Steel pipe pile head cutting work is performed to adjust the horizontal levels of piles, and it is essential for the stable transfer of an upper structure load to the ground. However, the field survey results show that steel pipe pile head cutting process is highly dangerous as laborers especially deal with gas and plasma cutting machines. Moreover, the laborers are exposed to continuous risks because the piles are frequently felled, lifted, moved, and loaded using construction equipment, such as excavators, immediately after the piles are cut. Recently, the authors of this study developed a prototype of a steel pipe pile head cutting robot and verified its performance through laboratory experiments to improve work safety, productivity, and the quality of steel pipe pile head cutting work. The purpose of this study is to secure the economic feasibility of robot development and verify the sustainable utilization of a developed robot by analyzing the comprehensive performance and economic efficiency throughout the life cycle of a steel pipe pile head cutting robot developed in South Korea. In this study, sensitivity analysis was also performed on the variables expected to have a significant influence or variables that must be considered for the future commercialization of the developed robot. When the developed robot is applied to construction sites in the future, its ripple effects will be significant because it will be possible to prevent labor safety accidents, improve work productivity, secure uniform quality, and reduce input costs.

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Buildings aged 20 years or older account for 63.34% of all edifices in Korea. To ensure sustainable construction, apartment managers must plan and allocate financial resources to maintain communal facilities. However, on the one hand, long-term repair allowances (LTRAs) can be underestimated relative to actual repair costs; consequently, apartments can rapidly deteriorate. On the other hand, the long-term allowance may exceed the actual repair expenditure, thus, wasting resources. Existing estimation methods do not consider the apartment management degree, equipment condition, time value, or the extent of building deterioration. Based on multiple regression, this study developed a repair budget estimation model that considers the influencing factors that include the main characteristics of apartments and the time value, thereby allowing apartment managers to estimate the appropriate long-term repair expenses. In the conducted experiments, the root mean square and mean absolute percentage errors of the estimation model were USD 144,587.38 and 25.6%, respectively. Further, ANOVA results showed a difference between the actual and estimated total long-term repair costs. The resulting model should support apartment managers in establishing reliable maintenance budgets and effectively prevent the functional degradation of buildings.

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The displacement of retaining walls is measured using inclinometers in order to evaluate the safety of the wall. However, inclinometers have three problems: they (1) are difficult to install, (2) have local displacement detection, and (3) are measured using manpower. Consequently, a two-dimensional (2D) LiDAR sensor-based retaining wall displacement measurement system that facilitates installation and three-dimensional (3D) displacement detection (more economically feasible than inclinometers) was developed in order to overcome the aforementioned limitations. The developed system collects 3D point cloud data about the retaining wall by rotating the 2D LiDAR sensor 360° at a constant speed. Laboratory experiments were performed using a simulated deformation model to evaluate the displacement measurement performance of the system, which had a root-mean-square error of 2.82 mm at approximately 20 m. The economic feasibility of the system was analyzed, which revealed that the system was economically feasible, with a benefit/cost ratio and breakeven point of 3.52 and 2.71 years, respectively.