Engine Failure Data Analysis Method Based on Weibull Distribution Model

2011 ◽  
Vol 128-129 ◽  
pp. 850-854
Author(s):  
Ying Kui Gu ◽  
Jing Li
Keyword(s):  
Weibull Distribution ◽  
Distribution Model ◽  
Parallel Model ◽  
Analysis Method ◽  
Failure Data ◽  
Rod System ◽  
Distribution Parameters ◽  
Engine Failure ◽  
Engine Reliability ◽  
Drawing Method

The failure data of crank rod system was analyzed by using weibull parallel model on the base of the simple weibull method. The distribution parameters of the weibull parallel model were estimated by using drawing method. The solving process of WPP drawing method was given in detial. Results show that the fitting degree of the failure data in the weibull parallel model is higher than that of the simple weibull distribution model, and it can more accurately described the failure distribution curve of the system in life cycle, which can provide necessary information for engine reliability indexes computation.

A Reliability Data Analysis Method Using Mixture Weibull Distribution Model

2011 ◽  
Vol 148-149 ◽  
pp. 1449-1453 ◽  
Author(s):  
Ying Kui Gu ◽  
De Liang Ge ◽  
Yao Gang Xiong
Keyword(s):  
Weibull Distribution ◽  
Failure Time ◽  
Likelihood Estimation ◽  
Weibull Model ◽  
Distribution Model ◽  
Time Data ◽  
Failure Rate Function ◽  
Failure Data ◽  
Wide Range ◽  
Rod System

The weibull distribution plays a crucial role in reliability theory and life-testing experiments. Weibull mixtures are widely used to model lifetime and failure time data, since they exhibit a wide range of shapes for the failure rate function. In this paper, the failure data of crank rod system was analyzed by using mixture weibull distribution model. The distribution parameters of the mixture weibull distribution model were estimated by using maximum likelihood estimation and drawing method. The comparison of fitting degree of failure location between standard weibull distribution model and mixture weibull model was given. Results show that the fitting degree of the failure data in the mixture weibull distribution model is higher than that of the simple weibull distribution model, and it can more accurately described the failure distribution curve of the system in life cycle.

Development of a Diesel Engine Reliability Database (DEREL) for the U.S. Coast Guard

1999 ◽  
Vol 36 (03) ◽  
pp. 127-142
Author(s):  
N. A. Moore ◽  
A. N. Perakis
Keyword(s):  
Diesel Engine ◽  
Monitoring Program ◽  
Coast Guard ◽  
Analysis Program ◽  
Microsoft Access ◽  
Failure Data ◽  
Full Power ◽  
Engine Failure ◽  
Engine Reliability ◽  
The U.S

The Coast Guard currently determines when a diesel engine should be overhauled based on the results of the Diesel Engine Monitoring Program, Navy Oil Analysis Program, Full Power Trials, and especially engine operating hours. In an effort to reduce costs, the Coast Guard is considering shifting their preventative maintenance to a condition-based system to reduce labor and downtime. To accomplish this goal, an analysis of the criteria used to indicate when a diesel engine should be overhauled must be performed. Before any statistical analysis can be conducted, an extensive amount of data must be collected on main diesel engines. This paper addresses the problem of creating a computer database to collect engine failure data for the USCG. We have conducted a review of several current shipboard reliability databases along with a look at modern developments in this area. This knowledge was used in the creation of a fully functional USCG prototype database using Microsoft Access 95 software called DEREL (Diesel Engine RELiability database). The DEREL database is implementable immediately in order to speed the initiation of data collection for future uses.

Reliability Analysis of a Small Pneumatic Cylinder Life

2011 ◽  
Vol 110-116 ◽  
pp. 4240-4245
Author(s):  
Jun Zhao Zhang ◽  
Cong Ling Wang ◽  
Xue Fa Fang
Keyword(s):  
Maximum Likelihood ◽  
Weibull Distribution ◽  
Maximum Likelihood Method ◽  
Likelihood Method ◽  
Distribution Model ◽  
Pneumatic Cylinder ◽  
Life Test ◽  
Life Distribution ◽  
Median Rank ◽  
Distribution Parameters

The reliability of the pneumatic cylinder was investigated by routine life test. The results show that the failures of the pneumatic cylinder can be described as a Weibull distribution and fatigue fracture of the aluminum end cap and the head of install bolt is the major failure for the pneumatic cylinder. The pneumatic cylinder life distribution parameters were estimated by the median rank method in combination with maximum likelihood method. The distribution model for the reliability of the pneumatic cylinder was also proposed here.

Risk Assessment Model of Automobile Defect Based on Weibull

2011 ◽  
Vol 383-390 ◽  
pp. 7496-7502
Author(s):  
Guo Zhong Huang ◽  
Yan Wang ◽  
Ying Chen ◽  
Jing Wang
Keyword(s):  
Risk Assessment ◽  
Weibull Distribution ◽  
Assessment Model ◽  
Distribution Model ◽  
Risk Assessment Model ◽  
Event Tree ◽  
Event Tree Analysis ◽  
Probability Forecast ◽  
Failure Data ◽  
Risk Forecast

This paper analyzed the automobile defects and its risk characteristics; the Event Tree Analysis (ETA) method was introduced to determine the risk flow route of automobile defects. According to the scattered of automobile, a risk forecast method based on the Weibull distribution is established. Based on the thousand vehicle breakdown number for risk probability forecast, propose a risk assessment model of automobile defect. The results indicate that on gathering actual failure data from after-sales service, the Weibull distribution model has a favorable applicability for forecasting risk possibility.

scholarly journals Reliability assessment of cutting tools based on zero-failure data

2020 ◽  
Author(s):  
Bin Yang ◽  
Kai Guo ◽  
Bin Feng ◽  
Chang'an Zhou ◽  
Chao Sun ◽  
...  
Keyword(s):  
Weibull Distribution ◽  
Titanium Alloys ◽  
Weighted Least Squares ◽  
Cutting Tools ◽  
Reliability Assessment ◽  
Assessment Model ◽  
Machining Process ◽  
Distribution Model ◽  
Failure Data ◽  
Monolithic Components

Abstract Titanium alloys are widely utilized in aeronautical monolithic components due to their excellent mechanical properties. However, the low machinability of titanium alloys results in an uncertain lifetime of cutting tools. Reliability assessment on cutting tools has become more and more significant to the effectiveness and stability of machining systems. Considering that cutting tools are often replaced well before the end of their useful lifetime to avoid failures and thus few tools failure data can be obtained during the machining process of titanium alloys, a reliability assessment model based on zero-failure data is developed to evaluate the reliability of cutting tools. A Weibull distribution model is chosen to describe the life distribution of cutting tools for reliability evaluation. Matching distribution curve method and weighted least squares method are used to estimate the distribution parameters. A novel approach using hierarchical Bayesian method for estimating the prior distribution of failure probability with zero-failure data is proposed by combining the characteristics of Weibull distribution and Incomplete Beta distribution. Reliability analysis for cutting tools with zero-failure data is performed using the proposed method. By comparing with the experience of experts and adopting stochastic simulation, the results of point estimation show plausibility of the proposed approach.

scholarly journals Estimation on Reliability Models of Bearing Failure Data

2018 ◽  
Vol 2018 ◽  
pp. 1-21 ◽  
Author(s):  
Xia Xintao ◽  
Chang Zhen ◽  
Zhang Lijun ◽  
Yang Xiaowei
Keyword(s):  
Probability Distribution ◽  
Weibull Distribution ◽  
Normal Distribution ◽  
Distribution Model ◽  
Bearing Failure ◽  
Analysis Model ◽  
Failure Data ◽  
Log Normal ◽  
Log Normal Distribution ◽  
Two Parameter

The failure data of bearing products is random and discrete and shows evident uncertainty. Is it accurate and reliable to use Weibull distribution to represent the failure model of product? The Weibull distribution, log-normal distribution, and an improved maximum entropy probability distribution were compared and analyzed to find an optimum and precise reliability analysis model. By utilizing computer simulation technology and k-s hypothesis testing, the feasibility of three models was verified, and the reliability of different models obtained via practical bearing failure data was compared and analyzed. The research indicates that the reliability model of two-parameter Weibull distribution does not apply to all situations, and sometimes, two-parameter log-normal distribution model is more precise and feasible; compared to three-parameter log-normal distribution model, the three-parameter Weibull distribution manifests better accuracy but still does not apply to all cases, while the novel proposed model of improved maximum entropy probability distribution fits not only all kinds of known distributions but also poor information issues with unknown probability distribution, prior information, or trends, so it is an ideal reliability analysis model with least error at present.

Optimization of Distribution Model for CNC Lathes Early Failures

2009 ◽  
Vol 407-408 ◽  
pp. 107-111
Author(s):  
Dian Sheng Chen ◽  
Tian Shan Lv
Keyword(s):  
Weibull Distribution ◽  
Exponential Distribution ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Distribution Model ◽  
Early Failure ◽  
Index Method ◽  
Failure Data ◽  
Failure Distribution ◽  
Early Failures

To eliminate early failures of CNC lathes, it is necessary to study the early failure distribution to establish accurate early failure distribution model of CNC lathes. During the modeling process, the same group of failure data obeys Weibull distribution, exponential distribution, super-exponential distribution and gamma distribution at the same time. To optimize the failure distribution model, this paper used “relevant index” method by comparing the distribution function curve fitting and determined that this group of failure data fitted Weibull distribution using maximum likelihood estimation method with its shape parameter k 0.8706 and scale parameter b142.6991.

Railway Equipment Reliability Test Based on Weibull Distribution

2016 ◽  
Vol 851 ◽  
pp. 340-345 ◽  
Author(s):  
Ce Liang ◽  
Jian Wei Yao ◽  
Ke Xin Zhang ◽  
Ze Ping Zhao
Keyword(s):  
Weibull Distribution ◽  
Rank Order ◽  
Least Square Method ◽  
Sampling Plan ◽  
Least Square ◽  
Reliability Test ◽  
Failure Data ◽  
Equipment Reliability ◽  
Interval Censored ◽  
Distribution Parameters

This paper presents a new approach for reliability test sampling plan of Railway equipment. Based on the interval censored failure data, the mean rank order method is used for data pre-process and the least square method is used for fitting the parameters of Weibull distribution, where, the best estimations of distribution parameters are derived. The sampling inspection plan for interval censored data is established when the lifetime follows the Weibull distribution. In the case study, we applied the proposed method to design the reliability test sampling plan of an electric multiple units.

Modeling and Analysis of Machining Center Reliability Based on MATLAB

2014 ◽  
Vol 945-949 ◽  
pp. 3102-3106 ◽  
Author(s):  
Xue Li ◽  
Chuan Gui Yang ◽  
Xiao Cui Zhu ◽  
Xin Fang Yuan
Keyword(s):  
Maximum Likelihood ◽  
Weibull Distribution ◽  
Theoretical Basis ◽  
Maximum Likelihood Method ◽  
Likelihood Method ◽  
Distribution Model ◽  
Modeling And Analysis ◽  
Failure Data ◽  
Time Between Failures ◽  
Machining Center

A method is introduced to process the failure data of 12 sets of machining centers for modelling and analyzing their reliability. In this method, Matlab is applied to fit the failure data for getting a hypothesis that their time between failures obey weibull distribution. Then, MLE (maximum likelihood method) is used to estimate parameters of distribution model of the time between failure, and the K-S test is employed to test the above hypothesis for proving that time between failures of machining center obey weibull distribution. Finally, the analysis of their common failures and corresponding improvements are done, which provide the theoretical basis for improvement of reliability of machining center and are greatly valuable in engineering.

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