Advancements in building materials and technology have led to the rapid development of various design solutions. At the same time, life cycle assessment (LCA) and life cycle cost analysis (LCCA) of such solutions have become a great burden to engineers and project managers. To help conduct LCA and LCCA conveniently, this study (i) analyzed the information needed to conduct LCA and LCCA, (ii) evaluated a way to obtain such information in an easy and accurate manner using a building information modeling tool, and (iii) developed an Excel spreadsheet-based framework that allowed for the simultaneous implementation of LCA and LCCA. The framework developed for LCA and LCCA was applied to a real building case to evaluate three possible alternatives for an external skin system. The framework could easily and accurately determine which skin system had good properties in terms of the LCA and LCCA performance. Therefore, these results are expected to assist in decision making based on the perspectives of economic and environmental performances in the early phases of a project, where various alternatives can be created and evaluated.

The fast-track method is one of the most recognized methodologies for reducing construction project schedules. However, due to the lack of definitive research to date pertaining to the effects of fast-track application in terms of time and cost, it has been difficult for project owners to determine its correct application. This paper presents the time and cost optimized decision support (TACTICS) model, and it was developed based on the fast-track methodology and genetic algorithms (GAs). TACTICS was applied to two case studies, and the results indicated that the fast-track method could be expected to deliver more efficient projects compared with using the traditional method. In particular, (1) the average reduction in project duration by applying the fast-track method was 40.48% (Case I) and 18.59% (Case II) compared with using the traditional method, and (2) the average project costs were reduced by as much as 0.39% (Case I) and 4.48% (Case II). Consequently, TACTICS could be expected to help in...

A half-precast concrete slab system (HPCSS) is reported to exhibit excellent structural performance when compared with traditional slab systems. However, there is a lack of extant research examining the construction issues of an HPCSS. Thus, in this study, we analyze the construction process and productivity of applying an HPCSS by using a simulation method with the data collected from an actual construction case. The results indicate that (i) the construction productivity of HPCSS is 1.7 times that of a traditional slab system, (ii) the cost per productivity unit of HPCSS exceeds that of a traditional slab system, and (iii) critical resources affecting the HPCSS productivity include form crew and rebar crew. The results of this study suggest that it is possible to develop an optimal construction plan of a construction site in which an HPCSS is installed, and that the HPCSS can be actively applied in the future.

Over the past decades, automation and robotics have been widely adopted in the construction industry as a promising solution for troubleshooting issues. This field is highly interdisciplinary and rapidly changing, and new concepts and ideas are being actively introduced in association with the existing ones. To reveal new insights, the evolution of knowledge in this field needs to be characterized by identifying important knowledge elements and research trends from published data. This study investigated research trends and network characteristics in the field of construction automation and robotics by using a keyword network analysis based on published articles. We analyzed the structure of the keyword network and identified major research topics and their relationships. Notable findings of the research characteristics are as follows. 1) Popular research themes with a set of closely connected keywords continue to be selected and contribute to the evolution of the network. 2) As an interdisciplinary research area, popular keywords that actively interact with other keywords also bridge different clusters of related research concepts. This study could provide useful insights and a better understanding of the knowledge structure and research trends as well as information on future directions in the construction automation and robotics field.

The renovation of a building, instead of raising a new structure, is being scrutinized more closely at present as a sustainable alternative for reaping the benefits of improving a building’s energy performance and mitigating its physical deterioration. The extent of the benefits would be dependent on the optimal renovation time determined through the building owner’s decision-making process. Unfortunately, only a few studies have explored improvement of the decision-making process for determining an appropriate renovation time, making it difficult for building owners to conduct reliable cost-effective renovation planning. A model that estimates the optimal cost-effective renovation time of a building therefore would be a valuable tool, and the model introduced in this paper addresses this need. By applying the model to an actual renovation project as a case study, this model yielded 24 renovation alternatives for achieving a cost-effective renovation time, from which the optimal alternative was id...

Recently, the construction industry has experienced an increase in the volume of renovation work aimed at improving the physical and economic performance of buildings. However, owners often hesitate to execute renovation projects because they find it difficult to guarantee an improvement in the monetary value of buildings after their renovation. Therefore, by applying multiple regression analysis to data collected from 98 actual renovated office cases, this study develops a model to enable convenient estimation of the monetary value of renovated office buildings compared with existing methods. The application of the model to 20 validation cases shows: (1) an average error rate of 10.05%; and (2) the need for comparatively less information for implementing the model. Essentially, it will enable the owners to make decisions regarding the execution of building renovation projects based on an estimation of the monetary value of buildings after renovation, which will bolster the renovation market.