• Title, Summary, Keyword: Laplace trend test

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The Study for Comparative Analysis of Software Failure Time Using EWMA Control Chart (지수 가중 이동 평균 관리도를 이용한 소프트웨어 고장 시간 비교분석에 관한 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.8 no.3
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    • pp.33-39
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    • 2008
  • Software failure time presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offer information of outline content. In this paper, we discuss exponentially weighted moving average chart, in measuring failure time. In control, exponentially weighted moving average chart's uses are efficiency case of analysis with knowing information, Using real software failure time, we are proposed to use exponentially weighted moving average chart and comparative analysis of software failure time.

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Change-point Approach for Analyzing Failure Trend in Repairable Generating Systems (수리 가능 발전기 시스템의 고장추세 분석을 위한 변화점 접근방법)

  • Hong, Min-Pyo;Bae, Suk-Joo
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.32 no.1
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    • pp.11-19
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    • 2009
  • A number of trend test methods, i.e., Military Handbook test and Laplace test etc., have been applied to investigate recurrent failures trend in repairable systems. Existing methods provide information about only existence of trend in the system. In this paper, we propose a new change-point test based on the Schwarz Information Criterion(SIC). The change-point approach is more informative than other trend test methods in that it provides the number of change-points and the location of change-points if it exists, as well as the existence of change-point for recurrent failures. The change-point test is applied to nine 300MW generating units operated in East China. We confirm that the change-point test has a potential for establishing optimal preventive maintenance policy by detecting change-point of failure rate.

The Study for Software Future Forecasting Failure Time Using Time Series Analysis. (시계열 분석을 이용한 소프트웨어 미래 고장 시간 예측에 관한 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.11 no.3
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    • pp.19-24
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    • 2011
  • Software failure time presented in the literature exhibit either constant monotonic increasing or monotonic decreasing, For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offer information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. In this study, time series analys is used in the simple moving average and weighted moving averages, exponential smoothing method for predict the future failure times, Empirical analysis used interval failure time for the prediction of this model. Model selection using the mean square error was presented for effective comparison.

The Study for Software Future Forecasting Failure Time Using ARIMA AR(1) (ARIMA AR(1) 모형을 이용한 소프트웨어 미래 고장 시간 예측에 관한 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.8 no.2
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    • pp.35-40
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    • 2008
  • Software failure time presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offer information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. The used software failure time data for forecasting failure time is random number of Weibull distribution(shaper parameter 1, scale parameter 0.5), Using this data, we are proposed to ARIMA(AR(1)) and simulation method for forecasting failure time. The practical ARIMA method is presented.

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The Study for Software Future Forecasting Failure Time Using Curve Regression Analysis (곡선 회귀모형을 이용한 소프트웨어 미래 고장 시간 예측에 관한 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.12 no.3
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    • pp.115-121
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    • 2012
  • Software failure time presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offers information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. In this study, we predict the future failure time by using the curve regression analysis where the s-curve, growth, and Logistic model is used. The proposed prediction method analysis used failure time for the prediction of this model. Model selection using the coefficient of determination and the mean square error were presented for effective comparison.

Development of Reliability Analysis Procedures for Repairable Systems with Interval Failure Time Data and a Related Case Study (구간 고장 데이터가 주어진 수리가능 시스템의 신뢰도 분석절차 개발 및 사례연구)

  • Cho, Cha-Hyun;Yum, Bong-Jin
    • Journal of the Korea Institute of Military Science and Technology
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    • v.14 no.5
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    • pp.859-870
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    • 2011
  • The purpose of this paper is to develop reliability analysis procedures for repairable systems with interval failure time data and apply the procedures for assessing the storage reliability of a subsystem of a certain type of guided missile. In the procedures, the interval failure time data are converted to pseudo failure times using the uniform random generation method, mid-point method or equispaced intervals method. Then, such analytic trend tests as Laplace, Lewis-Robinson, Pair-wise Comparison Nonparametric tests are used to determine whether the failure process follows a renewal or non-renewal process. Monte Carlo simulation experiments are conducted to compare the three conversion methods in terms of the statistical performance for each trend test when the underlying process is homogeneous Poisson, renewal, or non-homogeneous Poisson. The simulation results show that the uniform random generation method is best among the three. These results are applied to actual field data collected for a subsystem of a certain type of guided missile to identify its failure process and to estimate its mean time to failure and annual mean repair cost.

The Study for Process Capability Analysis of Software Failure Interval Time (소프트웨어 고장 간격 시간에 대한 공정능력분석에 관한 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.7 no.2
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    • pp.49-55
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    • 2007
  • Software failure time presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offer information of outline content. From the subdivision of this analysis, new attemp needs the side of the quality control. In this paper, we discuss process capability analysis using process capability indexs. Because of software failure interval time is pattern of nonnegative value, instead of capability analysis of suppose to normal distribution, capability analysis of process distribution using to Box-Cox transformation is attermpted. The used software failure time data for capability analysis of process is SS3, the result of analysis listed on this chapter 4 and 5. The practical use is presented.

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Statistical Inference for an Arithmetic Process

  • Francis, Leung Kit-Nam
    • Industrial Engineering and Management Systems
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    • v.1 no.1
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    • pp.87-92
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    • 2002
  • A stochastic process {$A_n$, n = 1, 2, ...} is an arithmetic process (AP) if there exists some real number, d, so that {$A_n$ + (n-1)d, n =1, 2, ...} is a renewal process (RP). AP is a stochastically monotonic process and can be used for modeling a point process, i.e. point events occurring in a haphazard way in time (or space), especially with a trend. For example, the vents may be failures arising from a deteriorating machine; and such a series of failures id distributed haphazardly along a time continuum. In this paper, we discuss estimation procedures for an AP, similar to those for a geometric process (GP) proposed by Lam (1992). Two statistics are suggested for testing whether a given process is an AP. If this is so, we can estimate the parameters d, ${\mu}_{A1}$ and ${\sigma}^{2}_{A1}$ of the AP based on the techniques of simple linear regression, where ${\mu}_{A1}$ and ${\sigma}^2_{A1}$ are the mean and variance of the first random variable $A_1$ respectively. In this paper, the procedures are, for the most part, discussed in reliability terminology. Of course, the methods are valid in any area of application, in which case they should be interpreted accordingly.

The Comparative Study of NHPP Software Reliability Model Based on Log and Exponential Power Intensity Function (로그 및 지수파우어 강도함수를 이용한 NHPP 소프트웨어 무한고장 신뢰도 모형에 관한 비교연구)

  • Yang, Tae-Jin
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.8 no.6
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    • pp.445-452
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    • 2015
  • Software reliability in the software development process is an important issue. Software process improvement helps in finishing with reliable software product. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, proposes the reliability model with log and power intensity function (log linear, log power and exponential power), which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination($R^2$), for the sake of efficient model, was employed. Analysis of failure, using real data set for the sake of proposing log and power intensity function, was employed. This analysis of failure data compared with log and power intensity function. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the log type model is also efficient in terms of reliability because it (the coefficient of determination is 70% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can be able to help.

The Comparative Study of NHPP Software Reliability Model Based on Exponential and Inverse Exponential Distribution (지수 및 역지수 분포를 이용한 NHPP 소프트웨어 무한고장 신뢰도 모형에 관한 비교연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.9 no.2
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    • pp.133-140
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    • 2016
  • Software reliability in the software development process is an important issue. Software process improvement helps in finishing with reliable software product. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, we were proposed the reliability model with the exponential and inverse exponential distribution, which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination($R^2$), for the sake of efficient model, were employed. Analysis of failure, using real data set for the sake of proposing the exponential and inverse exponential distribution, was employed. This analysis of failure data compared with the exponential and inverse exponential distribution property. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the inverse exponential distribution model is also efficient in terms of reliability because it (the coefficient of determination is 80% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, the software developers have to consider life distribution by prior knowledge of the software to identify failure modes which can be able to help.