• Journal of KIISE:Software and Applications
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• v.36 no.9
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• pp.718-731
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• 2009

Software Maintenance needs to continually improve from corrective maintenance to operational management and service improvement. In this study, we propose a software maintenance maturity model and its evaluation criteria based on 4 maintenance projects of K organization. For the proposal, we derive 13 process areas and 64 evaluation criteria based on some references such as SMMM, ITSMM, ITIL. We evaluate the criteria using 5-point scale, and then establish the maturity model of K organization classified by levels of the maturity model based on the evaluation result. And, to verify and improve the maturity model of K organization, we propose improvements for evaluation criteria. In addition, we apply the maturity model to the 4 projects, evaluate the projects, and propose improvements for the projects based on the evaluation result to identify how the model shows software maintenance improvement.

• Journal of the Korean Society for Railway
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• v.9 no.6 s.37
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• pp.739-745
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• 2006

The role of maintenance in railway is going to be extended to improve the reliability of railway system in the aspect of Asset management gradually. In this paper, the meaning of reliability and safety in RCM which has been applied in order to improve the efficiency of maintenance is deduced. And the analysis task of reliability and safely which has been recommended in railway standards such as EN50126 and IEC62278 is reviewed in the aspect of RCM. Finally, the several ways are proposed to apply RCM to railway system through the comparison between the RCM procedure and the analysis procedure for the reliability and safety in railway standards. Hereafter, if the analysis of reliability and safety is performed with the concept of RCM in the beginning of railway business, it will be more efficient to improve the reliability and manage the railway asset.

• Journal of Applied Reliability
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• v.10 no.2
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• pp.93-105
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• 2010

The following thesis provides an explanation for the definition of the MIL-HDBK-2155 : Failure Reporting, Analysis and Corrective Action System (FRACAS), which systemizes the collection and analysis of failure data and the feedback process of the results. It also presents a plan based on MIL-HDBK-2155 for the collection and analysis of operating specifications on weapon systems. The collection and analysis of failure data and the feedback process utilizing FRACAS contributes to identifying improvement requirements during equipment operation as well as finding and eliminating the root cause of the failures. The objective of applying FRACAS to weapon systems is to receive source data feedback for reliability enhancements and performance improvements during operation. This is done by recognizing weaknesses in the design or operation by identifying the type of failures that might occur, and by performing Failure Modes, Effects and Criticality Analysis(FMECA) and Failure Tree Analysis(FTA).

• Nuclear Engineering and Technology
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• v.40 no.7
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• pp.615-624
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• 2008

In this paper, the contribution of task types and error types involved in the human-related unplanned reactor trip events that have occurred between 1986 and 2006 in Korean nuclear power plants are analysed in order to establish a strategy for reducing the human-related unplanned reactor trips. Classification systems for the task types, error modes, and cognitive functions are developed or adopted from the currently available taxonomies, and the relevant information is extracted from the event reports or judged on the basis of an event description. According to the analyses from this study, the contributions of the task types are as follows: corrective maintenance (25.7%), planned maintenance (22.8%), planned operation (19.8%), periodic preventive maintenance (14.9%), response to a transient (9.9%), and design/manufacturing/installation (6.9%). According to the analysis of the error modes, error modes such as control failure (22.2%), wrong object (18.5%), omission (14.8%), wrong action (11.1 %), and inadequate (8.3%) take up about 75% of the total unplanned trip events. The analysis of the cognitive functions involved in the events indicated that the planning function had the highest contribution (46.7%) to the human actions leading to unplanned reactor trips. This analysis concludes that in order to significantly reduce human-induced or human-related unplanned reactor trips, an aide system (in support of maintenance personnel) for evaluating possible (negative) impacts of planned actions or erroneous actions as well as an appropriate human error prediction technique, should be developed.

• Computers and Concrete
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• v.14 no.6
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• pp.727-743
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• 2014

The management of existing concrete bridges has become a major social concern in many developed countries due to the large number of bridges exhibiting signs of significant deterioration. This problem has increased the demand for effective maintenance and renewal planning. In order to implement an appropriate management procedure for a structure, a wide array of corrective strategies must be evaluated with respect to not only the condition state of each defect but also safety, economy and sustainability. This paper describes a new performance evaluation system for existing concrete bridges. The system evaluates performance based on load carrying capability and durability from the results of a visual inspection and specification data, and describes the necessity of maintenance. It categorizes all girders and slabs as either unsafe, severe deterioration, moderate deterioration, mild deterioration, or safe. The technique employs an expert system with an appropriate knowledge base in the evaluation. A characteristic feature of the system is the use of neural networks to evaluate the performance and facilitate refinement of the knowledge base. The neural network proposed in the present study has the capability to prevent an inference process and knowledge base from becoming a black box. It is very important that the system is capable of detailing how the performance is calculated since the road network represents a huge investment. The effectiveness of the neural network and machine learning method is verified by comparing diagnostic results by bridge experts.

• Geomechanics and Engineering
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• v.4 no.3
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• pp.219-227
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• 2012

Pavement management systems require systematic monitoring of pavement surfaces to determine preventive and corrective maintenance. The process involves the accumulation of large amounts of visual data, typically obtained from site visitation. The pavement surface condition is then correlated to a pavement distress index that is based on a scoring system previously established by state or federal agencies. The scoring system determines if the pavement section requires maintenance, overlay or reconstruction. One of the surface distresses forming part of the overall pavement distress index is the Alligator Crack Index (AC Index). The AC Index involves the visual evaluation of the crack severity of a section of a pavement as being low, medium, or high. This evaluation is then integrated into a formula in order to obtain the AC Index. In this study a quantification of the visual evaluation of the severity of alligator cracking is carried out using photographs and the fractal dimension concept from fractal theory. Pavements with low levels of cracking were found to have a fractal dimension equal to 1.051. Pavements with moderate levels of cracking had a fractal dimension equal to 1.1754. Pavements with high degrees of cracking had a fractal dimension that varied between 1.5037 (high) and 1.7111 (very high). Pavements with a level of cracking equal to 1.8976 represented pavements that disintegrated and developed potholes. Thus, the visual evaluation of the state of cracking of a pavement (the AC Index) could be enhanced with the use of the fractal dimension concept from fractal theory.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.5
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• pp.60-67
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• 2014

Wind power is one of the fastest growing renewable energy sources. The blades length and tower height of wind turbine have been growing steadily in the last 10 years in order to increase the output amount of wind power energy. The amount of wind turbine energy is increased by increasing the capacity of wind turbine, but the costs of preventive, corrective and replacement maintenance are also increased accordingly. Recently, Condition Monitoring System that can repair the fault diagnose and repair of wind turbine in the real-time. However, these system have a problem that cannot predict and diagnose of the fault. In this paper, wind turbine predict methodology is proposed by using the SVM method. In the case study, correlation analysis between wind turbine fault and external environmental factors is performed by using the SVM method.

• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.2041-2049
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• 1998

This paper suggests a technique for program segmentation and maintenance using PSDG(Post-State Dependency Graph) that improves the quality of a software by identifying and detecting defects in already fixed source code. A program segmentation is performed by utilizing source code analysis which combines the measures of static, dynamic and semantic slicing when we need understandability of defect in programs for corrective maintanence. It provides users with a segmental principle to split a program by tracing state dependency of a source code with the graph, and clustering and highlighting, Through a modeling of the PSDG, elimination of ineffective program deadcode and generalization of related program segments arc possible, Additionally, it can be correlated with other design modeb as STD(State Transition Diagram), also be used as design documents.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.1
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• pp.84-97
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• 2020

This paper aims to develop an optimized inventory management method for safety critical Instrument and Control (I&C) components. In this regard, the paper focuses on estimating the consumption rate of I&C components using demand forecasting methods. The target component for this paper is the Foxboro SPEC-200 controller. This component was chosen because it has highest consumption rate among the safety critical I&C components in Korean OPR-1000 NPPs. Three analytical methods were chosen in order to develop the demand forecasting methods; Poisson, Generalized Linear Model (GLM) and Bootstrapping. The results show that the GLM gives better accuracy than the other analytical methods. This is because the GLM considers the maintenance level of the component by discriminating between corrective and preventive.

• KCID journal
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• v.18 no.2
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• pp.142-160
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• 2011

This study was performed to apply the preventive management technique that is known for more economic and preventive for disaster than corrective technique to Repair & Improvement(R&I) Project policy of irrigational facilities. The appropriate periods of R&I Project had been driven to 40yrs, 24yrs, 27yrs, and 29yrs for reservoir, Pumping and drainage pumping station, Diversion weir and Irrigation & drainage canal respectively. The cost of R&I Project for 10 years had been estimated as 616.9 billion won per year including the 85 billion won for the project of 'Disaster prevention and Function continuity'. After the period of 'Improvement all at once', about 30yrs, 421.8 billion won was requested for 'Function continuity'.