• IE interfaces
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• v.25 no.4
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• pp.422-430
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• 2012

In this article, we introduced the estimation method by 'Safety Integrity Level'(SIL) for the criterion of safety assurance and performed a case study on a flame scanner. SIL requires probabilistic evaluation of each set of equipment used to reduce risk in a safety related system. FMEDA(Failure Modes, Effects and Diagnostic Analysis) method is widely used to evaluate the safety levels and provides information on the failure rates and failure mode distributions necessary to calculate a diagnostic coverage factor for a part or a component. Basically, two parameters resulting from FMEDA are used for SIL classification of the device : SFF(Safe Failure Fraction) and PFD(Probability of Failure on Demand). In this case study, it is concluded that the flame scanner is designed to fulfill the condition of SIL 3 in the aspect of SFF and PFD.

• Journal of the Korea Society for Simulation
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• v.14 no.1
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• pp.1-8
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• 2005

In the semiconductor manufacturing, yield enhancement is an urgent issue. It is ideal to prevent all the failures. However, when a failure occurs, it is important to quickly specify the cause stage and take countermeasure. Reviewing wafer level and composite lot level yield patterns has always been an effective way of identifying yield inhibitors and driving process improvement. This process is very time consuming and as such generally occurs only when the overall yield of a device has dropped significantly enough to warrant investigation. The automatic method of failure pattern extraction from fail bit map provides reduced time to analysis and facilitates yield enhancement. The automatic method of failure pattern extraction from fail bit map provides reduced time to analysis and facilitates yield enhancement. This paper describes the techniques to automatically classifies a failure pattern using a fail bit map.

• Journal of the Korean Society of Safety
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• v.15 no.2
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• pp.103-110
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• 2000

This paper deal with the stability evaluation and suggestion of progressive failure slope in biotite granite area of Andong. Based on geological site investigation and field test, stability analysis of slope was performed in conjunction with limit equilibrium methods and stereographic projection. Additionally, initial design and construction procedure was critically evaluated. Series of the slope stability analysis reveals the detection of local wedge and plane failure under the current slope condition. It is additionally appeared that a certain synthetic behavior of circle and plane failure exists on the right spot where the overall failure's going in progress. In order to construct more stable slope based on the suitability for the real state of the slope circumstances, this study issues a solution to eliminate the primary factors which cause the instability, by means of the grade of weathering and RMR classification of rock mass.

• Asia pacific journal of information systems
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• v.8 no.2
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• pp.121-132
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• 1998

Many cases of information systems (IS) failure have still continued to be reported ever since computer-based information systems were introduced to process business transactions in the early 1950s. Because an enormous amount of budgets is currently invested on information technology in many organizations, failures and problems of information systems may serve as key culprits to serious business problems which will face the organizations. Thus, there have been a number of studies on IS failures which aimed to identify causes and reasons for such failures and reveal their inherent nature, Some studies developed conceptual frameworks to classify categories of diverse IS failure phenomena. However, little research performed an empirical study to investigate the underlying structure of IS failures perceived by IS professionals by measuring their perception. In this regard, the current study collected systems developers perceptual data towards IS failure phenomena to identify what constitute IS failure. The data was analyzed using a multidimensional scaling program and ten categories of problems were identified to constitute the IS failure structure, It was found that most categories were related to problems with users, hardware, and systems quality.

• Journal of the Earthquake Engineering Society of Korea
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• v.28 no.4
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• pp.215-222
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• 2024

Many older reinforced concrete (RC) buildings were constructed and designed with only gravity loads in mind. Columns in those buildings have insufficient reinforcement details that do not satisfy the requirements specified in current seismic design standards. This study aims to develop drift-based fragility functions for lightly RC columns. For this purpose, a database of 193 lightly RC columns was constructed to determine central and dispersion values of drift ratios for individual damage states. Additionally, to develop more accurate fragility functions of the columns, the failure mode of RC columns was incorporated into fragility functions. The classification procedure for column failure mode is proposed in this study. Fragility functions for older RC columns are constructed according to four different damage states. The main variables of the fragility functions proposed in this study are column properties and failure mode.

• Journal of Electrical Engineering and Technology
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• v.1 no.2
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• pp.257-262
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• 2006

Insulation failure in an electrical utility depends on the continuous stress imposed upon it. Monitoring of the insulation condition is a significant issue for safe operation of the electrical power system. In this paper, comparison of recognition rate variable classification scheme of PD (partial discharge) sources that occur within an electrical utility are studied. To acquire PD data, five defective models are made, that is, air discharge, void discharge and three types of treeinging discharge. Furthermore, these statistical distributions are applied to classify PD sources as the input data for the classification tools. ANFIS shows the highest rate, the value of which is 99% and PCA-LDA and ANFIS are superior to BP in regards to other matters.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.1-16
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• 2008

The purpose of this paper is to propose a new binary classification method for predicting corporate failure based on genetic algorithm, and to validate its prediction power through empirical analysis. Establishing virtual companies representing bankrupt companies and non-bankrupt ones respectively, the proposed method measures the similarity between the virtual companies and the subject for prediction, and classifies the subject into either bankrupt or non-bankrupt one. The values of the classification variables of the virtual companies and the weights of the variables are determined by the proper model to maximize the hit ratio of training data set using genetic algorithm. In order to test the validity of the proposed method, we compare its prediction accuracy with ones of other existing methods such as multi-discriminant analysis, logistic regression, decision tree, and artificial neural network, and it is shown that the binary classification method we propose in this paper can serve as a premising alternative to the existing methods for bankruptcy prediction.

• Journal of Multimedia Information System
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• v.8 no.4
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• pp.211-220
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• 2021

The process of inspecting SMDs on the PCB boards improves the product quality, performance and reduces frequent issues in this field. However, undesirable scenarios such as assembly failure and device breakdown can occur sometime during the assembly process and result in costly losses and time-consuming. The detection of these components with a model based on deep learning may be effective to reduce some errors during the inspection in the manufacturing process. In this paper, YOLO models were used due to their high speed and good accuracy in classification and target detection. A SMD detection and classification method using YOLO networks based on robust data preprocessing and augmentation techniques to deal with various types of variation such as illumination and geometric changes is proposed. For 9 different components of data provided from a PCB manufacturer company, the experiment results show that YOLOv4 is better with fast detection and classification than YOLOv3.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.6
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• pp.509-519
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• 2007

This paper presents new techniques under development for monitoring the health and vibration of the active components in nuclear power plants, The purpose of this study is to develop an automated system for condition classification of a check valve one of the components being used extensively in a safety system of a nuclear power plant. Acoustic emission testing for a check valve under controlled flow loop conditions was performed to detect and evaluate disc movement for valve failure such as wear and leakage due to foreign object interference in a check valve, It is clearly demonstrated that the evaluation of different types of failure types such as disc wear and check valve leakage were successful by systematically analyzing the characteristics of various AE parameters, It is also shown that the leak size can be determined with an artificial neural network.

• Geomechanics and Engineering
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• v.13 no.4
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• pp.571-584
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• 2017

Slope mass rating (SMR) is commonly used for the geomechanical classification of rock masses in an attempt to evaluate the stability of slopes. SMR is calculated from the $RMR_{89-basic}$ (basic rock mass rating) and from the characteristic features of discontinuities, and may be applied to slope stability analysis as well as to slope support recommendations. This study attempts to utilize the SMR classification system for slope stability analysis and to investigate the engineering geological conditions of the slopes and the slope stability analysis of the Gas Flare site in phases 6, 7 and 8 of the South Pars Gas Complex in Assalouyeh, south of Iran. After studying a total of twelve slopes, the results of the SMR classification system indicated that three slope failure modes, namely, wedge, plane and mass failure were possible along the slopes. In addition, the stability analyses conducted by a number of computer programs indicated that three of the slopes were stable, three of the slopes were unstable and the remaining six slopes were categorized as 'needs attention'classes.