.The standby unit failson exceeding the maximum time threshold andthereafterthe decision about its repair/replacement is subjected tothe inspection. While after surpassing the maximum operating time limit preventive maintenance is carried outfor the operating unit.To study the long-run performance or life-cycle of the system various performance indices have been analyzed usingthe theory of discrete-state continuous-time semi-Markov regenerative processes.Exponential, Rayleigh and Weibull probability distributions are used to study the system performance numerically.

Sign in / Sign up

Export Citation Format

Share Document