Prefabricated construction has been widely accepted as an alternative to conventional cast-in-situ construction, given its improved performance. Great efforts have also been made to develop prefabricated construction technologies in China. However, there is a lack of an appropriate pattern for evaluating its comprehensive economic merits, and reasonable mathematical models for providing a comparative analysis of conventional cast-in-situ and prefabricated building projects have yet to be developed. Therefore, the research in this paper aims to comprehensively evaluate the economic benefits of implementing prefabricated construction techniques in order to surpass the economic barrier and promote the development of prefabricated buildings in China. The comprehensive economic evaluation is formulated in terms of resource-use efficiencies, project progress, and incentive policies. An apartment building in Shanghai is selected as a case study. Construction progress is simulated on the BIM platform when the same case study is rationally transformed from the prefabricated to the conventional cast-in-situ construction technique. The results reveal that the comprehensive economic merit can reach ¥739.6/m2 when selecting the prefabricated construction process. The economic benefit brought by shortening the construction period can be regarded as the most significant contributor. Yet, the current incentive policies only contribute 7.1% of the comprehensive economic evaluation. Overall, this research contributes an assessment framework for decision-making in the technique management of building construction. The BIM-based simulation approach can greatly help investors to identify the relevant economic factors and adopt the latest incentive policies.

In order to achieve the sustainable growth of its urbanization and natural resources, China has been making great efforts to develop prefabricated construction technologies. However, the high incremental cost of prefabricated buildings (PRBs) is a fundamental obstacle to the latter. The current study mainly focuses on analyzing the incremental cost of the on-site construction stage. It is hard to comprehensively identify the incremental cost composition without considering the incremental cost caused by prefabricated components (PFCs) production. Moreover, the results of incremental cost calculation are not accurate enough by comparing the cost of two similar but different PRB and traditional buildings (TRB), and the case-based calculation results suffer from a lack of representation. To address these issues, we first establish a two-dimensional incremental cost index system from the dimension of cost items and prefabricated technologies to study the incremental cost composition of the whole construction stage. Additionally, based on China’s latest policies documents, the applicability of incremental cost composition items can also be improved. Then a building information modeling (BIM)-based calculation model is presented to avoid the calculation error caused by comparing the cost of two different PRBs and TRBs. To validate the proposed index system and calculation method, an actual prefabricated project in China is also conducted as a case study. The results suggest that: (1) Incremental cost is composed of band bearing and retaining walls and inner walls PFCs production, PFCs hoisting and grouting, post-pouring concrete, and full decoration. (2) The BIM-based incremental calculation result of a PRB case from Shanghai is within the range of the national average PRB incremental estimation results. The incremental cost composition items and BIM-based calculation approach can greatly help investors to identify the largest increase in cost and make effective cost optimization strategies.

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Robotic building inspection is gaining popularity as a way to increase the security, productivity, and cost-effectiveness of traditional inspection tasks. Despite the development of numerous building inspection robotic platforms, their motions still require manual control. To facilitate full automation, there is a need to explore autonomous navigation strategies for building inspection robots. Although various autonomous navigation strategies have been developed in the robotics field, few of them are suitable for building structural inspection behavior. In accordance with the responsibilities of professional inspectors, the robot is required to follow the structural components within a desired distance and dynamically avoid obstacles to conduct in-depth scanning. This navigation task becomes more difficult when providing smooth following path in special building scenarios, such as narrow corners. Motivated by this need, the present study aimed to explore autonomous navigation for building inspection robots. To save the cost of map construction, the local navigation strategies, which control the robots' travel in unknown environments, were targeted.Specifically, the objective is to develop a robust fuzzy logic controller (FLC) for wall-following behavior. The inputs are the distances within the designed interval ranges, which were measured with a 360-degree laser. The membership functions and the decision-making rules were designed based on robot and camera configurations, building designs, and structural inspection criteria. The outputs are the real-time angular and linear velocities. Tested in both simulation and real-world environments, the novelty of the designed FLC is: 1) enabling "finding wall," "wall-following," "turning," and "obstacle avoidance" behaviors in various unknown building scenarios; 2) preventing wavy motions; and 3) preventing path deviations for arbitrary surfaces. The results can be employed to perform daily structural inspections, and they are dedicated to automating the building inspection tasks. However, the FLC is sensitive to the reflective components because of the limitations of the position sensors.