• Journal of the Korean Society for Railway
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• v.13 no.3
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• pp.257-263
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• 2010

Operation and maintenance cost of a rolling stock is generally higher than its acquisition cost. Therefore, it is necessary for reducing life cycle cost (LCC) to make rolling stocks easy and low costly for operation and maintenance. In addition, their operation and maintenance support systems should be effective and efficient. To accomplish this, operator should specify LCC requirements in the early stage of acquisition and make a contractor to provide the rolling stocks of low LCC. This article presents a procedure and a verifiable LCC model available in the general acquisition process where an operator specify requirements and a contractor provide the rolling stock meeting the requirements.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1650-1655
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• 2010

This paper presents an activation plan for reliability centered maintenance (RCM) of rolling stock. The KTX is carrying out the maintenance in compliance with RCM. MKBSF, that is one of the reliability indices for KTX, is shown 183,483 km in 2009, whereas it is shown 68,986 km in 2004. It means that the reliability of KTX has been growing every year. It also is result of reliability management activities. KORAIL did not apply RCM until now about the conventional rolling stocks. But KORAIL decided that applies RCM system because of reliability management effect of KTX. In this study, we tried to know an activation plan for the reliability centered maintenance of the conventional rolling stocks.

• International Journal of Railway
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• v.1 no.3
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• pp.94-98
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• 2008

Static inverters are essential devices onboard of rolling stock. State-of-the-art static inverters have an impact on both rail infrastructure and vehicle maintenance due to their new topology with new features. The paper describes two important aspects as examples of new features available in state-of-the-art static inverters: active input current control and the effects on the rail infrastructure as well as the detection of the state of charge and the state of health of batteries to simplify vehicle maintenance.

• Journal of the Korean Society for Railway
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• v.10 no.2 s.39
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• pp.195-200
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• 2007

The most important part of RIMS(Rolling Stock Information Maintenance System) project is to construct BOM(Bill of Material). BOM is a listing or description of raw materials, parts, and assemblies that define a product. To construct BOM for RIMS is not a easy task due to several reasons such as data base scale and flexibility, proper integration between physical BOM and functional BOM, interoperability with other systems, etc. In this study we show several principles that Seoul Metro takes to get over the difficulties mentioned above. Based on these principles we propose the methodology Seoul Metro employs to construct BOM efficiently. We also discuss the applicability of BOM in several fields.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1301-1307
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• 2008

The Seoul-Metro is the first city railroad corporation to operate RIMS(Rolling-stock Information Maintenance System). The development of "RIMS Project" and trial running task were started from Mar 29, 2001. Finally, this project was completed successfully on Dec 31, 2005, as integrated systems including light or heavy maintenance works in Ji-Chuk and Chang-Dong Rolling-stock Offices. After that, from 2006 to Dec 31, 2007, we promoted a this new program to other four rolling-stock offices (Su-Seo, Gun-Ja, Sin-Jeong) and the headquarter. For the duration of trial running, we developed and applied new complementary program having made up for the weak points or defects. The series of new program which were newly developed and applied are comprised of an operation management, trouble management, wheel management, heavy maintenance table automatic creation programs and ordering prediction programs to purchase goods smoothly. The Seoul-Metro have registered these programs(RIMS) to Computer Program Protection Committee. We'd like to introduce a composition of program for enhancement of a city railroad Information Systems.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.57-64
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• 2007

RIMS（Rolling Stock Information Maintenance System)　was installed in structure which it can analyze the data base in need of credibility maintenance. So it could accumulate real data without repulsion of working spot. Information system was installed not following to system but following to working spot. The development of RIMS project was started from March 29, 2001 and it has been operating from October 12, 2004 in Chang-dong Car depot for light maintenance in charge subway line4. So substantial data base was accumulated for three years. This study calculated all RAMS data by analyzing data base accumulated in RIMS and used in dada base about credibility maintenance and found investigation of propriety, expectation of the life cycle cost, the improvement plan on credibility of sorts of cars and formation about the cycle of repairing and maintenance. This got MKBSF MKBF and MTBF about devices and sorts of line4 Rolling Stocks for it.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.143-150
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• 2007

RIMS（Rolling Stock Information Maintenance System)　was installed in structure which it can analyze the data base in need of credibility maintenance. So it could accumulate real data without repulsion of working spot. Information system was installed not following to system but following to working spot. The development of RIMS project was started from March 29, 2001 and it has been operating from October 12, 2004 in Chang-dong Car depot for light maintenance in charge subway line4. So substantial data base was accumulated for three years. This study calculated all RAMS data by analyzing data base accumulated in RIMS and used in dada base about credibility maintenance and found investigation of propriety, expectation of the life cycle cost, the improvement plan on credibility of sorts of cars and formation about the cycle of repairing and maintenance. This got MKBSF MKBF and MTBF about devices and sorts of line4 Rolling Stocks for it.

• Proceedings of the KSR Conference
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• 2002.05a
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• pp.423-430
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• 2002

This study was started to develop maintenance technology for wheel tread suitable domestic railway environment. As a pre-study to develop optima] wheel tread, we analyzed the wear characteristics of wheel tread that is being applied to railway rolling-stock in KNR. To analyze wheel wear characteristics. we have conducted the simulation and experiment for passenger rolling-stock and obtained useful datum. Here, we describe some results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.1597-1598
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• 2013

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.57-64
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• 2017

In order to reduce damages to major railroad components, which have the potential to cause interruptions to railroad services and safety accidents and to generate unnecessary maintenance costs, the development of rolling stock maintenance technology is switching from preventive maintenance based on the inspection period to predictive maintenance technology, led by advanced countries. Furthermore, to enhance trust in accordance with the speedup of system and reduce maintenances cost simultaneously, the demand for fault diagnosis and prognostic health management technology is increasing. The objective of this paper is to propose a highly reliable learning model using various machine learning algorithms that can be applied to critical rolling stock components. This paper presents a model for railway rolling stock component fault diagnosis and conducts a mechanical failure diagnosis of motor components by applying the machine learning technique in order to ensure efficient maintenance support along with a data preprocessing plan for component fault diagnosis. This paper first defines a failure diagnosis model for rolling stock components. Function-based algorithms ANFIS and SMO were used as machine learning techniques for generating the failure diagnosis model. Two tree-based algorithms, RadomForest and CART, were also employed. In order to evaluate the performance of the algorithms to be used for diagnosing failures in motors as a critical railroad component, an experiment was carried out on 2 data sets with different classes (includes 6 classes and 3 class levels). According to the results of the experiment, the random forest algorithm, a tree-based machine learning technique, showed the best performance.