• 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.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.597-602
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• 2011

A robust asset management methodology is essential for effective decision-making of maintenance, repair and rehabilitation of a bridge network. It can be achieved by a computer-based bridge management system (BMS). Successful BMS development requires a reliable bridge deterioration model, which is the most crucial component in a BMS, and an optimal management philosophy. The maintenance optimization methodology proposed in this paper is developed for a small bridge network with limited structural condition rating records. . The methodology is organized in three major components: (1) bridge health index (BHI); (2) maintenance and budget optimization; and (3) reliable Artificial Intelligence (AI) based bridge deterioration model. The outcomes of the paper will help to identify BMS implementation problems and to provide appropriate solutions for managing small bridge networks.

• 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 societal Security
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• v.1 no.4
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• pp.41-49
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• 2008

As bridges have been longer and bigger recently, lots of bridge management systems (BMS) have been developed for each bridge. However, the differences among the data models developed by different system developers give a serious problem in integrated information management for national security. The aim of this study is to develop a common data model which can be referred in development of the BMS. The existing BMS and work process by laws are carefully analyzed. Based on the analysis results, the bridge management and maintenance process is categorized into the four basic activity types. In addition, common data models for each the unit activity type are defined.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.533-538
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• 2005

An outline of an Artificial Neural Network (ANN) model for bridge condition rating and the results of a pilot study are presented in this paper. Most BMS implementation systems involve an extensive range of data collection to operate accurately. It takes many years to effectively implement a BMS using existing methodologies. This is due to unmatched data requirements. Such problems can be overcome by adopting the ANN model presented in this paper. The objective of the proposed model is to predict bridge condition ratings using historical bridge inspection data for effective BMS operation.

• Spatial Information Research
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• v.14 no.4 s.39
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• pp.421-431
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• 2006

Nowadays, the importance of safety monitoring for facilities is increasing. Therefore, the introduction of ubiquitous technology to replace the existing manually-operated methods is required. In this study, a web-based GIS system that provides monitoring information of bridges in real-time for the application of a bridge management system through the use of ubiquitous technology is constructed. Particular attention is given to the effective interconnection of bridge monitoring information and bridge management system and, through a ubiquitous environment, how to connect this with the UFID and the GIS-based bridge management system (BMS) operated by the Ministry of Construction and Transportation. In addition, data expression methods are also suggested that state the detailed locations and attributes of structures in bridge management by using GIS.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.13-20
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• 2016

The computerized management system for bridges is required due to the increased service life and number of bridges. This paper provides information and communication technology (ICT) - based bridge management system (BMS) to enable life cycle management through a comparative study with the development trend and function of domestic and foreign BMSs. BMS developed as an operation system combined an internet and mobile program, and was based on GIS technology and an object-based information management system. BMS supports the establishment of long-term strategies and short-term plans based on predicting the life-cycle performance profile and the necessary budget by object-based informatization for the whole life-cycle information of bridges. Useful knowledge information for supporting decision making was derived from the life-cycle management strategies establishment for approximately 6,000 existing bridges. BMS was developed to be applicable to all nationwide road bridges. In addition, it can be used practically to maintain the performance based on accurate maintenance result management, reducing cost by reasonable budget management, and enhancing the convenience and reliability of field data collection.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.2
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• pp.267-275
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• 2023

As aged infrastructures have been increased, the importance of accurate maintenance costs and proper budget allocation for infrastructure become prominent under limited resources. This study proposed a mapping algorithm between representative defects, repair methods, and the estimated maintenance costs for concrete bridges. In this regard, using BMS (Bridge Management System) data analysis, bridge repair methods were classified and matched with defects according to their locations, types, and sizes. In addition, the maintenance costs were estimated based on the amount of work-load and quantity per unit using CSPR (Cost Standard Production Rate). As a result, the level of accuracy was an average of 85.1 % compared with the actual bill of quantity for Seoul bridge maintenance. The accuracy of maintenance costs is expected to be enhanced by considering the various site conditions such as pier height, extra charge conditions, additional equipment, etc.

• Journal of the Korean Society for Railway
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• v.13 no.1
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• pp.71-77
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• 2010

It is increasing annually that the cost for bridge Maintenance Repair & Rehabilitation (MR&R) in developed countries. Based on Intelligent Technology, Bridge Management System (BMS) is developed for optimization of Life Cycle Cost (LCC) and reliability to predict long-term bridge deteriorations. However, such data are very limited amongst all the known bridge agencies, making it difficult to reliably predict future structural performances. To alleviate this problem, an Artificial Neural Network (ANN) based Backward Prediction Model (BPM) for generating missing historical condition ratings has been developed. Its reliability has been verified using existing condition ratings from the Maryland Department of Transportation, USA. The function of the BPM is to establish the correlations between the known condition ratings and such non-bridge factors as climate and traffic volumes, which can then be used to obtain the bridge condition ratings of the missing years. Since the non-bridge factors used in the BPM can influence the variation of the bridge condition ratings, well-selected non-bridge factors are critical for the BPM to function effectively based on the minimized discrepancy rate between the BPM prediction result and existing data (deck; 6.68%, superstructure; 6.61%, substructure; 7.52%). This research is on the generation of usable historical data using Artificial Intelligence techniques to reliably predict future bridge deterioration. The outcomes (Long-term Bridge deterioration Prediction) will help bridge authorities to effectively plan maintenance strategies for obtaining the maximum benefit with limited funds.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.128-134
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• 2016

Estimating the repair and reinforcement (R&R) costs for each bridge member is essential for managing the life cycle of a bridge using a bridge management system (BMS). Representative members of a bridge were defined in this study, and detailed and representative R&R methods for each one were drawn in order to develop a systematic maintenance cost model that is applicable to the BMS. The unit cost for each detailed R&R method was established using the standard of estimate and historical cost data, and a systematic procedure is presented using an integration program to enable easy renewal of the R&R unit cost. Also, the average unit cost of the representative R&R methods was calculated in the form of a weighted average by considering the unit cost and application frequency of each detained R&R method. The appropriateness of the drawn average unit cost was reviewed by comparing and verifying it with the previous historical unit cost. The suggested average R&R unit cost can be used to review the validity of the required budget or the appropriateness of the R&R performance cost in the stage to establish the bridge maintenance plan. The results of this study are expected to improve the reliability of maintenance cost information and the rationality of decision making.