• Corrosion Science and Technology
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• v.11 no.2
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• pp.43-47
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• 2012

Recently, regulatory bodies quite often encourage to adopt risk-based inspection (RBI) and management programs because they can enhance safety simultaneously with deregulation in Korea. RBI is an integrated methodology that factors risk into inspection and maintenance decision making. This paper describes an example of how to use known risk assessment codes (API 580, API 581 BRD) to address such safety analysis requirements for risk management in the refining industry. Specifically, this paper reports the methodology and the results of implementation to the Crude Distillation Unit(CDU) plant of refinery units using the $KGS-RBI^{TM}$ program, developed by the Korea Gas Safety Corporation in reference of API Codes and ASME PC (Post Construction) with a suitable consideration of Korean situation. The results of the risk and reliability assessment using $KGS-RBI^{TM}$ program are useful in determining whether the detected defects are tolerable or required to be repaired. The subsequent decisions are to manage the future inspection, repair and maintenance planning in the risk reduction control.

• Journal of Korea Port Economic Association
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• v.23 no.4
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• pp.23-47
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• 2007

We analyzed the questionnaire survey for the current maintenance of Incheon port's loading and unloading equipments and the possibility of TPM(Total Productive Maintenance) application. And also, We certificated Structural Equation Model with computer packages. Results of the survey indicated that the current maintenance of Incheon port's loading and unloading equipments was not good. We recognized the relationship of contextual factors about the productivity of the loading and unloading equipments The productivity of the loading and unloading equipment positively depends on maintenance management of equipments, but the organization and personnel management does not have a influence on the productivity of the loading and unloading equipment. So we suggest TPM as the future maintenance methodology of equipments. Using TPM to the loading and unloading equipments, we will try to improve the methodology of the organization and personnel management.

• Journal of the Korea Safety Management & Science
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• v.8 no.2
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• pp.169-184
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• 2006

We analyzed the questionnaire survey for the current maintenance of Incheon port's loading and unloading equipments and the possibility of TPM(Total Productive Maintenance) application. Results of the survey indicated that the current maintenance of Incheon port's loading and unloading equipments was not good. So we suggest TPM as the future maintenance methodology of equipments. Using TPM to the loading and unloading equipments we will expect to improve the productivity of the loading and unloading operation and to increase the life time of equipment. And also it will raise the safety of Incheon port.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.440-449
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• 2007

This paper describes the efforts in developing several versions of bridge management system (BMS) in Taiwan. There were several versions of stand-alone BMS developed in Taiwan prior to the Ji-Ji earthquake that occurred in year 1999. Since many bridges were seriously damaged by this earthquake, the Ministry of Transportation and Communication determined to develop a nationwide BMS to have a better by control on the status of bridge maintenance. Implemented in year 2000, the Taiwan Bridge Management system (T-BMS) is now the dominating and mandatory system used by all the government agencies that are responsible for bridge maintenance. Having more then 25,000 bridges in its inventory, T-BMS has thousands of logins per month to update data in the relevant database. The experiences and difficulties of using such a nationwide bridge management system are discussed. Finally, future plans for BMS development are also proposed in this paper.

• Journal of the Korean Society for Railway
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• v.7 no.3
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• pp.223-231
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• 2004

The accumulated BMS data have made it easy to make reasonable decision-making for bride maintenance and repair work. In the developing period of BMS, the bridge management was not easy due to the lack of understanding of BMS and low credibility of the data. In recent years, it has been possible to enhance the credibility of the data and to expand the application scopes of BMS with the efforts of Local Road Construction Offices. The reasonable decision making for bridge management can improve the performance of bridges under the practical constraints such as limited budget. It can then result in the reduction of bridge maintenance budget. This study provides the methodology for the application of mobile internet-based KOBMS for bridge management. The data flow for BMS is the most important factor for decision-making on budget allocation, and this study establishes the basic scheme of the data flow for BMS. The implementation of PDA for BMS may suggest a new paradigm of 'Mobile' in the field of construction management.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.227-233
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• 2021

Predictive maintenance has been one of important applications of data science technology that creates a predictive model by collecting numerous data related to management targeted equipment. It does not predict equipment failure with just one or two signs, but quantifies and models numerous symptoms and historical data of actual failure. Statistical methods were used a lot in the past as this predictive maintenance method, but recently, many machine learning-based methods have been proposed. Such proposed machine learning-based methods are preferable in that they show more accurate prediction performance. However, with the exception of some learning models such as decision tree-based models, it is very difficult to explicitly know the structure of learning models (Black-Box Model) and to explain to what extent certain attributes (features or variables) of the learning model affected the prediction results. To overcome this problem, a recently proposed study is an explainable artificial intelligence (AI). It is a methodology that makes it easy for users to understand and trust the results of machine learning-based learning models. In this paper, we propose an explainable AI method to further enhance the explanatory power of the existing learning model by targeting the previously proposedpredictive model [5] that learned data from a core facility (Hyper Compressor) of a domestic chemical plant that produces polyethylene. The ensemble prediction model, which is a black box model, wasconverted to a white box model using the Explainable AI. The proposed methodology explains the direction of control for the major features in the failure prediction results through the Explainable AI. Through this methodology, it is possible to flexibly replace the timing of maintenance of the machine and supply and demand of parts, and to improve the efficiency of the facility operation through proper pre-control.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1008-1012
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• 1987

This paper describes the general approach to ISDN operation & maintenance. First we focused on the CCITT SG XVIII activities on the ISDN. As a general principles for operating and maintaining an ISDN they propose TMN(Telecommunication Management Network) concept which specifies several OM function modules and standard interfaces. Based on the concept we studied proper methodology to set up an efficient OM structure under the ISDN environments.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.05a
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• pp.162-163
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• 2014

Operation and maintenance stage consists the largest portion of project life cycle cost. Appropriate management and analysis of such stages have massive effect on the total project cost. The effective prediction of optimized repair period is one of main factors in ㅌ management. However, it has been analyzed that the prediction of appropriate repair period revealed limitations in reliability. Therefore, this study suggests a methodology of repair period prediction by dividing finished projects into similar groups with same properties to be compared with the target project using quantitative variables.

• Proceedings of the Korea Database Society Conference
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• 1998.09a
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• pp.448-474
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• 1998

Data warehouse (DW) is important for analytical processing. Metadata is a key to its architecture. This paper proposes an architecture that consists of seven components. To illustrate data warehouse environment (DWE), this Paper proposes taxonomies having four flows. on the basis or the taxonomies and metadata, this paper proposes a methodology for building the data warehouse and metadata simultaneously. This integrated development methodology (IDM) consists of seven phases: (i) preparatory phase, (ii) requirement analysis phase, (iii) data warehouse development phase, (iv) operational data store development phase, (v) data mart development phase, (vi) metastore development phase, and (vii) maintenance phase. A metastore system is Proposed to help develop metadata interactively. An illustrative example is investigated to demonstrate the usefulness of IDM.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.66-73
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• 2011

With rapid industrialization, electric power consumption has been increasing every year in Korea and in other countries. The provision of additional power stations to produce more electricity is one possible response to this steady increase in consumption. Another alternative is to improve the efficiency of existing stations through timely and effective maintenance works. Since the construction of a new power plant involves a large amount of capital as well as difficulties in the selection of sites, the improvement of existing power stations' efficiencies is often a preferred solution. Therefore, this paper focuses on maintenance project management to address this issue. Among several types of maintenance works, this paper concentrates on planned outage maintenance (POM). This focus arises from the critical impact of POM on other maintenance work, as well as the entire process of electricity production. Unlike other maintenance work, POM is done on the basis of mid and long-term plans. In addition, only POM works are conducted during the outage of all power plants. To evaluate the efficiency of POM works, budget data relating to 164 POM projects between 2001 and 2008 was collected from 7 sites in South Korea. Data envelopment analysis (DEA) was selected as a methodology for evaluation. From this analysis, comparative study was used to determine the categories of projects that had performed well, and those with the most optimized budget structures. Moreover, through discussion with industry, this research develops a feasible proposed method by which to enhance the efficiency of POM projects.