• International Journal of Reliability and Applications
• /
• v.2 no.4
• /
• pp.253-262
• /
• 2001

A k-out-of-n standby system is considered where all of its components are s-independent and classified either working or cold standby connected with imperfect switches. The probability density function of the life length for this system is established in closed form, when the underlying components have constant failure rates. Also the reliability function of the system is derived. Finally, the reliability functions for one, two and three out of four systems are deduced for perfect or imperfect switches and identical or non-identical constant failure rates for working and standby components.

• Journal of applied mathematics & informatics
• /
• v.9 no.2
• /
• pp.761-769
• /
• 2002

Due to the large scale application of software systems, software reliability plays an important role in software developments. In this paper, a software reliability growth model (SRGM) is proposed. The testing time on the right is truncated in this model. The instantaneous failure rate, mean-value function, error detection rate, reliability of the software, estimation of parameters and the simple applications of this model are discussed .

• Transactions of the Korean Society of Automotive Engineers
• /
• v.15 no.3
• /
• pp.63-71
• /
• 2007

During the design phase of a product, reliability and design engineers are called upon to evaluate the reliability of the system, The question of how to meet target reliability for the system arises when estimated reliability or cost is inadequate. This then becomes a problem of reliability allocation and system structure design. This study proposes the optimization methodology to achieve target reliability with minimum cost through construction of the cost function of system. In cost function, total cost means the sum of initial cost, repair cost and maintenance cost. This study constructs optimization problem about system structure design and reliability allocation using cost function. This problem constructed is solved by Multi-island Genetic Algorithm(MIGA), and applies to urban transit brake system. Current brake system of the urban transit is series system. Series system is the simplest and perhaps one of the most common system, but it demands high reliability and maintenance cost because all components must be operating to ensure system operation. Thus this study makes a comparative study by applying k-out-of-n system to brake system. This methodology presented can be a great tool for aiding reliability and design engineers in their decision-makings.

• Proceedings of the ESK Conference
• /
• 1996.04a
• /
• pp.113-127
• /
• 1996

In Human Reliability Analysis(HRA), the uncertainties involved in many factors that affect human reliability have to be represented as the quantitative forms. Conventional probability- based human reliability theory is used to evaluate the effect of those uncertainties but it is pointed out that the actual human reliability should be different from that of conventional one. Conventional HRA makes use of error rates, however, it is difficult to collect data enough to estimate these error rates, and the estimates of error rates are dependent only on engineering judgement. In this paper, the error possibility that is proposed by Onisawa is used to represent human reliability, and the error possibility is obtained by use of fuzzy reasoning that plays an important role to clarify the relation between human reliability and human error. Also, assuming these factors are connected to the top event through Fault Tree structure, the influence and correlation of these factors are measured by fuzzy operation. When a fuzzy operation is applied to Fault Tree Analysis, it is possible to simplify the operation applying the logic disjuction and logic conjuction to structure function, and the structure of human reliability can be represented as membership function of the top event. Also, on the basis of the the membership function, the characteristics of human reliability can be evaluated by use of the concept of pattern recognition.

• Journal of the Korean Data and Information Science Society
• /
• v.13 no.2
• /
• pp.39-44
• /
• 2002

We compare MISE of the MLE, UMVUE, invariantly optimal estimator and Jacknife estimator for the reliability function of the Weibull distribution when the sample size is small.

• Proceedings of the Korean Reliability Society Conference
• /
• 2002.06a
• /
• pp.305-305
• /
• 2002

A continuum structure function is a non-decreasing mapping from the unit hypercube to the unit interval. Within the class of continuum structure functions, new axiomatic characterizations of the Natvig and the Barlow-Wu subclass are obtained.

• Journal of the Korean Data and Information Science Society
• /
• v.6 no.1
• /
• pp.39-51
• /
• 1995

This paper deals with the problem of obtaining some Bayes estimators of Rayleigh reliability function in a time censored sampling with incomplete information. Using the priors about a reliability function some Bayes estimators are proposed and studied under squared error loss and Harris loss.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.7 no.4
• /
• pp.7-14
• /
• 2011

Infinite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rate per fault (hazard function). This infinite non-homogeneous Poisson process is model which reflects the possibility of introducing new faults when correcting or modifying the software. In this paper, polynomial hazard function have been proposed, which can efficiency application for software reliability. Algorithm for estimating the parameters used to maximum likelihood estimator and bisection method. Model selection based on mean square error and the coefficient of determination for the sake of efficient model were employed. In numerical example, log power time model of the existing model in this area and the polynomial hazard function model were compared using failure interval time. Because polynomial hazard function model is more efficient in terms of reliability, polynomial hazard function model as an alternative to the existing model also were able to confirm that can use in this area.

• Journal of Applied Reliability
• /
• v.18 no.2
• /
• pp.130-142
• /
• 2018

Purpose: The purpose of this study is to introduce regression method in the presence of competing risks and to show how you can use the method with hypothetical data. Methods: Survival analysis has been widely used in biostatistics division. But the same method has not been utilized in reliability division. Especially competing risks, where more than a couple of causes of failure occur and the occurrence of one event precludes the occurrence of the other events, are scattered in reliability field. But they are not utilized in the area of reliability or they are analysed in the wrong way. Specifically Kaplan-Meier method is used to calculate the probability of failure in the presence of competing risks, thereby overestimating the real probability of failure. Hence, cumulative incidence function is introduced. In addition, sample competing risks data are analysed using cumulative incidence function along with some graphs. Lastly we compare cumulative incidence functions with regression type analysis briefly. Results: We used cumulative incidence function to calculate the survival probability or failure probability in the presence of competing risks. We also drew some useful graphs depicting the failure trend over the lifetime. Conclusion: This research shows that Kaplan-Meier method is not appropriate for the evaluation of survival or failure over the course of lifetime in the presence of competing risks. Cumulative incidence function is shown to be useful in stead. Some graphs using the cumulative incidence functions are also shown to be informative.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.30 no.3
• /
• pp.103-108
• /
• 2007

This paper presents the conceptual framework for estimating and predicting system's susceptibility to failure as function of condition parameter value which is representing the current status of performance measure using on-line performance reliability. The performance of such system depends on one parameter with a probability distribution that degrades with time gracefully. Performance reliability represents the probability that physical performance will remain satisfactory over a finite period of time or usage cycles in the future. An empirical physical performance function is constructed to incorporate explanatory variables (operating and environmental conditions) over a time or usage dimension. This function enables one to model device performance and the associated classical reliability measures simultaneously, in the performance domain and time domain. The conditional performance reliability structure developed represents a tool to predict system performance over time or usage for next usage period. By enabling such a framework, it can bring us more efficient planning and execution in system's operation control as well as maintenance to reduce costs and/or increase profits.