scholarly journals Reliability Evaluation for the Running State of the Manufacturing System Based on Poor Information

2016 ◽  
Vol 2016 ◽  
pp. 1-19 ◽  
Author(s):  
Xintao Xia ◽  
Wenhuan Zhu ◽  
Bin Liu
Keyword(s):  
Probability Distribution ◽  
Product Quality ◽  
Manufacturing System ◽  
Evaluation Method ◽  
Probability Distributions ◽  
Bootstrap Method ◽  
Maximum Entropy Principle ◽  
Reliability Evaluation ◽  
Small Sample ◽  
Inspection Data

The output performance of the manufacturing system has a direct impact on the mechanical product quality. For guaranteeing product quality and production cost, many firms try to research the crucial issues on reliability of the manufacturing system with small sample data, to evaluate whether the manufacturing system is capable or not. The existing reliability methods depend on a known probability distribution or vast test data. However, the population performances of complex systems become uncertain as processing time; namely, their probability distributions are unknown, if the existing methods are still taken into account; it is ineffective. This paper proposes a novel evaluation method based on poor information to settle the problems of reliability of the running state of a manufacturing system under the condition of small sample sizes with a known or unknown probability distribution. Via grey bootstrap method, maximum entropy principle, and Poisson process, the experimental investigation on reliability evaluation for the running state of the manufacturing system shows that, under the best confidence levelP=0.95, if the reliability degree of achieving running quality isr>0.65, the intersection area between the inspection data and the intrinsic data isA(T)>0.3and the variation probability of the inspection data isPB(T)≤0.7, and the running state of the manufacturing system is reliable; otherwise, it is not reliable. And the sensitivity analysis regarding the size of the samples can show that the size of the samples has no effect on the evaluation results obtained by the evaluation method. The evaluation method proposed provides the scientific decision and suggestion for judging the running state of the manufacturing system reasonably, which is efficient, profitable, and organized.

scholarly journals The Smoothed Bootstrap Fine-Tuning

2019 ◽  
Vol 1 (1) ◽  
pp. 716-723
Author(s):  
Renata Dwornicka ◽  
Andrii Goroshko ◽  
Jacek Pietraszek
Keyword(s):  
Probability Distribution ◽  
Empirical Distribution ◽  
Bootstrap Method ◽  
Small Sample ◽  
Fine Tuning ◽  
Smoothed Bootstrap ◽  
Full Probability ◽  
The Bootstrap Method

AbstractThe bootstrap method is a well-known method to gather a full probability distribution from the dataset of a small sample. The simple bootstrap i.e. resampling from the raw dataset often leads to a significant irregularities in a shape of resulting empirical distribution due to the discontinuity of a support. The remedy for these irregularities is the smoothed bootstrap: a small random shift of source points before each resampling. This shift is controlled by specifically selected distributions. The key issue is such parameter settings of these distributions to achieve the desired characteristics of the empirical distribution. This paper describes an example of this procedure.

Use in Probabilistic Design of the Maximum Entrophy Distribution Based on Ranked Data

1980 ◽  
Vol 102 (3) ◽  
pp. 460-468
Author(s):  
J. N. Siddall ◽  
Ali Badawy
Keyword(s):  
Probability Distribution ◽  
Maximum Entropy ◽  
Probability Distributions ◽  
Maximum Entropy Principle ◽  
Random Variable ◽  
Probabilistic Design ◽  
Entropy Principle ◽  
Almost All ◽  
New Distribution

A new algorithm using the maximum entropy principle is introduced to estimate the probability distribution of a random variable, using directly a ranked sample. It is demonstrated that almost all of the analytical probability distributions can be approximated by the new algorithm. A comparison is made between existing methods and the new algorithm; and examples are given of fitting the new distribution to an actual ranked sample.

Reliability Assessment Methods of Complicated Mechanical Product Based on Statistical Learning Theory

2008 ◽  
Vol 44-46 ◽  
pp. 575-580 ◽  
Author(s):  
X.Y. Shao ◽  
Jun Wu ◽  
Ya Qiong Lv ◽  
Chao Deng
Keyword(s):  
Statistical Learning ◽  
Learning Theory ◽  
Evaluation Method ◽  
Statistical Learning Theory ◽  
Time Series Prediction ◽  
Reliability Evaluation ◽  
Small Sample ◽  
Accelerated Life Test ◽  
System Level ◽  
Support Vector

As the reliability test data of complicated mechanical products is rare in quantity on the system-level and difficult to determine the accurate composition of the life distribution unit as well, the traditional reliability evaluation method based on evolutionary theory has been of little use. And the Statistical Learning Theory begins to be widely focused on as a novel small sample statistic method, which has been mostly applied to pattern recognition, fault detection, time series prediction and so on. This paper creates a new method for reliability evaluation derived from Statistical Learning Theory. By constructing Support Vector Machine with analog reasoning, and solving linear operator equation, the probability density of product can be evaluated directly and then the product reliability index can be obtained. Compared with the traditional way, this method can apparently increase the accuracy and generalization ability of reliability evaluation within limited samples. Finally, this paper presents the bridge of a certain heavy special vehicle as an example to testify the efficiency of this method, and uses the accelerated life test of the vehicle bridge to estimate its reliability.

scholarly journals Research on Reliability Evaluation Method of Aerospace Pyrotechnic Devices Based on Energy Measurement

2020 ◽  
Vol 10 (22) ◽  
pp. 8200
Author(s):  
Yubo Zhu ◽  
Jili Rong ◽  
Qianqiang Song ◽  
Zhipei Wu
Keyword(s):  
Evaluation Method ◽  
High Reliability ◽  
Reliability Evaluation ◽  
Small Sample ◽  
Performance Parameters ◽  
Measuring Devices ◽  
Reliability Method ◽  
The Cost ◽  
Sample Method ◽  
T Distribution

High reliability is the basic requirement of aerospace pyrotechnic devices. Traditional reliability evaluation methods require a lot of tests, which become too expensive; therefore, the small-sample evaluation method is needed to reduce the cost. Using energy as a performance parameter can better reflect the essence of the function of the pyrotechnic device compared to using force. Firstly, this article assumes that the strength obeys the normal distribution, and the stress is a constant; therefore, the reliability evaluation formula based on the t distribution is proposed. Then, taking the pin puller as the research object, four sets of energy measuring devices were developed so as to obtain its performance parameters. Finally, the evaluation results show that the pin puller has a high reliability of 0.9999999765 with a confidence level of 0.995. The reliability method proposed in this paper is a small-sample method for evaluating aerospace pyrotechnic devices, which can greatly reduce the cost of reliability evaluation. Moreover, the energy measuring devices developed in this paper can provide a new way of measuring performance parameters for piston-type pyrotechnic devices.

scholarly journals A Reliability Evaluation Method for System's Dependent Competition Failure and Multi-Parameter Degradation Failure

2019 ◽  
Vol 37 (6) ◽  
pp. 1191-1199
Author(s):  
Qiguo Hu ◽  
Zhan Gao
Keyword(s):  
Stochastic Process ◽  
Maximum Likelihood ◽  
Evaluation Method ◽  
Maximum Likelihood Method ◽  
Bootstrap Method ◽  
Failure Process ◽  
Reliability Evaluation ◽  
Likelihood Method ◽  
Gaussian Stochastic Process ◽  
Degradation Failure

In order to enhance the reliability of a system that has dependent competition failure, a reliability evaluation method is proposed to evaluate the dependent competition failure and multi-parameter degradation failure. The multi-parameter degradation failure process is described with the Wiener stochastic process and the inverse Gaussian stochastic process. The Copula function is used to model the system's multi-degradation failure process. The two-stage maximum likelihood method is used to estimate the degradation failure parameters. The conditional probability of dependent competition failure in terms of degradation degree is established. The Bayes-Bootstrap method is utilized to correct the dependent competition failure parameters obtained with the maximum likelihood method and to further establish the system's dependent competition failure model. The degradation data of an aero-engine is used as an example to analyze the reliability under competition between dependent competition failure and multi-parameter degradation failure. The analysis results can effectively demonstrate the reliability of an aero-engine's performance and verify the validity of the model, thus having good engineering application values.

Robust Test Method of TSOP PEMs for Space Application

2019 ◽  
Author(s):  
Yasunobu Iwai ◽  
Koichi Shinozaki ◽  
Daiki Tanaka
Keyword(s):  
Evaluation Method ◽  
Low Cost ◽  
Reliability Evaluation ◽  
Test Method ◽  
Thermal Shock Test ◽  
Space Application ◽  
Space Applications ◽  
Limit Test ◽  
Long Time ◽  
Short Time

Abstract Compared with space parts, consumer parts are highly functional, low cost, compact and lightweight. Therefore, their increased usage in space applications is expected. Prior testing and evaluation on space applicability are necessary because consumer parts do not have quality guarantees for space application [1]. However, in the conventional reliability evaluation method, the test takes a long time, and the problem is that the robustness of the target sample can’t be evaluated in a short time. In this report, we apply to the latest TSOP PEM (Thin Small Outline Package Plastic Encapsulated Microcircuit) an evaluation method that combines preconditioning and HALT (Highly Accelerated Limit Test), which is a test method that causes failures in a short time under very severe environmental conditions. We show that this method can evaluate the robustness of TSOP PEMs including solder connections in a short time. In addition, the validity of this evaluation method for TSOP PEM is shown by comparing with the evaluation results of thermal shock test and life test, which are conventional reliability evaluation methods.

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