In order to make informed decisions on routine maintenance of bridges of expressways, the hierarchical regression analysis\nmethod was used to quantify factors influencing routine maintenance cost. Two calculation models for routine maintenance cost\nbased on linear regression and time-series analysis were proposed. The results indicate that the logarithm of the historical routine\nmaintenance cost is the dependent variable and the bridge age is the independent variable. The linear regression analysis was used\nto obtain a cost prediction model for routine maintenance of a beam bridge, which was combined with the quantity and price, and\nverified by a physical engineering example. In order to cope with the cost changes and future demands brought about by the\nemergence of new maintenance technologies, the time-series analysis method was used to obtain a model to predict the engineering\nquantities for the routine maintenance of a bridge based on standardized minor repair engineering quantities. Taking\ninto account the actual cost of the minor repair project as well as the time-series analysisâ?? sample size demands, the annual\nengineering quantity was randomly decomposed into four quarterly data quantities, and the time-series analysis result was verified\nby physical engineering. These results can improve the calculation accuracy of the routine maintenance costs of reinforced\nconcrete beam bridges. Furthermore, it can have a certain application value for improving the cost measurement module of bridge\nmaintenance management systems.
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