Selecting the best materials that ensure maximum performance is crucial in the construction engineering design of any construction project. However, this is challenging and usually not properly considered because of the lack of systematic and scientific evaluation methods for the performance of materials. This paper proposes a new approach of selecting material to satisfy the performance goal of material designers in building constructions based on the analytic hierarchy process method. To validate the suggested model, a case study was conducted for a concrete system form, the performance of which is susceptible to its materials and has a strong effect on overall project productivity. The newly developed form comprising polymers and alloys showed that the proposed material selection model provided a better combination of materials, and the solution was technically more advanced and ensured better performance. This paper contributes to the body of knowledge by expanding the understanding of how construction material properties affect project performance and provides a guideline for material engineers to select the best-performing building materials while considering a performance goal.

Construction firms attempt to estimate building information modeling (BIM) return on investment (ROI) to confirm whether BIM effects are sufficiently positive to satisfy decision-makers. Previous studies have presented the ROI in various ways, but a more definitive answer is required to consider possible various effects. Therefore, this study proposes a framework for an integrated BIM ROI, a simple, easy-to-understand, and practical tool that is established from substantive requirements from experts in the construction field. The framework consists of a three-phase process including a total of 11 steps. These phases are assessment planning, primary BIM ROI based on preventing rework, and integrated BIM ROI. Based on the proposed framework, an actual effect analysis of BIM project was conducted and the suitability of the methodology was discussed. The results of applying the framework showed that the primary ROI based on prevented rework costs was about 167.8% and the integrated BIM ROI to consider the overall effect of applying BIM was about 476.72%. In addition, the expert’s discussion confirmed that the framework can be employed as a practical means to evaluate BIM performance. This framework can be provided as a guideline to present an integrated BIM effect and assist to efficiently BIM application.

Building information modeling (BIM) and modular construction are important technologies for construction industry sustainability. This study proposes a relational matrix of key activities and BIM tasks of modular construction projects to analyze practical BIM tasks in Korea. To achieve this objective, 11 key activities and eight BIM tasks are identified through a comprehensive literature review and expert interviews. Then, the relational matrix of key activities and BIM tasks is proposed, and the BIM tasks in the matrix are analyzed in terms of necessity and efficiency using 5-point Likert scales. Finally, the matrix with the BIM utilization index is suggested. As a result, the average BIM utilization index is 0.80 in the off-site phase, and the index results show that 3D shop drawings have the highest index. In the on-site phase, the average BIM UI is 0.73 and the integration of a 4D model with quantity take-off is the most efficient at 0.85. Additionally, from the decision-maker’s perspective, the priority through the index presented helps in making decisions and in practical BIM execution planning. The proposed matrix is a practical reference for decision-makers considering the application of BIM in modular projects, and it contributes to a sustainable construction industry.

In the information age, the role of data in any industry is getting more and more important. In the construction industry, however, experts’ experience and intuition are still key determinants in decision-making, while other industries achieve tangible improvement in paradigm shifts by adopting cutting-edge information technology. Cost and schedule controls, which are closely connected, are decisive in the success of construction project execution. While a vast body of research has developed methodologies for cost-schedule integration over 50 years, there is no method used in practice; it remains a significant challenge in the construction industry. This study aims to propose a data processing algorithm for integrated cost-schedule data management employing big data technology. It is designed to resolve the main obstacle to the practicality of existing methods by providing integrity and flexibility in integrating cost-schedule data and reducing time on building and changing databases. The proposed algorithm is expected to transform field engineers’ current perception regarding information management as one of the troublesome tasks in a data-friendly way.

Ondol is a heating system unique to Korean homes that increases indoor temperatures by supplying hot water through pipes embedded in floor slabs. Known for its comfort and sustained heating advantages, ondol has garnered international interest in countries requiring efficient heating solutions. Given the inherent challenges faced during installation and operation, timely inspection of ondol is crucial due to difficulties in detecting and locating defects in buried concrete pipes, often leading to costly rework and removal. However, specialized inspection systems tailored to ondol pipes remain underexplored. Therefore, this paper proposes a robotic inspection system capable of assessing the conditions of ondol pipelines. We analyze the characteristics of ondol piping to establish system requirements and develop a prototype of a compact capsule-shaped inspection robot tailored for ondol pipe inspection. Subsequent laboratory testing validates system performance and usability, confirming field applications through curvature maneuverability and image reception quality tests. This study aims to motivate advancements in ondol-specific system implementation and performance validation, potentially contributing to the smartification of ondol maintenance practices.