PURPOSES : The reliability of traffic volume estimates based on location intelligence data (LID) is evaluated using various statistical techniques. There are several methods for determining statistical significance or relationships between different database sets. We propose a method that best represents the statistical difference between actual LID-based traffic volume estimates and the VDS values (i.e., true values) for the same road segment. METHODS : A total of 2,496 datasets aggregated for 1-h LID and VDS data were subjected to various statistical analyses to evaluate the consistency of the two datasets. The VDS data were defined as the true values for comparison. Four different statistical techniques (procrutes, 2-sample t-test, paired-sample t-test, and model performance rating scale) were applied. RESULTS : In cases where there is a specific pattern (e.g., traffic volume distribution considering peak and off-peak times), distribution tests such as Procrustes or Kolmogorov-Smirnov are useful because not only the prediction accuracy but also the similarity of the data distribution shape is important. CONCLUSIONS : The findings of this study provide important insight into the reliability of LID-based traffic volume estimation. To evaluate the reliability between the two groups, a paired-sample t-test was considered more appropriate than the performance evaluation measure of the machine-learning model. However, it is important to set the acceptance criteria necessary to statistically determine whether the difference between the two groups in the paired-sample t-test varies according to the given problem.

PURPOSES : We propose a framework to evaluate the reliability of integrating homogeneous or heterogeneous mobility data to produce the various data required for greenhouse gas emission estimation. METHODS : The mobility data used in the framework were collected at a fixed time from a specific point and were based on raster data. In general, the traffic volume for all traffic measurement points over 24 h can be considered raster data. In the future, the proposed framework can be applied to specific road points or road sections, depending on the presence or absence of raster data. RESULTS : The activity data required to calculate greenhouse gas emissions were derived from the mobility data analysis. With recent developments in information, communication, and artificial intelligence technologies, mobility data collected from different sources with the same collection purpose can be integrated to increase the reliability and accuracy of previously unknown or inaccurate information. CONCLUSIONS : This study will help assess the reliability of mobility data fusion as it is collected on the road, and will ultimately lead to more accurate estimates of greenhouse gas emissions.

The event recording devices such as EDR and DTG have recently been developed and installed in automobiles. The reliability of EDR application is being conducted in many previous studies, but with the development and development of autonomous vehicles, it is necessary to study the reliability of EDR and DTG application results for programs that can analyze autonomous driving. Therefore, in this study, the analysis was carried out in a way to secure the reliability of the application results of EDR and DTG of Carmaker, which can analyze the traffic accident analysis program PC-Crash and autonomous driving, and secure the reliability of the Carmaker program that applied EDR in Korea and abroad. As a result of the analysis, it was found that the speed error rate gradually increased from high speed to low speed, and the maximum error speed was less than 5 km/h through the average error rate for each speed. In the future, it is thought that it can be usefully used for analysis of traffic accidents in the event of autonomous vehicle accidents.

Naval combat system developed in-country is progressing at an alarming rate since 2000. ROK navy will be achieved all vessels that have combat system in the near future. The importance of System Engineering and Integrated Logistics Support based on reliability analysis is increasing. However, reliability analysis that everyone trusted and recognized is not enough and applied practically for development of Defense Acquisition Program. In particular, Existing Reliability Analysis is focusing on reliability index (Mean Time Between Failure (MTBF) etc.) for policy decision of defense improvement project. Most of the weapon system acquisition process applying in the exponential distribution simply persist unreality due to memoryless property. Critical failures are more important than simple faults to ship’s operator. There are no confirmed cases of reliability analysis involved with critical failure that naval ship scheduler and operator concerned sensitively.Therefore, this study is focusing on Mean Time To Critical Failure (MTTCF), reliability on specific time and Operational Readiness Float (ORF) requirements related to critical failure of Patrol Killer Guided missile (PKG) combat system that is beginning of naval combat system developed in-country. Methods of analysis is applied parametric and non-parametric statistical techniques. It is compared to the estimates and proposed applications. The result of study shows that parametric and non-parametric estimators should be applied differently depending on purpose of utilization based on test of normality. For the first time, this study is offering Reliability of ROK Naval combat system to stakeholders involved with defense improvement project. Decision makers of defense improvement project have to active support and effort in this area for improvement of System Engineering.

자동차와 복사기와 같은 제품의 보증범위는 일반적으로 보유기간 뿐만 아니라 작동 기간(주행거리, 복사매수 등)에 의해서도 제한된다. 이와 같은 제품의 보증데이터는 보 유기간과 작동기간, 두 가지 척도에 따라 신뢰성 분석을 진행할 수 있다. 본 논문에서는 두 가지 척도의 보증범위를 갖는 이차원 보증데이터를 이용한 신뢰 성 분석에 대한 동향연구를 진행하고자 한다. 이를 통해 이차원 보증데이터를 활용하 여 효과적으로 신뢰성 분석을 할 수 있는 연구방안을 제안하고자 한다.

제한된 환경인 실험실에서 짧은 시험 시간으로 신속하게 수명을 파악할 수 있는 가 속시험 데이터와 극한 환경시험 데이터는 실험실 데이터로서 정밀한 결과를 제공하지 만, 실제 사용 환경을 잘 반영하지 못한다. 그러나 사용현장데이터인 보증데이터는 보 증기간 동안 보증서비스 센터에 접수된 고장으로부터 얻어진 필드 데이터로 사용자의 실제 사용 환경에 따른 제품 고장을 파악할 수 있으므로 제품의 수명을 추정하기에 더욱 효과적일 수 있다. 본 연구에서는 보증데이터의 특징을 설명하였으며 보증정책에 따른 분석방법으로 1 차원, 2차원으로 분류하였다. 이에 따른 연구 동향과 적용 현황을 조사하여 보증데이 터를 사용한 필드 신뢰성 분석의 효과적인 활용방안을 논의하고자 한다.

In aerospace industry, MTBF (Mean Time Between Failure) and MFTBF (Mean Flight Time Between Failure) are generally used for reliability analysis. So far, especially to Korean military aircraft, MFTBF of avionic equipments is predicted by MIL-HDBK-217 and MIL-HDBK-338, however, the predicted MFTBF by military standard has a wide discrepancy to that of real-world operation, which leads to overstock and increase operation cost. This study analyzes operational data of avionic equipments. Operational MFTBF, which is calculated from operational data, is compared with predicted MFTBF calculated conventionally by military standard. In addition, failure rate trend is investigated to verify reliability growth in operational data, the investigation shows that failure rate curve from operational data has somewhat pattern with decreased failure rate and constant failure rate.

In aerospace industry, MTBF(Mean Time Between Failure) and MFTBF((Mean Flight Time Between Failure) are generally used for reliability analysis. So far, especially to Korean military aircraft, MFTBF of avionic equipments is predicted by MIL-HDBK-217 and MIL-HDBK-338, however, the predicted MFTBF by military standard has a wide discrepancy to that of real-world operation, which leads to overstock and increase operation cost. This study analyzes operational data of avionic equipments. Operational MFTBF, which is calculated from operational data, is compared with predicted MFTBF calculated conventionally by military standard. In addition, failure rate trend is investigated to verify reliability growth in operational data, the investigation shows that failure rate curve from operational data has somewhat pattern with decreased failure rate and constant failure rate.

This paper is a case study of reliability assessment with field warranty data of Clutch Master Cylinder (CMC) in hydraulic clutch system. We estimate lifetime distribution using field warranty data which contain much useful information for understanding reliability of the system in the real-world environments. However, the estimated parameters are far from existing reference values, which seems to be caused right censored field warranty data. To modify the parameters, we use the information of the durability test which is performed to verify that the lifetime of the item meets the required level. After that, we can observe that the modified parameters are closer to the existing reference values. This case study shows a possible idea to supplement lack of right censored field warranty data and its applicability.

This paper is a case study of reliability assessment with field warranty data of Clutch Master Cylinder(CMC) in hydraulic clutch system. We estimate lifetime distribution using field warranty data which contain much useful information for understanding reliability of the system in the real-world environments. However, the estimated parameters are far from existing reference values, which seems to be caused right censored field warranty data. To modify the parameters, we use the information of the durability test which is performed to verify that the lifetime of the item meets the required level. After that, we can observe that the modified parameters are closer to the existing reference values. This case study shows a possible idea to supplement lack of right censored field warranty data and its applicability

The paper reviews the methodologies of confirmatory data analysis(CDA) and exploratory data analysis(EDA) in statistical quality control(SQC), design of experiment(DOE) and reliability engineering(RE). The study discusses the properties of flexibility, openness, resistance and reexpression for EDA.

본 연구는 BPR(Business Process Reengineering)을 이루기 위한 가장 근본적이고 중요한 정보의 통합관리로써 MDM(Master Data Management)이라는 기준정보 관리 체계를 제시하였으며, 효과를 산출하기 위하여 국내의 글로벌 A 기업인 수행한 MDM 시스템을 분석하였다. 인사 및 고객 정보 위주로만 사용되었던 MDM을 제품 생산에 직접적으로 연관된 장비와 자재 부문까지 확장시켜 전사적으로 기업을 관리할 수 있는 정보

This paper is to propose two computation procedures of reliability measures for large interval data. First method is efficient to verify the relationship among four reliability measures such as F(t), R(t), f(t) and λ(t). Another method is effective to interpret the concept of various reliability measures. This study is also to reinterpret and recompute the errors of four reliability measures discovered in the reliability textbooks. Various numerical examples are presented to illustrate the application of two proposed procedures.

Because the damages of corrosion resulting from the chloride ion are very serious, many research studies have been performed to measure the penetration depth of the chloride ion. However, there is a problem with data selection obtained from collection during experiments. After careful study, it appears that the collected data are not conformed to a normal distribution. The result of this study will play a very important role, as a first step for the development and construction of a forecasting system to help determine a reliable service lifetime of marine structures.

Field data have been recorded as the time to failure or the number of failure of systems. We consider the time to failure and covariate variables in some pre-specified follow-up or warranty period. This paper aims to investigate study on the reliability estimation when some additional field data can be collected within-warranty period or after-warranty period. A various likelihood-based methods are outlined and examined for exponential or Weibull distribution.

다양한 컴포넌트들로 구성된 시스템의 수명 데이터는 시스템 컴포넌트들의 신뢰성을 추정하는데 많이 사용된다. 하지만 비용이나 고장진단의 기술적 문제 때문에 시스템 고장의 정확한 원인을 밝혀내기는 어렵다. 시스템이나 컴포넌트의 수명 데이터 중 정확한 고장원인을 알 수 없는 데이터를 마스크 데이터라 한다. 본 연구는 마스크데이터와 베이지안 추정의 연구방향을 살펴보고, 그리고 고장률의 비정보 사전분포를 이용하여, 컴포넌트가 직렬로 구성된 시스템의 수명 데이터가 마스크 데이터를 갖는 지수분포의 시스템 컴포넌트 고장률을 추정 한다.

This paper is concerned with the method of estimating lifetime distribution for field data in warranty period and for a situation where some additional field data can be gathered after the warranty period. Implementing the proposed methods in this paper will result in obtaining the more precise product life time estimation and product improvement.

This paper deals with the effect of spatial distribution of material properties on its statistical characteristics and numerical estimation method of reliability of fatigue sensitive structures with respect to the fatigue crack growth. A method is proposed to determine experimentally the probability distribution functions of material parameters of Paris law. da/dN=C(ΔK/K sub(0) ) super(m), using stress intensity factor controlled fatigue tests. The result with a high tensile strength steel shows that the distribution of the parameter m is approximately normal and that of 1/C, is a 3-parameter Weibull. The main result obtained are : (1) The theoretical autocorrelation of the resistance, 1/C, to fatigue crack growth are almost same for different lengths. (2) The variance decreases with the increasing a averaging length. When spatial correlation length is very small. the variane decreases significantly were the averaging length. (3) The probability distribution of load cycles or the number for a crack to reach a certain length can be estimated using these functions by simulation of non-Gaussian(expecially Weibull) Stochastic Process.

In this study, among the reliability assessment method for measured data of dam instrumentation, time series analysis and behavior analysis were introduced and the reliability assessment cases for seepag weir, pore-pressure meter, concrete stress meter and joint meter were presented.