Quality control is essential to a successful modular construction project and should be enhanced throughout the project from design to construction and installation. The current methods for analyzing the assembly quality of a removable floodwall heavily rely on manual inspection and contact-type measurements, which are time-consuming and costly. This study presents a systematic and practical approach to improve quality control of the prefabricated modular construction projects by integrating building information modeling (BIM) with three-dimensional (3D) laser scanning technology. The study starts with a thorough literature review of current quality control methods in modular construction. Firstly, the critical quality control procedure for the modular construction structure and components should be identified. Secondly, the dimensions of the structure and components in a BIM model is considered as quality tolerance control benchmarking. Thirdly, the point cloud data is captured with 3D laser scanning, which is used to create the as-built model for the constructed structure. Fourthly, data analysis and field validation are carried out by matching the point cloud data with the as-built model and the BIM model. Finally, the study employs the data of a removable floodwall project to validate the level of technical feasibility and accuracy of the presented methods. This method improved the efficiency and accuracy of modular construction quality control. It established a preliminary foundation for using BIM and laser scanning to conduct quality control in removable floodwall installation. The results indicated that the proposed integration of BIM and 3D laser scanning has great potential to improve the quality control of a modular construction project.

An Analytical Network Process (ANP) was created to test the Lean and BIM concepts with data collected from U.S. companies to find the success factors of the Lean/BIM framework. After an extensive literature review, a total of 17 sub-categories for Lean/BIM are classified into three clusters, namely Communication, Production, and Visualization. An ANP network is then established to station the links between the attributes of the framework while computing their importance weights. Eight experienced civil engineers took part in the questionnaire study to assess the relations between the attributes. The main purpose of this study is to reveal the synergy between Lean and BIM with different components reflecting this synergy and present the Lean and BIM synergy on a comprehensive model. The results indicate that Production is the prominent cluster and Production Control, Standardization and Information accuracy are the most important factors in the Lean/BIM synergy. To validate the model, five construction projects were selected to test and observe the results accordingly. The study is expected to help construction industry leaders set their priorities, benefit more from the interaction between Lean and BIM, and revise their strategies accordingly. This study identifies Lean/BIM categories and subcategories as a roadmap for research and implementation. In this context, the study reveals the relationship between the categories/subcategories along with the weights and most and less important categories for Lean/BIM implementation and research.

Construction is a hazardous industry. The project-based nature and fragmentation in the industry lead to change and uncertainty requiring special expertise. To handle those, construction firms must develop strategies and action plans along with the experience gained from lessons learned. Among the risks, safety risks are of critical importance leading to accidents. Hence, firms need to strengthen their safety programs, review their strategies for safety management, and develop effective safety training sessions to protect their workers. This study focuses on the success factors promoting safety performance. In this respect, a questionnaire was designed and administered to the Engineering News-Record (ENR) 2020 Top 400 Contractors. The questionnaire data was utilized in conducting a factor analysis to group and name the factors considering the total variance. The analysis of the factors resulted in six-factor groups; namely, project and firm-related factors, demographic factors, practical factors, motivational factors, organizational factors, and human-related factors. Project and firm-related factors were found to be the most essential factor group in terms of promoting the effectiveness of safety training. The results of this study are expected to guide industry practitioners in terms of reviewing and revising their safety training programs.

Lean implementation aims to maximize customer satisfaction while minimizing waste. However, the Lean philosophy has not yet been well understood in the construction industry due to complex and dynamic nature of construction projects. Even though Lean efforts in construction have recently gained popularity, there are still problems with the implementation processes. Therefore, it is essential to identify critical success factors (CSFs) in Lean implementation for conducting projects more effectively. Due to lack of studies in revealing CSFs in Lean implementation and the need for an up-to-date Lean implementation roadmap, this article provides an extensive set of CSFs for construction practitioners to benefit in their projects. Within this context, 27 variables were identified through an in-depth literature review. Moreover, a survey is designed and given to Lean practitioners to rank the variables based on their importance. The findings of the survey indicate that management commitment is ranked as the most important driver of Lean implementation, whereas the supportive nature of governmental regulations in Lean is ranked as the least important. A factor analysis of CSFs result in six factor groups, namely motivational factors, project factors, strategic and policy factors, company factors, technical factors, and workforce and resource factors.

The construction industry is a risky endeavour. Therefore, it is essential to develop significant safety measures for lowering risks and ensuring safety during projects. However, current safety applications are yet to be developed given the increasing number of workplace accidents. Among these, Lean applications have the potential to improve safety standards and enhance safety performance. Within this context, this study develops components for Lean implementation and construction safety performance, and it presents a conceptual framework to study the relationship between them. A questionnaire was designed and given to Lean practitioners to quantify the impact of the components. Structural Equation Modelling was used to analyse the framework and validate the relationship between Lean implementation and safety performance. The results of the study indicate that there is a significant relationship between Lean implementation and safety performance. The findings also imply that firms that perform well in implementing Lean practices achieve better safety performance. The primary contribution of this research is to prove that Lean practices are closely related to safety performance, with the aim of encouraging construction practitioners to work in a safer environment by using well-established Lean practices. Moreover, the study aims to expand the use of Lean practices to achieve better safety performance by revealing the strong ties between safety and Lean. Finally, this study can guide construction practitioners to adopt Lean techniques and apply them in their projects to enhance safety performance.

The philosophy of Lean aims to maximize customer satisfaction while minimizing waste. However, complex, dynamic, and project-based nature of construction projects bring up uncertainties in achieving benefits of Lean implementations (i.e., improvements in the schedule, budget, safety, and quality). The major objective of this study is to propose a comprehensive success model for Lean implementation in the construction industry. Within this context, a set of success criteria are identified based on extensive literature research, and the criteria set are classified into seven categories namely the financial, managerial, technical, workforce, culture, government, and communication. Then, an analytical network process (ANP) model is developed in order to reveal the links between the attributes of success while computing the importance weights of these attributes by the expert team of five. Data used for the ANP model are collected from eight experienced civil engineers through a questionnaire administered in two parts. Delphi method was adopted in the questionnaire administration, where several rounds of questionnaires were sent to the group of experts. Lean training, availability of Lean tools and techniques and market share were found as the most important success factors of Lean implementation. The performance of the proposed model is tested on six different construction projects and the results were evaluated to validate the ANP model. The study is expected to lead Lean practitioners and Engineering Managers with overcoming challenges in Lean implementation process and guide them about success parameters to consider and prioritize tasks when implementing Lean in their organizations.