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This paper aims to identify the different system approach using Building Information Modelling (BIM) technology that is equipped with decision making processes. Maintenance planning and management are integral components of the construction sector, serving the broader purpose of post-construction activities and processes. However, as Precast Concrete (PC) construction projects increase in scale and complexity, the interconnections among these activities and processes become apparent, leading to planning and performance management challenges. These challenges specifically affect the monitoring of façade components for corrective and preventive maintenance actions.

The concept of maintenance planning for façades, along with the main features of information and communication technology tools and techniques using building information modeling technology, is grounded in the analysis of numerous literature reviews in PC building scenarios.

This research focuses on an integrated system designed to analyze information and support decision-making in maintenance planning for PC buildings. It is based on robust data collection regarding concrete façades' failures and causes. The system aims to provide appropriate planning decisions and minimize the risk of façade failures throughout the building's lifetime.

The study concludes that implementing a research framework to develop such a system can significantly enhance the effectiveness of maintenance planning for façade design, construction and maintenance operations.

Prefabricated building has been widely applied in the construction industry all over the world, which can significantly reduce labor consumption and improve construction efficiency compared with conventional approaches. During the construction of prefabricated buildings, the overall efficiency largely depends on the lifting sequence and path of each prefabricated component. To improve the efficiency and safety of the lifting process, this study proposes a framework for automatically optimizing the lifting path of prefabricated building components using building information modeling (BIM), improved 3D-A* and a physic-informed genetic algorithm (GA).

Firstly, the industry foundation class (IFC) schema for prefabricated buildings is established to enrich the semantic information of BIM. After extracting corresponding component attributes from BIM, the models of typical prefabricated components and their slings are simplified. Further, the slings and elements’ rotations are considered to build a safety bounding box. Secondly, an efficient 3D-A* is proposed for element path planning by integrating both safety factors and variable step size. Finally, an efficient GA is designed to obtain the optimal lifting sequence that satisfies physical constraints.

The proposed optimization framework is validated in a physics engine with a pilot project, which enables better understanding. The results show that the framework can intuitively and automatically generate the optimal lifting path for each type of prefabricated building component. Compared with traditional algorithms, the improved path planning algorithm significantly reduces the number of nodes computed by 91.48%, resulting in a notable decrease in search time by 75.68%.

In this study, a prefabricated component path planning framework based on the improved A* algorithm and GA is proposed for the first time. In addition, this study proposes a safety-bounding box that considers the effects of torsion and slinging of components during lifting. The semantic information of IFC for component lifting is enriched by taking into account lifting data such as binding positions, lifting methods, lifting angles and lifting offsets.

This paper aims to explore UAE's transition towards circular economy (CE) through construction and demolition waste (CDW) management in the pre-construction stage. The extent of circularity is assessed by five key aspects of CE, such as policies and strategic frameworks, design for waste prevention, design for disassembly or deconstruction, use of prefabricated elements and CDW management plans.

Multiple case studies were conducted in the context of the Dubai construction industry (UAE). Three significant and unique construction projects were selected as the cases. Semi-structured interviews were carried out to collect data, and the thematic analysis technique and NVIVO 12 software were used for data analysis.

Findings reveal several positive initiatives towards CE in the UAE context; yet it is identified that the transition is still at the initial stage. Selected case studies, the best-case scenarios of UAE (i.e. influential cases), demonstrated adequate measures in relation to four key CE aspects out of five. For instance, (a) policies and strategic frameworks such as lean standards, green building standards and standards developed by the local authorities, (b) design for waste prevention (e.g. adherence to the 3R principle, and construction planning with BIM), (c) use of prefabricated elements and application of innovative construction technologies (e.g. 3DPC, DfMA) and (d) CDW management planning such as 3R principle were evident. However, the selected cases hardly showcase designing for disassembly or deconstruction.

The existing CDW practices are mostly conventional, as most constructions in UAE are procured through conventional building materials and methods. Therefore, there is a necessity of encouraging CE principles in CDW management. Even though the transition towards CE was evident in four key CE aspects out of five, the UAE construction industry has yet to adopt more effective CE-based CDW management practices to accelerate the circularity. Hence, it is necessary to enforce standard waste management guidelines, including the 3R principle, to standardise CDW management in UAE and encourage construction practitioners to adhere to CE principles.

The findings of this study provide valuable insights for decision-making processes around CDW management towards a CE. This paper contributes to the literature by bridging the CE concept with CDW management in the pre-construction stage. The study provides insights for industry practitioners for planning CE in terms of policies and strategic frameworks, CDW management planning, construction planning and application of innovative construction technologies.

The purpose of this study is to explore existing literature on Building Information Modelling (BIM) in Malaysia and examine the perception of practitioners about the potential of BIM applications in reducing construction waste and enhancing productivity.

First, using 244 bibliographic data extracted from the Scopus database, the paper used scientometric analysis and VOSviewer mapping technique to assess the most impactful publication literature on BIM in Malaysia to identify the existing research gaps. Second, using a structured questionnaire, a total of 100 questionnaires were distributed to practising practitioners who incorporate BIM in the delivery of their projects. Descriptive analysis using cross-tabulation in SPSS software, radar chart, relative importance index and Pearson’s correlation were used to analyze the data.

The research gaps are in the fields of construction projects, buildings, energy efficiency, lifecycle and housing. The findings of the survey indicate that quantity take-off, clash detection, site utilization planning, digital fabrication as well as 4D stimulation were the main BIM applications used among the practitioners in Johor and Selangor.

By assessing the state-of-the-art of BIM and BIM applications in this region, the practical implications of this study provide useful insights to construction stakeholders, funding organizations, policymakers, research institutions, professionals, journal editors, reviewers and researchers to understand the overall trend of BIM in Malaysia and its usage.

This paper is the first to use science mapping using scientometrics to reveal the current BIM research in “Malaysia only”. Relying on the identified gaps, the study further examined the usage of BIM applications in Malaysian construction projects.

In academics and industry, significant efforts have been made to lead planners and control teams in evaluating project performance and control. In this context, numerous control metrics have been devised and put into practice, often with little emphasis on analyzing their underlying concepts. To cover this gap, this research aims to identify and analyze a holistic list of control metrics and their functionalities in the construction industry.

A multi-step analytical approach was conducted to achieve the study’s objectives. First, a holistic list of control metrics and their functionalities in the construction industry was identified. Second, a quantitative analysis based on social network analysis (SNA) was implemented to discover the most important functionalities.

The results revealed that the most important control metrics' functionalities (CMF) could differ depending on the type of metrics (lagging and leading) and levels of control. However, in general, the most significant functionalities include managing project progress and performance, evaluating the look-ahead level’s performance, measuring the reliability and stability of workflow, measuring the make-ready process, constraint management and measuring the quality of construction flow.

This research will assist the project team in getting a comprehensive sensemaking of planning and control systems and their functionalities to plan and control different dynamic aspects of the project.

Construction activities conducted in urban areas are often a source of significant noise disturbances, which cause psychological and health issues for residents as well as long-term auditory impairments for construction workers. The limited effectiveness of passive noise control measures due to the close proximity of the construction site to surrounding neighborhoods often results in complaints and eventually lawsuits. These can then lead to delays and cost overruns for the construction projects.

The paper proposes a novel approach to integrating construction noise as an additional dimension into scheduling construction works. To achieve this, a building information model, including the three-dimensional construction site layout object geometry, resource allocation and schedule information, is utilized. The developed method explores further project data that are typically available, such as the assigned equipment to a task, its precise location, and the estimated duration of noisy tasks. This results in a noise prediction model by using noise mapping techniques and suggesting less noisy alternative ways of construction. Finally, noise data obtained from sensors in a case study contribute real values for validating the proposed approach, which can be used later to suggest solutions for noise mitigation.

The results of this study indicate that the proposed approach can accurately predict construction noise given a few available parameters from digital project planning and sensors installed on a construction site. Proactively integrating construction noise control measures into the planning process has benefits for both residents and construction managers, as it reduces construction noise-related disturbances, prevents unexpected legal issues and ensures the health and well-being of the workforce.

While previous research has concentrated on real-time data collection using sensors, a more effective solution would also involve addressing and mitigating construction noise during the pre-construction work planning phase.

Cyber-physical systems (CPS) enable the synergistic integration of virtual models with the physical environment. This integration is gaining recognition for its potential to enhance construction project information management, thereby contributing to improved cost management in construction. Similarly, quantity surveyor (QS) plays a key role in construction projects by estimating and monitoring construction costs. Consequently, this research aims to explore redefining the role of QSs by integrating CPS.

The research adopted an interpretivism stance to collect and analyse data. Two rounds of 21 and 19 semi-structured interviews were conducted, with experts selected through heterogeneous purposive sampling. Code-based content analysis was used to analyse the data using NVivo12. MS Visio data visualisation tool was used to present the findings.

It is empirically proven the potential of CPS to facilitate nine key roles of QSs in all stages of the RIBA plan of work through the identification of 15 CPS applications and technologies. Nine key roles of QSs that CPS can facilitate were identified as preliminary estimation, measurement and quantification, contract administration, preparation of BOQ, interim valuation and payments, tender and contract documentation, cost planning, cost control and procurement advice. The study explored how adopting CPS technologies can transform traditional quantity surveying practices and enhance their value within the construction industry.

The findings add to the body of knowledge by redefining the role of QS through the integration of CPS for the first time and then by highlighting the usages of CPS in the construction industry rather than limiting it to a specific sector of the construction industry, as previous studies have done. This research uncovers several other research arenas on CPS as being the very first research to evaluate CPS to facilitate key roles of QSs. The findings can enhance the awareness and the practical implementation of CPS by intervening to form more partnerships among application developers and industry leaders.

Due to its longer length compared to other construction materials and distinctive stacking patterns, obtaining construction steel bars in congested construction sites with limited storage capacity becomes challenging. Lack of storage space in crowded places prompts the need for building steel bar storage choice optimization. Therefore, this study aims to optimize the construction steel bar procurement plan by providing when and how much rebar to order and how to stack different sizes of rebar considering limited storage capacity.

A novel approach has been presented in this paper by integrating 4D building information modelling (BIM) and mixed-integer linear programming (MILP). This technique uses BIM to retrieve material quantities, including rebar, during the design phase. Following that, activities are scheduled depending on the duration determined by crew productivity data and material quantity. Then, based on the prior price, the price of each unit of rebar is projected for the duration of construction using the exponential smoothing method. After that, the MILP approach is used to generate an optimal steel bar procurement plan for limited storage space following the scheduled rebar-related operations.

The developed strategy minimizes overall procurement costs and ensures the storage of rebar as per standard guidelines. An optimal rebar procurement and storage plan to construct a six-storied RC frame has been presented in this paper as a demonstrative example to show the effectiveness of the proposed method.

This work partially satisfies a long-sought research need for establishing a comprehensive construction steel bar procurement system, making it a very useful source of information for practitioners and researchers. The proposed method can be used to minimize a key performance limitation that the conventional rebar procurement practice for crowded building sites may experience.

The existing literature has been mainly focused on local problems but without an overall framework for studying the top-level planning of intelligent construction from a systematic perspective. The purpose of this paper is to fill this gap.

This research adopts a deductive research approach.

This research proposes a reference architecture and related business scenario framework for intelligent construction based on the existing theory and industrial practice.

The main contribution of this research is to provide a useful reference to the Chinese government and industry for formulating digital transformation strategies, as well as suggests meaningful future research directions in the construction industry.

The purpose of this study is to ascertain and list the most effective management strategies in efficiently handling the project complexities to enhance the performance of the project.

To fulfill the aim of this study, a comprehensive literature review was conducted, and the qualitative Delphi technique in two rounds was applied. Participants of the Delphi technique consisted of 12 subject matter experts (SMEs) with cumulative experience of 250 years in working in construction projects. In the first round of the Delphi technique, SMEs were asked to provide complexity management strategies to address the complexities due to 37 complexity indicators (CIs) under 11 complexity categories. In the second round of the Delphi technique, SMEs identified the top three management strategies for each of the 37 CIs.

This study collected the outcome of the two-round Delphi technique and based on the output developed the list of strategies to manage complexities related to each indicator. For example, establishing a well-informed governance team, assigning a Project Manager (PM) when the number of projects is more than one in an organization, and assigning a PM efficient enough to communicate with higher authority effectively will help in managing complexity that arises due to faulty assessment of the influence of a project on the organization’s overall success.

This study will help practitioners in effectively managing the project complexities, and thus will reduce the monetary loss associated with project complexities.