• Proceedings of the KSR Conference
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• 2010.06a
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• pp.2048-2051
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• 2010

Almost all companies have paid much attention to the safety management ranging from maintenance to operation even at the stage of designing in order to prevent accidents, but fatal accidents continue to increase throughout the world. In particular, it is essential to systematically prevent such fatal accidents as fire, explosion or leakage of toxic gas at factories in order to not only protect the workers and neighbors but also prevent economic losses and environmental pollution. In addition, HRA may be used to detect the human errors which may cause accidents or trace back to any mistake on the part of workers. Usually, HRA technique is used in association with other risk assessment techniques. Moreover, it can serve to enumerate the human errors which may occur during operation or down-time or correct the existing system to reduce the mistakes. This work focuses on the coincidence of human error and mechanical failure for management of human error, and on some important performance shaping factors to propose a method for improving safety effectively of the process industries.

• Industrial Engineering and Management Systems
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• v.12 no.1
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• pp.41-45
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• 2013

Age replacement policy is a commonly policy in maintenance management of spare part. It means that a spare part is always replaced at failure or fixed time after its installation, whichever occurs first. An optimal age replacement policy of spare parts concerns with finding the optimal replacement time determined by minimizing the expected cost per unit time. The age of the part was generally assumed to be a random variable in the past literatures, but in many situations, there are few or even no observed data to estimate the probability distribution of part's lifetime. In order to solve this phenomenon, a new uncertain age replacement policy has been proposed recently, in which the age of the part was assumed to be an uncertain variable. This paper discusses the optimal age replacement policies by dealing with the parts' lifetimes as different distributed uncertain variables. Several results on the optimal age replacement time are provided when the lifetimes are described by the uncertain linear, zigzag and lognormal distributions.

• Korean Journal of Construction Engineering and Management
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• v.10 no.1
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• pp.126-135
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• 2009

Recently, operation of highway is the complex digital Infrastructure based on complicated IT. The application of IT is increasing more and more in digital Infrastructure. Though IT is very convenient, if unpredicted operating risk of highway occurs, widespread damage can be large. When operating risk of highway occurs, road users are out of smoothly-run service because of the operating interruption. This risk causes unpredicted operating management cost and additional maintenance cost. It will excess over the planned operating cost, which may leads to users's unsafety and operator's insolvency because of income loss. Until now, related studies to find out the risk are not sufficient. The purpose of this study is to suggest risk cost items and to estimate the reasonable risk cost by using simulation method in case of occurring the huge power failure at the operating digitalized highway. This study indicates the several plans to hedge against risk cost and the management of highway project. From now on, it will be used as basic data to confirm the soundness of operating system in Digital Infrastructure.

• Journal of the Korean Society for Railway
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• v.20 no.5
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• pp.703-712
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• 2017

The railway system is an interface industry that can be safely operated by organically operating the lines, vehicles, controls, etc. Various data are generated in the operation and maintenance activities of the railway system. These data are utilized in cooperation with safety and maintenance activities in each field, but amount of data is insufficient for data analysis of safety management due to relevant data being produced without any synchronous criteria such as time or space. In particular, reference data such as location and time of failure data for each field are set to different criteria according to the work characteristics in each field. So, it is not easy to analyze data integrally based on location and time. Therefore, mapping of reference data can be required for integrated analysis of data defined in different formats. By selecting data mapping tools and verifying the results of safety relevant data with the same criteria, the purpose of this paper is to enable integrated analysis of railway safety management data occurring in different fields based on location and time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1B
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• pp.22-30
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• 2007

In this paper, to achieve consistency maintenance as well as stable service execution, we build a Fault-Tolerant Object Group framework that provides both of the group management service and the load scheduling service. The group management service supports the object management such as registration and authentication, and provides two schemes for failure recovery using the service priority and the checkpointing. In the load scheduling servile, we improve the effectiveness of service execution through the reasoning process of object loads based on the ANFIS architecture. The effectiveness in the performance of the developed framework is validated through a virtual home-network simulation based on the FTOG framework.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.2
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• pp.113-121
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• 2023

High-precision lasers and anti-aircraft radars are the main equipment to protect the Korean Peninsula, and require preemptive maintenance before signs of failure. Of the key components in the drive sector, bearings do not have a fault alarm function. Therefore, the technology for diagnosing defects in bearings before the performance degradation of equipment occurs is becoming more important. In this paper, for the experimental analysis, we measured the acceleration of the four sets of the same lot using acceleration sensors. Through periodic measurements, the factors that changed until the bearing stopped rotating were analyzed. To determine the replacement time, the main factors and threshold values of the bearing signal were analyzed. The error of the theoretical and experimental analysis results of the defect frequency was within 2.8 %, and the validity of the theoretical analysis results could be confirmed. Based on the results, it is possible to remotely transmit trouble alerts to users through the system check function.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.96-104
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• 2017

A one-shot system (device) refers to a system that is stored for a long period of time and is then disposed of after a single mission because it is accompanied by a chemical reaction or physical destruction when it operates, such as shells, munitions in a defense weapon system and automobile airbags. Because these systems are primarily related with safety and life, it is required to maintain a high level of storage reliability. Storage reliability is the probability that the system will operate at a particular point in time after storage. Since the stored one-shot system can be confirmed only through inspection, periodic inspection and maintenance should be performed to maintain a high level of storage reliability. Since the one-shot system is characterized by a large loss in the event of a failure, it is necessary to determine an appropriate inspection period to maintain the storage reliability above the reliability goal. In this study, we propose an optimal inspection policy that minimizes the total cost while exceeding the reliability goal that the storage reliability is set in advance for the one-shot system in which periodic inspections are performed. We assume that the failure time is the Weibull distribution. And the cost model is presented considering the existing storage reliability model by Martinez and Kim et al. The cost components to be included in the cost model are the cost of inspection $c_1$, the cost of loss per unit time between failure and detection $c_2$, the cost of minimum repair of the detected breakdown of units $c_3$, and the overhaul cost $c_4$ of $R_s{\leq}R_g$. And in this paper, we will determine the optimal inspection policy to find the inspection period and number of tests that minimize the expected cost per unit time from the finite lifetime to the overhaul. Compare them through numerical examples.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.142-148
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• 2015

Due to advancements in technology and manufacturing capability, it is not uncommon that life tests yield no or few failures at low stress levels. In these situations it is difficult to analyse lifetime data and make meaningful inferences about product or system reliability. For some products or systems whose performance characteristics degrade over time, a failure is said to have occurred when a performance characteristic crosses a critical threshold. The measurements of the degradation characteristic contain much useful and credible information about product or system reliability. Degradation measurements of the performance characteristics of an unfailed unit at different times can directly relate reliability measures to physical characteristics. Reliability prediction based on physical performance measures can be an efficient and alternative method to estimate for some highly reliable parts or systems. If the degradation process and the distance between the last measurement and a specified threshold can be established, the remaining useful life is predicted in advance. In turn, this prediction leads to just in time maintenance decision to protect systems. In this paper, we describe techniques for mapping product or system which has degrading performance parameter to the associated classical reliability measures in the performance domain. This paper described a general modeling and analysis procedure for reliability prediction based on one dominant degradation performance characteristic considering pseudo degradation performance life trend model. This pseudo degradation trend model is based on probability modeling of a failure mechanism degradation trend and comparison of a projected distribution to pre-defined critical soft failure point in time or cycle.

• Journal of Korea Water Resources Association
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• v.43 no.11
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• pp.967-976
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• 2010

AFDA (Approximate Full Distribution Approach) model of FORM (First-Order Reliability Model) which can quantitatively calculate the probability that storm sewer reach to performance limit state was developed in this study. It was defined as a failure if amount of inflow exceed the capacity of storm sewer. Manning's equation and rational equation were used to determine the capacity and inflow of reliability function. Furthermore, statistical characteristics and distribution for the random variables were analyzed as a reliability analysis. It was found that the statistical distribution for annual maximum rainfall intensity of 10 cities in Korea is matched well with Gumbel distribution. Reliability model developed in this study was applied to Y shaped storm sewer system to calculate the probability that storm sewer may exceed the performance limit state. Probability of failure according to diameter was calculated using Manning's equation. Especially, probability of failure of storm sewer in Mungyeong and Daejeon was calculated using rainfall intensity of 50-year return period. It was found that probability of failure can be significantly increased if diameter is decreased below the original diameter. Therefore, cleaning the debris in sewer pipes to maintain the original pipe diameter should be one of the best ways to reduce the probability of failure of storm sewer. In sewer system, two sewer pipes can flow into one sewer pipe. For this case, probability of system failure was calculated using multiple failure mode. Reliability model developed in this study can be applied to design, maintenance, management, and control of storm sewer system.

• Journal of Korean Society for Quality Management
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• v.49 no.4
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• pp.581-594
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• 2021

Purpose: The purpose of this study is to compare machine learning models for anomaly detection of mechanical facility equipment and suggest an anomaly detection system for mechanical facility equipment in subway stations. It helps to predict failures and plan the maintenance of facility. Ultimately it aims to improve the quality of facility equipment. Methods: The data collected from Daejeon Metropolitan Rapid Transit Corporation was used in this experiment. The experiment was performed using Python, Scikit-learn, tensorflow 2.0 for preprocessing and machine learning. Also it was conducted in two failure states of the equipment. We compared and analyzed five unsupervised machine learning models focused on model Long Short-Term Memory Variational Autoencoder(LSTM-VAE). Results: In both experiments, change in vibration and current data was observed when there is a defect. When the rotating body failure was happened, the magnitude of vibration has increased but current has decreased. In situation of axis alignment failure, both of vibration and current have increased. In addition, model LSTM-VAE showed superior accuracy than the other four base-line models. Conclusion: According to the results, model LSTM-VAE showed outstanding performance with more than 97% of accuracy in the experiments. Thus, the quality of mechanical facility equipment will be improved if the proposed anomaly detection system is established with this model used.