• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.6
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• pp.1321-1329
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• 1993

Long time creep strength and life prediction of 1% Cr-Mo-V and 12% Cr rotor steel were performed by using round-bar type specimens under static load at 500-600.deg. C TTP (time temperature parameter), MCM (minimum commitment method) and ISM (initial strain method newly devised) as life prediction methods were investigated, and the results could be summarized as follows. (1) The minimum parameter of SEE (standard error) by TTP was proved as LMP (larson-miller parameter), and the minimum parameter of RMS (root mean squares), by data less than 10$^{3}$hrs was MHP (manson-haferd parameter). (2) The parameters of the minimum and the maximum strength values predicted in $10^{5}$hrs creep life of 1% Cr-Mo-V steel by TTP were LMP and MSP, respectively. In case of 12% Cr steel above $550^{\circ}C$ OSDP (orr-sherby-dorn parameter) was minimum and MSP (manson-succop parameter) was maximum, but below $550^{\circ}C$, the inverse phenomena was observed. On the other hand the creep strengths before $10^{3}hrs$ life by MCM were similar to those by TTP, but the strengths after $10^{3}hrs$ life were 10-25% lower than those by TTP. (3) Creep strengths by ISM were maximum 5% lower than those by TTP. Because $10^{5}hrs$ strengths were similar to those of the lower band by TTP, the ISM was safer than the TTP.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.18-30
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• 2022

Predicting remaining useful life (RUL) becomes significant to implement prognostics and health management of industrial systems. The relevant studies have contributed to creating RUL prediction models and validating their acceptable performance; however, they are confined to drive reasonable preventive maintenance strategies derived from and connected with such predictive models. This paper proposes a data-driven preventive maintenance method that predicts RUL of industrial systems and determines the optimal replacement time intervals to lead to cost minimization in preventive maintenance. The proposed method comprises: (1) generating RUL prediction models through learning historical process data by using machine learning techniques including random forest and extreme gradient boosting, and (2) applying the system failure time derived from the RUL prediction models to the Weibull distribution-based minimum-repair block replacement model for finding the cost-optimal block replacement time. The paper includes a case study to demonstrate the feasibility of the proposed method using an open dataset, wherein sensor data are generated and recorded from turbofan engine systems.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.2
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• pp.46-53
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• 2022

This paper presents the design and manufacture of a Solid State Relay (SSR) life prediction device that can predict the lifetime of an SSR, which is a key component of a glass forming machine. The lifetime of an SSR is over when the current supplied to the relay is overcurrent (20 A or higher), and the operating time is 100,000 h or longer. Therefore, the life prediction device for the SSR was designed using DSP to accurately read the current and temperature values from the current and temperature sensors, respectively. The characteristic test of the manufactured non-contact relay life prediction device confirmed that the current and temperature were safely measured. Thus, the SSR lifetime prediction device developed in this study can be used to predict the lifetime of an SSR attached to a glass forming machine.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.10 no.1
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• pp.64-69
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• 2014

Gr. 91 steel is used for the major structural components of Generation-IV reactor systems, such as a very high temperature reactor(VHTR) and sodium-cooled fast reactor(SFR). Since these structures are designed for up to 60 years at elevated temperatures, the prediction of long-term creep life is important for a design application of Gr. 91 steel. In this study, a number of creep rupture data were collected through world-wide literature surveys, and using these data, the long-term creep life was predicted in terms of three methods: the single-C method in Larson-Miller(L-M) parameter, multi-C constant method in the L-M parameter, and a modified method("sinh" equation) in the L-M parameter. The results of the creep-life prediction were compared using the standard deviation of error value, respectively. Modified method proposed by the "sinh" equation revealed better agreement in creep life prediction than the single-C L-M method.

• Steel and Composite Structures
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• v.9 no.6
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• pp.557-568
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• 2009

Fatigue tests for extremely thick plates require a great deal of manufacturing time and are expensive to perform. Therefore, if predictions could be made through simulation models such as an artificial neural network (ANN), manufacturing time and costs could be greatly reduced. In order to verify the effects of fatigue strength depending on the various factors in SM520C-TMC steels, this study constructed an ANN and conducted the learning process using the parameters of calculated stress concentration factor, thickness and input heat energy, etc. The results showed that the ANN could be applied to the prediction of fatigue life.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1883-1888
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• 2000

In this paper a computer aided analysis method is proposed for durability assessment in the early design stages using dynamic analysis, stress analysis and fatigue life prediction method. From dynamic analysis of a vehicle suspension system, dynamic load time histories of a suspension component are calculated. From the dynamic load time histories and the stress of the suspension component, a dynamic stress time history at the critical location is produced using the superposition principle. Using linear damage law and cycle counting method, fatigue life cycle is calculated. The predicted fatigue life cycle is verified by experimental durability tests.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.1019-1032
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• 2013

The accurate prediction of future mortality is an important issue due to recent rapid increases in life expectancy. An accurate estimation and prediction of mortality is important to future welfare policies. The optimal selection of a mortality model is important to estimate and predict mortality; however, the period of time series data used is also an important issue. It is essential to understand that the time series data for mortality is short in Korea and the data before 1982 is incomplete. This paper divides the time series of Korean mortality into two sets to compare the parameter estimates of the LC model and LC model with a cohort effect by the period of data used. A modeling and prediction of the mortality index and cohort effect index as well as the evaluation of future life expectancy is conducted. Finally, some suggestions are proposed for the future prediction of mortality.

• Journal of the Semiconductor & Display Technology
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• v.12 no.4
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• pp.45-48
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• 2013

The electronic device, such as flat panel display (FPD), is very important in our life as a means of communication between humans. Liquid crystal display (LCD), which is categorized as a flat panel display, has been used in many display products, especially in TV industry. An LED TV is composed of several electrical components, such as liquid critical module (LCM), analog to digital convertor (AD), power supplier, and inverter board. These modules are very vulnerable to particulate contamination, and causing malfunction or visibility degradation. In this study, we developed a test method for prediction of LCM's lifetime. The test system consists of carbon particle generation flame, dilution system, test chamber, and particle concentration monitoring instrument. Since the carbon particles are the most abundant in the atmosphere and easily absorb light, soot particles are used as a challenging material for this test. The concentration of generated soot particles is set around 4,000,000 #/cc, which is 400 times higher than that of usual atmospheric particles. Through this experiment, we deduced the relationship between the dust concentration and life time of the test specimen.

• Journal of Korean Society for Quality Management
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• v.35 no.2
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• pp.45-52
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• 2007

The danger of self-ignition of single base propellants will increase with time. Therefore, a good prediction of the safe storage time is very important. In order to determine the remaining shelf-life of the propellants, the content of stabilizer is determined. The propellants stored under normal storage conditions about 10 to 18 years were investigated and accelerated aging test was carried out by storing propellant sample at higher temperature. Finally, we analyzed the results by various methods in order to show the best way to predict the realistic shelf-life. The safe storage life of the propellants will be 24 years, at least 15 years. In case of applying Arrhenius's law, using the reaction rate constant at 28$^{\circ}C$ to 30$^{\circ}C$ to predict the shelf-life by accelerated aging test is reasonable for a good prediction.

• International Journal of Railway
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• v.1 no.3
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• pp.122-127
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• 2008

Rubber components are widely used in many application such as vibration isolators, damping, ride quality. Rubber spring is used in primary suspension system for railway vehicle. Characteristics and useful life prediction of rubber spring was very important in design procedure to assure the safety and reliability. Non-linear properties of rubber material which are described as strain energy function are important parameter to design and evaluate of rubber spring. These are determined by physical tests which are uniaxial tension, equi-biaxial tension and pure shear test. The computer simulation was executed to predict and evaluate the load capacity and stiffness for rubber spring. In order to investigate the useful life, the acceleration test were carried out. Acceleration test results changes as the threshold are used for assessment of the useful life and time to threshold value were plotted against reciprocal of absolute temperature to give the Arrhenius plot. By using the acceleration test, several useful life prediction for rubber spring were proposed.