• Journal of Ship and Ocean Technology
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• v.2 no.1
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• pp.42-57
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• 1998

Genetic Algorithm (GA) is applied to obtain optimal Inspection plan for fatigue deteriorating structures. The optimization problem is defined so as to minimize inspection cost in the 1ifs-time of the structure under the constraint that the increment of failure probability in each inspection interval is maintained below a target value. Optimization parameters are the inspection timing and the inspection quality. The inspection timing is selected from the discrete intervals such as one year, two years, three years, etc. The inspection quality is selected from the followings; no inspection, normal inspection, sampling inspection or precise inspection. The applicability of the proposed GA approach is demonstrated through the numerical calculations assuming a structure consisting of four member sets. Influences of the level of target failure probability, initial defect condition and stress increase due to plate thickness reduction caused by corrosion on inspection planning are discussed.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2008.05a
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• pp.43-45
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• 2008

According to industrial development, Ingots are more large and various. In particular large STS ingot. The probability of shrinkage cavity occurrence is higher than carbon steel and alloy steel. To manufacture ultra clean steel the technical development is nearly necessary for example controlling inclusions and total [H]. In this study, after measured the mold temperature and adjusted thermo conductivity of STS steel and compared existing mold to new one with CAE. As a result, the new mold more reduced than existing mold for the probability of shrinkage cavity occurrence.

• Journal of Electrical Engineering and Technology
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• v.3 no.4
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• pp.571-575
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• 2008

Stator insulation quality assessment for high voltage motors is a major issue for the reliable maintenance of industrial and power plants. To assess the condition of stator insulation, nondestructive tests were performed on the sixty coil groups of twelve motors. After completing the nondestructive tests, the AC voltage applied to the stator winding was gradually increased until insulation failure in order to obtain the breakdown voltage. The stator winding of each motor was classified into five coil groups; one group with healthy insulation and four groups with four different types of artificial defects. To analyze the breakdown voltage statistically, Weibull distribution was employed for the tests on the fifty coil groups of ten motors. The 50th percentile values of the measured breakdown voltages based on the statistical data of the five coil groups of ten motors were 26.1kV, 25.0kV, 24.4kV, 26.7kV and 30.5kV, respectively. Almost all of the failures were located in the line-end coil at the exit of the core slot. The breakdown voltages and the types of defects showed strong relation to the stator insulation tests such as in the case of dissipation factor and ac current. It is shown that the condition of the motor insulation can be determined from the relationship between the probability of failure and the type of defect.

• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.649-664
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• 2017

Purpose: This paper introduces the technology of prognostics for Industry 4.0 and presents its application procedure for fitness-for-service assessment of natural gas pipelines according to ISO 13374 framework. Methods: Combining data-driven approach with pipe failure models, we present a hybrid scheme for the gas pipeline prognostics. The probability of pipe failure is obtained by using the PCORRC burst pressure model and First Order Second Moment (FOSM) method. A fuzzy inference system is also employed to accommodate uncertainty due to corrosion growth and defect occurrence. Results: With a modified field dataset, the probability of failure on the pipeline is calculated. Then, its residual useful life (RUL) is predicted according to ISO 16708 standard. As a result, the fitness-for-service of the test pipeline is well-confirmed. Conclusion: The framework described in ISO 13374 is applicable to the RUL prediction and the fitness-for-service assessment for gas pipelines. Therefore, the technology of prognostics is helpful for safe and efficient management of gas pipelines in Industry 4.0.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1195-1200
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• 2019

This paper proposes a detection algorithm for group testing. Group testing is a problem of finding a very small number of defect samples out of a large number of samples, which is similar to the problem of Compressed Sensing. In this paper, we define a noiseless group testing and propose a probabilistic algorithm for detection of defective samples. The proposed algorithm is constructed such that the extrinsic probabilities between the input and output signals exchange with each other so that the posterior probability of the output signal is maximized. Then, defective samples are found in the group testing problem through a simulation on the detection algorithm. The simulation results for this study are compared with the lower bound in the information theory to see how much difference in failure probability over the input and output signal sizes.

• Journal of KSNVE
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• v.5 no.3
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• pp.353-360
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• 1995

A new automatic diagnostic system for predicting multiple defects in rolling element bearings is developed by taking probbability into account. A database is constructed from the frequency characteristics of tested bearings with various types of defects. The proposed algorithms for the automatic diagnosis of bearing defects are shown to be satisfactory through the experiments. This method can be effectively used for quality control of the rolling bearing in plants.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.773-782
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• 2007

The statistical process control charts are very extensively used for monitoring of process mean, deviation, defect rate or reject rate. In this paper we consider a control chart to monitor the process reject rate in the high yield process, which is based on the observed cumulative probability of the number of items inspected until r defective items are observed. We first propose selection of the optimal value of r in the CPC-r charts, and also consider the usefulness of the chart in high yield process such as semiconductor or TFT-LCD manufacturing process.

• Journal of KIISE
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• v.43 no.12
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• pp.1334-1341
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• 2016

In recent years, the importance of managing software defects in the implementation stage has emerged because of the rapid development and wide-range usage of intelligent smart devices. Even if not a few studies have been conducted on the prediction models for software defects, their outcomes have not been widely shared. This paper proposes an efficient probabilistic management model of software metrics based on the Bayesian network, to overcome limits such as binary defect prediction models. We expect the proposed model to configure the Bayesian network by taking advantage of various software metrics, which can help in identifying improvements for refactoring. Once the source code has improved through code refactoring, the measured related metric values will also change. The proposed model presents probability values reflecting the effects after defect removal, which can be achieved by improving metrics through refactoring. This model could cope with the conclusive binary predictions, and consequently secure flexibilities on decision making, using indeterminate probability values.

• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.23-29
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• 2017

This paper introduces the mold technology for the development of ultra-compact package of less than 1mm, and also analyze the error pattern of the results using this mold technology. The existing ultra-small mold structure was one-piece, which caused the surface of EDM to be rough and increase the error rate. This has been an obstacle to further reducing the size of the mold. On the other hand, the proposed mold technology tries to overcome the limitation of the one-piece type by using the prefabricated type method. This paper also classify defect patterns in the results of the proposed mold structure and analyze the occurrence probability of each pattern to use as a basic data to develop a detector.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.05b
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• pp.222-232
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• 2000

The relationship between carrier electron concentration(n) and atmosphere oxygen partial pressure($P_{O_2}$ for pure ZnO calculated by the mass-action law, well-known as n ${\propto}P^{-1/m}_{O_2}$ where m = 4 or 6 for the single or the double ionization of the native donor defects due to its nonstoichiometry, respectively, is found in competition with the calculation result on the basis that the total defect concentration is the sum of those of unionized and ionized defects. Definitively, it is found inconsistent with the calculation result by employing the Fermi-Dirac(FD) statistics for their ionization processes. By application of the FD statistics law to the ionization while assuming the defect formation is still ruled by the mass-action law, the calculation results shows the concentration is proportional to $P^{-1/2}_{O_2}$ whenever they ionize singly and/or doubly. Conclusively we would like to propose the new theoretical relation n ${\propto}P^{-1/m}_{O_2}$ because the ionization processes of donors in ZnO should be treated with the electronoccupation probability at localized quantum states in its forbidden band created by the donor defects, i.e. the FD statistics