Purpose: Maintaining appropriate operational availability (Ao) is a key element of combat victory, but estimates vary according to estimation methods. The purpose of this study is to improve the accuracy of estimating operational availability by tracing the changes of the weapon system's failure rate, repair rate, and the level of logistic support. Methods: In order to track the change in the operating availability, the MDT (mean down time) is modeled by adding the repair time and the ALDT (administration and logistic delay time) to the service time. Results: Using the field data of the weapon system A operated by the ROKAF, the failure rate follows a non-homogeneous Poisson process that changes with time, and it is modeled considering the changing repair rate and the logistic support time. Conclusion: The accuracy of the analytical results was verified by comparing the actual operating data with the estimated availability. The results of this study can be used to track and evaluate the availability in a realistic situation where the failure rate and maintenance rate continuously change in operating environment.

Purpose: This study has developed the accelerated lifetime test method for smps for outdoor lighting LED through two factors of temperature and humidity. Methods: Acceleration condition was confirmed for each stress and model, and acceleration life test model was estimated according to acceleration condition. Results: As a result of confirming the accelerated life test model, in the case of humidity, acceleration was established only in the foreign products. Therefore, it is confirmed that the acceleration condition is insufficient. However, the estimated parameters for temperature are relatively constant. It is therefore suitable for power supply acceleration tests for outdoor lighting LEDs. Conclusion: The SMPS acceleration test for outdoor lighting LED can improve the availability of the product by developing an accelerated life test method that guarantees the reliability of the product.

Purpose: The purpose of this study is to set up an anomaly detection criteria for sensor data coming from a motorcycle. Methods: Five sensor values for accelerator pedal, engine rpm, transmission rpm, gear and speed are obtained every 0.02 second from a motorcycle. Exploratory data analysis is used to find any pattern in the data. Traditional process control methods such as X control chart and time series models are fitted to find any anomaly behavior in the data. Finally unsupervised learning algorithm such as k-means clustering is used to find any anomaly spot in the sensor data. Results: According to exploratory data analysis, the distribution of accelerator pedal sensor values is very much skewed to the left. The motorcycle seemed to have been driven in a city at speed less than 45 kilometers per hour. Traditional process control charts such as X control chart fail due to severe autocorrelation in each sensor data. However, ARIMA model found three abnormal points where they are beyond 2 sigma limits in the control chart. We applied a copula based Markov chain to perform statistical process control for correlated observations. Copula based Markov model found anomaly behavior in the similar places as ARIMA model. In an unsupervised learning algorithm, large sensor values get subdivided into two, three, and four disjoint regions. So extreme sensor values are the ones that need to be tracked down for any sign of anomaly behavior in the sensor values. Conclusion: Exploratory data analysis is useful to find any pattern in the sensor data. Process control chart using ARIMA and Joe's copula based Markov model also give warnings near similar places in the data. Unsupervised learning algorithm shows us that the extreme sensor values are the ones that need to be tracked down for any sign of anomaly behavior.

Purpose: Accelerated degradation tests can be effective in assessing product reliability when degradation leading to failure can be observed. This article proposes an accelerated degradation test model for highly reliable solid state drives (SSDs). Methods: We suggest a nonlinear mixed-effects (NLME) model to degradation data for SSDs. A Monte Carlo simulation is used to estimate lifetime distribution in accelerated degradation testing data. This simulation is performed by generating random samples from the assumed NLME model. Conclusion: We apply the proposed method to degradation data collected from SSDs. The derived power model is shown to be much better at fitting the degradation data than other existing models. Finally, the Monte Carlo simulation based on the NLME model provides reasonable results in lifetime estimation.

Purpose: This research is to develop Trailer Durability Test of towing device, in order to cover usage conditions of bike type as well as general type trailer. With the diversification of leisure activities, the population that enjoys various sports and leisure has increased rapidly, and the number of vehicles equipped with camping trailers and bike carriers is also increasing steadily. The purpose of this study is to develop a durable vehicle that has no problem in various customer conditions. Methods: We measured the input load under various conditions of the user by attaching load cell to the body fixing part and towing ball of the towing device. The load in various modes was measured, and the difference between the trailer and the bike carrier type was compared and analyzed. Results: Due to the difference in fixing method and weight between the two types, the trailer has a large longitudinal force and the bike type has a large vertical force. Therefore, it is necessary to durability test method capable of satisfying all longitudinal force and vertical force. Conclusion: We improved the durability test of the towing device by changing the test surface. The new mode has made it possible to shorten the durability test schedule by increasing test efficiency.

Purpose: To propose improved method for normalization, compare to the de facto international standard which is IESNA TM-21 or conventional normalization methods. Methods: Firstly, we analysed conventional methods and specified the problem of normalization method which is based on first measured data. Secondly, we proposed our approach which is based on the design specification. Lastly, we studied a real degradation data which is conducted for 15,000 hours. Conclusion: Proposed normalization method is better approach because it can reflect real data and design specification, and reduce distortion when analysing degradation data. Also, It is appliable to other long-life reliability items.

Purpose: The purpose of this study is to estimate shelf life of fuze MTSQ (Mechanical Time & Super Quick) KM577A1 from Ammunition Stockpile Reliability Program (ASRP) data. Methods: For many years, ammunition test data had been gathered from ASRP. In this study, lot selection criteria and reliability score of functioning time for fuze are proposed. Reliability score of functioning time and failure data are used to estimate shelf life. Results: The results of this study are as follows; The failure modes of fuze MTSQ KM577A1 are dud, inverse function and mechanical time functioning failure (not operating in intended time). Dud and inverse function are major failure modes. Fuze MTSQ KM577A1's shelf life ($B_5$) is estimated 18.2 years conservatively. Conclusion: Degradation of chemical components in fuze MTSQ KM577A1 is major factor for its reliability. And shelf life ($B_5$) of fuze MTSQ KM577A1 is estimated 18.2 years conservatively.

Purpose: Performance recovered from SCR through cleaning was studied, measuring differential pressure, NOx reduction efficiency, fuel consumption and engine power before and after cleaning. Ideal cleaning intervals are proposed based on SCR mileage and differential pressure. SCR endurance and reliability improvements through cleaning were studied through physicochemical testing of SCR durability at 43,000km 50,000km, and 110,000km respectively. Methods: Engine power, fuel consumption and exhaust gas were measured using engine full load tests and ND-13 MODE by installing the SCR before cleaned at total engine mileages of 400,000 km, 300,000km and 200,000km. The same tests were performed after cleaning the SCR catalytic converter. Endurance and reliability of the SCR cleaning was studied through the same test by SCR catalyst after each 43,000km 50,000km, 110,000km, durability test on SCR cleaning. Conclusion: We confirmed the low-performance of the SCR due to clogging is restored by SCR cleaning technology. The NOx reduction efficiency was restored to 82%, 86% and 88% from 69%, 72% and 79%. As well as the NOx reduction efficiency, it was confirmed that the engine power, fuel consumption and back pressure was restored to fresh SCR levels. As a result of the durability and reliability achieved through SCR cleaning, we confined the appearance and reduction efficiency through visual inspection and ND-13 MODE are similar to new SCR catalysts. Finally, it was judged that there was no change in performance even when driving the SCR without cleaning throughout the 100,000 km mileage warranty.

Purpose: Numerical and experimental study was performed to evaluate the effect of peening temperature on the residual compressive stress distribution and magnitude of residual compressive stress at the material surface. Methods: A compressive air-propelled warm peening equipment was designed and manufactured for warm peening test. Results: 3D dynamic finite element (FE) model of the warm peening test was proposed and validity of the proposed FE model was verified by comparing the predicted residual stresses with the measured residual stresses in the open literature. Maximum warm peening temperature and a proper peening time were investigated with the proposed FE model. Conclusion: Compressive residual stress increased remarkably with peening temperature increased. But, peening temperature is greater than $350^{\circ}C$, the effect of peening temperature disappeared. Therefore, maximum peening temperature possibly applicable for warm peening industry might be $350^{\circ}C$ and peening time is 45s.

Purpose: This article provides a mathematical model for the accelerated degradation test when the performance degradation characteristic follows the lognormal distribution. Method: For developing test plans, the total number of test units and the test time are determined based on the minimization of the asymptotic variance of the q-th quantile of the lifetime distribution at the use condition. Results: The mathematical model for the accelerated degradation test is provided. Conclusion: Accelerated degradation test method is widely used to evaluate the product lifetime within a resonable amount of cost and time. In this article. a mathematical model for the accelerated degradation test method is newly developed for this purposes.

Purpose: In this study, the defect quantification of thin metal plate was evaluated by using lock-in infrared thermography. Methods: A STS304 standard specimens, which had the artificial-defects of different size, were used. The focal distance between the infrared camera and the specimen was set to 500mm, and the distance between the lump and the specimen was set to 200mm. One halogen lamp with a maximum capacity of 1kW was used, and phase-lock infrared thermal images with a frequency of 1Hz were captured and analyzed. Result: Objectively quantified data values were obtained by analyzing the contrast ratio and signal-to-noise ratio. Conclusion: The possibility of defect diagnosis for thin metal plate was confirmed by using the lock-in infrared thermography technique.