Building Construction Management Research Articles

THE EFFECT OF BUILDING INFORMATION MODELLING (BIM) METHOD IMPLEMENTATION ON THE EFFECTIVENES OF BUILDING CONSTRUCTION IMPLEMENTATION MANAGEMMENT IN THE CONSTRUCTION INDUSTRY

The aim of this study is to analyze the impact of Building Implementation Information Modeling (BIM) on the efficiency of building construction management quantitatively. It has become a significant method in the construction industry with the potential to improve collaboration, coordination and information management in the implementation of construction projects. The research method uses simple linear regression analysis with data from construction professional respondents. The study involved 52 contractor companies in the construction industry. The selection of these samples is aimed at obtaining representative and adequate data for simple linear regression analysis. With large sample sizes, the results are expected to be more accurate and reliable. In addition, the selection of 52 respondents is also carried out to cover a variety of perspectives and professional experience of construction, making the data obtained more representative, and more reliable for the analysis performed. Implementation of BIM has a significant and positive impact on building construction management, demonstrated by a count t value = 12.217 greater than the table t value of 2.00856. The determination coefficient (R-square) of 0.749 or 74.9% suggests that 74.9 percent variation in building management efficiency can be explained by the implementation of BIM. This finding emphasizes the importance of using BIM to improve management effectiveness in building construction in the construction industry. The implications of this research provide a basis for encouraging the adoption of BIM as an effective tool in the management of construction projects.

A BIM-integrated multi objective optimization model for sustainable building construction management

Purpose The construction industry is tasked with creating sustainable, efficient and cost-effective buildings. This study aims to develop a building information modeling (BIM)-based multiobjective optimization (MOO) model integrating the nondominated sorting genetic algorithm III (NSGA-III) to enhance sustainability. The goal is to reduce embodied energy and cost in the design process. Design/methodology/approach Through a case study research method, this study uses BIM, NSGA-III and real-world data in five phases: literature review, identification of factors, BIM model development, MOO model creation and validation in the architecture, engineering and construction sectors. Findings The innovative BIM-based MOO model optimizes embodied energy and cost to achieve sustainable construction. A commercial building case study validation showed a reduction of 30% in embodied energy and 21% in cost. This study validates the model’s effectiveness in integrating sustainability goals, enhancing decision-making, collaboration, efficiency and providing superior assessment. Practical implications This model delivers a unified approach to sustainable design, cutting carbon footprint and strengthening the industry’s ability to attain sustainable solutions. It holds potential for broader application and future integration of social and economic factors. Originality/value The research presents a novel BIM-based MOO model, uniquely focusing on sustainable construction with embodied energy and cost considerations. This holistic and innovative framework extends existing methodologies applicable to various buildings and paves the way for additional research in this area.

Green construction practices and economic performance: The mediating role of social performance and environmental performance.

Currently, there is a surge in the adoption of green construction practices (GCP) to address and attempt to alleviate the adverse effects of construction activities on the natural environment. The current research surrounding sustainability in the industry has witnessed a notable surge in efforts, primarily driven by a growing consciousness of environmental concerns. In this context, it is worth noting that the focus of assessment schemes in developed countries has predominantly gravitated towardeconomic and environmental factors, with relatively less emphasis placed on social performance (SP). Many researchers have underscored this disparity, highlighting the need for a more comprehensive approach encompassing all three sustainability dimensions. Hence, the present research examines the effects of green construction practices on economic performance (ECP) while considering the mediating role of environmental performance (EP) and SP. The results showed no direct impact of GCP on ECP. However, the mediating role of SPand EPin the association between GCP and ECP was found to be statistically significant. The present study provides several implications. This study presents empirical evidence that implementing GCP yields several benefits for contractors, including cost reduction in waste management, legal expenses, and energy consumption. These cost savings effectively offset the initial investment required to implement GCP, enabling construction projects to attain ECP thresholds. This study provides a significant contribution to the expanding corpus of knowledge concerning green building site practices and construction management. It offers novel insights into the influence of a project's EPand SP on its economic feasibility. Furthermore, this research study has effectively showcased the positive impact of GCPon construction projects'environmental construction performance, particularly concerning environmental and social considerations. Integr Environ Assess Manag 2024;20:1396-1406. © 2024 SETAC.

Factors Affecting the Physical and Functional Performance of Buildings in Kenya

Building performance is a broad subject whose meaning covers the ability of structures to serve the intended function based on a well-defined criterion such as the assessment of functional, physical, environmental, or even social attributes considered jointly or separately. Building failures and general collapses are some of the most severe consequences of failed performance of buildings which have a great impact on livelihoods yet have remained persistent in Kenya over decades despite various interventions. This paper analyses building performance based on observable attributes and sentiments of respondents collected from construction project sites across Kenya. The study aimed to characterize buildings that are likely to fail physically and functionally at different stages based on five factors drawn from the literature as institutional, ethical, financial, legal, and technical factors, with the intention of proposing the necessary stop-gap measures. The study employed a cross-sectional (survey) design in which quantitative research methods were applied to collect and analyze data from a random sample of 400 building construction projects selected through proportionate cluster sampling across the 47 counties of Kenya. A semi-structured questionnaire was used to gather data on the perception of industry professionals, building users, and generally the stakeholders on the identified area of the research. Data was analyzed using descriptive statistics, factor analysis, and regression analysis. The physical performance of buildings appeared to cause an alarming concern with elements such as wall and slab stability recording poor scores. Based on functional performance the aspects of disability mainstreaming and compliance to green building standards were noted to be under-performing. Multiple Regression analysis results revealed that institutional, ethical, financial, legal, and technical factors explained 17.1% of the variability in building performance. Notably, only ethical, legal, and technical factors were the statistically significant predictors of building performance. The study thus recommends a detailed review, restructuring, and optimization of the ethical, legal, and technical environment of building construction management to enhance buildings performance.

Application research of intelligent system based on BIM and sensors monitoring technology in construction management

Architectural engineering is a dynamic process, and it is difficult to achieve ideal results with fixed standard management. This article proposes research on intelligent building construction management methods based on BIM and information soft sensor monitoring technology, attempting to construct a construction building model and an information database that includes basic data and expanded data. Establish a BIM model, split it into various modules, and graft the real-time dynamic database detected by environmental monitoring sensors with the BIM model to simulate the entire construction process, conduct dynamic monitoring, and adjust emergency plans in real-time through intelligent internet to ensure the rationality of the entire construction stage of multiple blocks. Based on the expected construction process requirements, resources are scheduled and managed. Compared with traditional management models, information sensors and monitoring intelligent management systems are more efficient, effectively improving resource utilization, achieving low-carbon construction, and significantly accelerating project progress.

Retracted: Research on Nonlinear Time Series Processing Method for Automatic Building Construction Management

Retracted: Research on Nonlinear Time Series Processing Method for Automatic Building Construction Management

Applications of BIM in Information Technology: A Review

Abstract: To promote intelligent development in the construction sector and enhance construction management efficiency, the concept of smart development has been integrated into the planning of smart cities. A crucial aspect of smart city projects is developing a 3D digital city model. The integration of GIS and BIM technology is vital for achieving this, supporting the creation and analysis of dynamic smart cities. Using AR technology, we can recreate real-world scenes in virtual reality to provide customers with a more "immersive" experience. This article explores the diverse applications of GIS-BIM integration technology, focusing on construction schedule management, site material handling, and worker safety. Additionally, it delves into the application trends of GIS-BIM integration technology, global wide area network, Internet of Things (IoT), virtual reality, and other emerging technologies in integrated building construction management, promoting intelligent and visually enhanced management through GIS-BIM technology. This paper addresses safety management considering the entire project life cycle, setting a benchmark to elevate safety standards comprehensively in construction projects

Atmospheric-moisture-induced polyacrylate hydrogels for hybrid passive cooling

Heat stress is being exacerbated by global warming, jeopardizing human and social sustainability. As a result, reliable and energy-efficient cooling methods are highly sought-after. Here, we report a polyacrylate film fabricated by self-moisture-absorbing hygroscopic hydrogel for efficient hybrid passive cooling. Using one of the lowest-cost industrial materials (e.g., sodium polyacrylate), we demonstrate radiative cooling by reducing solar heating with high solar reflectance (0.93) while maximizing thermal emission with high mid-infrared emittance (0.99). Importantly, the manufacturing process utilizes only atmospheric moisture and requires no additional chemicals or energy consumption, making it a completely green process. Under sunlight illumination of 800 W m−2, the surface temperature of the film was reduced by 5 °C under a partly cloudy sky observed at Buffalo, NY. Combined with its hygroscopic feature, this film can simultaneously introduce evaporative cooling that is independent of access to the clear sky. The hybrid passive cooling approach is projected to decrease global carbon emissions by 118.4 billion kg/year compared to current air-conditioning facilities powered by electricity. Given its low-cost raw materials and excellent molding feature, the film can be manufactured through simple and cost-effective roll-to-roll processes, making it suitable for future building construction and personal thermal management needs.

Retracted: Artificial Intelligence Technology Based on Deep Learning in Building Construction Management System Modeling

Retracted: Artificial Intelligence Technology Based on Deep Learning in Building Construction Management System Modeling

Research Methods of Carbon Emissions

As a pillar industry, the construction industry generates 28% of the total carbon emissions of the whole society throughout its life cycle. Through the carbon emission ratio of the whole life cycle of existing buildings, it is found that the carbon emission per unit time in the construction phase is the highest among all phases, and the various environmental pollution caused by it is also the most concentrated. In order to achieve low carbon construction and reduce environmental pollution, relevant parts of the country have promulgated building construction management documents since 2007. The documents put forward clear requirements for green and low-carbon urban and rural construction to ensure green and low-carbon construction activities. It can be seen that in the context of the "two carbon" strategy, carbon emission monitoring and carbon emission reduction of construction have attracted wide attention from all walks of life. In this paper, through the analysis of carbon emission monitoring methods of construction projects, a carbon emission calculation model based on carbon sources and sinks of the construction process is established to realize the quantitative calculation of carbon emission in the construction phase of construction projects. It also establishes a carbon emission monitoring method for the construction phase of the construction project, which provides practical guidance for the carbon emission data monitoring of each construction project and guides the real-time monitoring of carbon emission during the construction phase of the construction project.

Analysis on construction practice of intelligent prefabricated building based on BIM technology

In the rapid development of Chinese construction industry, intelligent assembly building construction based on low cost, high efficiency and other advantages, in the practice of inquiry has been widely paid attention to. Although scholars around the world have strengthened the research on the theory of intelligent prefabricated building construction technology, with the vigorous development of the construction industry, a large number of safety problems have emerged in existing construction projects. Therefore, some scholars have proposed to scientifically solve the problems faced by intelligent prefabricated building construction management with the help of information integrated BIM technology, so as to build a highly efficient and normative safety management system. On the basis of understanding the construction management of intelligent prefabricated building and the research status of BIM technology, this paper deeply discusses how to apply BIM technology in intelligent prefabricated building construction and give full play to the unique advantages of BIM technology according to the main characteristics and construction requirements of intelligent prefabricated building construction in the new era.

Discussion on Optimization Measures of Building Construction Management Technology

Building construction needs have expanded in line with people's demands and the quality of life in today’s society. Therefore, the traditional construction management technology can no longer meet the current management and construction requirements, so it is necessary to further optimize the construction management technology. Therefore, this paper focuses on exploring measures regarding building construction technology optimization. Firstly, the paper briefly expounds its optimization value, then systematically analyzes some problems faced by the current housing construction management, and finally puts forward some targeted management optimization measures for future reference.

Research on Nonlinear Time Series Processing Method for Automatic Building Construction Management

Aiming at the nonlinear time series of automatic building construction management, a neural network prediction model is proposed to analyze and process the nonlinear sequence of deformation monitoring number cutter. The specific content of this method is as follows: for the noise problems existing in deformation monitoring data, a wavelet is used to denoise the preprocessing; for the BP network and RBF network commonly used in neural networks, the performance of the two networks is compared and demonstrated by MATLAB program, which proves that RBF neural network can significantly improve the accuracy of deformation prediction. By comparing the results, the maximum relative error of BP network prediction is 18.59%, while the maximum relative error of RBF network prediction is 29.16%, and the average relative error of 13P network prediction is 7.02%, while the average relative error of RBF network prediction value is 10.5%. The comprehensive error of network prediction is 6.1%, RBF network prediction is 8.52%, the standard deviation RMSE of BP network prediction error is 15.347, and that of RBF network prediction error is 21.401, and it shows that the prediction accuracy of BP network is higher than that of RBF network.

Artificial Intelligence Technology Based on Deep Learning in Building Construction Management System Modeling

In order to explore the application of AI technology in construction management system modeling, the author proposed the application of a deep learning-based AI technology in construction management system modeling. The 3 D reconstruction deep learning model is first introduced, and then the model idea of the construction progress reliability control system is designed based on BIM (building information model). Second, the construction process of the 4dbim model is described, and the construction method is introduced. The construction of the model provides data information for the construction schedule reliability control system. Finally, the three functional modules of progress monitoring, progress reliability early warning, and progress prediction are realized by combining the S-curve comparison method, and the work of the system is described through case simulation. The early warning result is from June 7 to June 11, the progress deviation is between (−2%, 2%), and the progress is basically controlled. On June 13, the planned workload was 81.099%, and the actual cumulative workload was 7.099%, which was 4% less than the planned workload. The project progress was out of date, so it needs to be closely tracked. On June 15, the planned workload was 85.511%, and the actual cumulative workload was 80.899%, 4.5% less than the planned workload. The forecast result is the line forecast of the actual cumulative completion percentage on June 17. After calculation, the forecast result on June 17 is 84.311%. The progress deviation on June 17 was 5.21%. If no timely delay is taken on June 15, the delay will get worse. In addition, the system can predict the completion period of the project. When the actual percentage of cumulative completion is greater than or equal to 100%, it indicates that the project has been completed. Therefore, we can calculate the completion period of the three-storey project, and the construction period is about June 29 or 30. When the simulation can be carried out, the simulation number is set as 1000 times, the completion probability of the project is only 40%, and the completion probability is not too high. Artificial intelligence technology can realize progress monitoring, progress reliability early warning, and progress prediction. This system model prepares for software development and is conducive to improving the progress reliability control level of construction enterprises. Starting from the schedule planning subsystem and the schedule control subsystem, this paper studies the application of the artificial intelligence technology based on deep learning in the modeling of a building construction management system. The results show that this technology can effectively improve the efficiency of the building construction schedule management. Compared with the existing management methods, it shows great advantages in terms of operating costs and ease of use. It also promotes the application of artificial intelligence technology in the construction phase.

Innovation Analysis of the Building Construction Management Based on Green Construction Management Concept

Innovation Analysis of the Building Construction Management Based on Green Construction Management Concept

Research on BIM Application in Assembly Building Design and Construction Management

Research on BIM Application in Assembly Building Design and Construction Management

Brazilian BIM Objects Technical Standard: a first approach on Acoustics parameters

The Building Information Modeling (BIM) has increased worldwide as a new approach on the building design, construction, and facilities management. Given this panorama, the Brazilian Government enforced a regulation in 2019, Decreto 9983, which outlines a roadmap for the BIM implementation in the Brazilian construction ecosystem. As one of its guidelines is to publish the necessary technical standards, a special committee, ABNT CEE 134, was hosted at the Brazilian organization for Technical Standardization with a dedicated WG for establishing BIM objects parameters. In the framework of the WG, a subgroup on Acoustics analysis aimed to deal on how to incorporate acoustic requirements to the BIM Object. In this paper, the authors describe the development of this feature, unprecedented so far. The approach adopted for incorporating acoustic requirements into BIM objects at the Brazilian BIM Standard aimed to facilitate the workflow of acoustic consulting, while adapting it to the limitations imposed by the existing software and the construction market culture in Brazil. This paper also provides some guidelines on how this issue could be addressed in future standards revisions.

Application of BIM Technology in Prefabricated Green Building Construction Management

Increasing the research on BIM Technology of prefabricated energy-saving green building construction can promote the process of prefabricated green construction in the construction industry. Firstly, this paper analyzes the characteristics of prefabricated housing and BIM green construction. Secondly, BIM Technology is applied to the design and processing of prefabricated components in prefabricated residential design. In this paper, a family library of prefabricated components is established, which can improve the design accuracy of prefabricated components and assist to realize lean production. BIM Technology improves the design efficiency from four aspects: preliminary planning, scheme design, scheme deepening and collaborative design. Combined with the relevant characteristics of BIM Technology, this paper discusses the role of BIM Technology in the first two aspects of prefabricated residential green construction. The test results show that the application of BIM Technology in the design and construction of prefabricated housing can not only improve the design efficiency, but also greatly improve the green construction of buildings.

Intelligent Building Construction Management Based on BIM Digital Twin.

In order to improve the construction effect of intelligent buildings, this paper combines the BIM digital twin technology to construct the overall structure of the building construction operation and maintenance system driven by the BIM digital twin. Moreover, this paper conducts intelligent simulation of the construction process of the building and combines the construction process of the intelligent building to apply the BIM digital twin technology to the construction management of the intelligent building. In addition, this paper uses BIM to simulate the construction process. After the construction management plan is developed, BIM can be used to simulate the construction, find the problems in the construction, and formulate a reliable construction management plan in time. Through simulation experiment research, it can be known that the intelligent building construction management model based on BIM digital twin proposed in this paper can help the deployment of intelligent building construction process in many aspects and help improve the efficiency of building construction management.

Barriers of value management implementation for building projects in Egyptian construction industry

This research aims to address barriers and obstacles to the adoption of value management (VM) in the Egyptian building projects. Furthermore, the primary contribution of this research paper is to establish the current level of the VM implementation in the Egyptian construction industry which is the first research that appears this level. The research was limited to the regions of Cairo and Giza, and clients, consultants, and contractors with sufficient experience in building construction management are the key participants. With a view to find answers from those who work actively as part of the construction industry, a quantitative questionnaire survey was used. The analysis of the collected data was based on descriptive statistical tools. Research shows that the critical barriers in the construction industry are inadequate facilitation of skills and training, and difficulty in the involvement of decision-makers and other key partners in the VM workshop. The results constitute barriers to VM implementation in the country and its guidelines will significantly promote VM adoption, both in the country and in other developing nations, where the same projects are carried out. On the other hand, this study concluded that implementation and usage of the VM technology concept within the organization has a significant impact on professionals and management skills.