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A Big Data Approach for Decision Making in Bridge Maintenance

Yu-Han Chuang and Nie-Jia Yau
Graduate Institute of Construction Engineering and Management, National Central University, Taoyuan, Taiwan

Abstract—The Taiwan Bridge Management System (TBMS) has been online since 2000 and the total amount of inventory is 33,275, including all kinds of bridges and culverts. Currently, the number of fields in all tables in the databases of TBMS is around 6,500 with more than 3.4 million data records in its databases. There are more than 11,200 bridges that are over 20 years old with another 9,300 bridge having unknown built years in the TBMS. The bridges in Taiwan have stepped into the stage where maintenance is crucial and frequently required. Therefore, this research aims at analyzing the database in the TBMS using Exploratory Factor Analysis for determining maintenance strategies for these bridges. This paper describes results of the first year’s research efforts. Relevant literature in bridge maintenance, prioritization, and life-cycle bridge management were firstly reviewed. Concepts, theories, and available software for analyzing “Big Data” were also introduced.
Index Terms—bridge maintenance, bridge management, big data, decision making

Cite: Yu-Han Chuang and Nie-Jia Yau, "A Big Data Approach for Decision Making in Bridge Maintenance," International Journal of Structural and Civil Engineering Research, Vol. 5, No. 3, pp. 216-222, August 2016. doi: 10.18178/ijscer.5.3.216-222