Construction Quality Management Research Articles

Strategic Approaches to Design Teams for Construction Quality Management and Green Building Performance

Buildings exert a profound influence on the environment, with the design phase recognized as the pivotal determinant of a building’s overall performance. Green building design, in particular, introduces heightened complexity, where the attributes of the design team play a pivotal role in shaping performance outcomes. Consequently, the characteristics of the design team emerge as crucial factors in the enhancement of both green building design performance and client attributes. This study aims to empirically examine a model formulated to gauge the extent to which Effective Design Team Attributes contribute to the enhancement of performance in designing green buildings and influencing client attributes. To achieve this objective, a comprehensive questionnaire survey was administered to professionals within the architecture and engineering domains actively engaged in the design and consulting sectors of the building industry. The collected data underwent meticulous scrutiny for authenticity and dependability using the WINSTEPS 5.2.5 software before undergoing subsequent analysis. Statistical analyses were conducted using SPSS version 19, with Principal Components Analysis (PCA) and the Structural Equation Modeling (SEM) approach implemented through Amos version 18 to derive the most robust model. The findings underscore the pivotal role of an adeptly managed design team in significantly improving both the performance of green building designs and the qualities of clients. Rasch’s analysis confirmed the validity of our 5-point Likert scale for Design Green Building Performance (DGBP), Effective Design Team Attributes (EDTA), and Client Qualities (CQ). All items demonstrated excellent reliability, separation, and discrimination, ensuring robust data quality. Dimensionality tests revealed the appropriateness of response categories, indicating satisfactory scale performance. The Effective Design Team Model, validated through Principal Components Analysis (PCA), exhibited a satisfactory fit, supported by significant chi-square statistics, high goodness-of-fit indices, and acceptable root mean square residual values. Client attributes displayed a strong association with effective design team management, validating key model elements. The intricacies inherent in the design process can be mitigated by adopting the green design charrette approach. Consequently, the establishment of an effective design team, coupled with green design leadership, active participation, and clarity in roles and responsibilities, emerges as a potent strategy for elevating the performance level of green building designs.

Research on Quality Management Measures of Green Building Construction

Urbanization has led to the rapid development of the construction industry. However, this has also led to higher requirements for the construction engineering management. Other than the quality monitoring of engineering construction, the energy-saving properties of the building should also be considered. Therefore, a scientific management approach should be adopted to improve green building management. This paper primarily examines the importance of quality management in green building construction, along with the factors influencing it. It also identifies the quality issues present in current green building construction. Finally, it proposes measures for quality management in the green building construction process to facilitate the industry’s healthy development.

Blockchain Impact on Construction Quality Management and Its Adoption Analysis: A Game Theory–Based Method

Blockchain Impact on Construction Quality Management and Its Adoption Analysis: A Game Theory–Based Method

Method for estimating management points for dimensional quality management in shipbuilding and offshore plant construction using terrestrial laser scanning and a computer-aided design model

This study proposes a method for estimating management points for dimensional quality management in shipbuilding and offshore plant construction using terrestrial laser scanning. The dimensional quality is managed by calculating errors between quality management points in a 3-dimensional (3D) computer-aided design (CAD) model and their corresponding measurement points in a fabricated block. The proposed method utilizes a point cloud of the fabricated block together with a 3D CAD model of the block to estimate the measurement points. To achieve this, global registration, extraction of the region of interest, point segmentation in the region of interest, plane estimation of the segmented points, and estimation of measurement points are performed in an automated manner. To verify the proposed method, it is implemented and experimented with actual ship blocks. The experimental results reveal that the estimated measurement points are within the allowable tolerance of 7 mm.

Professional perceptions of right-first-time and quality management in construction projects through open-ended feedback

PurposeThe construction industry has struggled to deliver schemes on time to budget and right-first-time (RFT). There have been many studies into nonconformance and rework through quantitative research over the years to understand why the industry continues to see similar issues of failure. Some scholars have reported rework figures as high as 12.6% of total contract value, highlighting major concerns of the sustainability of construction projects. Separately, however, there have been few studies that explore and detail the views of industry professions who are caught in the middle of quality issues, to understand their perceptions of where the industry is failing. As such, this paper interrogates qualitative data (open-ended questions) on the topic of nonconformance and rework in construction to understand what industry professionals believe are the causes and suggested improvement areas.Design/methodology/approachA qualitative approach is adopted for this research. An industry survey consisting of seven open-ended questions is presented to two professional working groups within a Tier 1 contractor, and outputs are analysed using statistic software (NVivo 12) to identify prominent themes for discussion. Inductive analysis is undertaken to gain further insight into responses to yield recurrent areas for continuous improvement.FindingsQualitative analysis of the survey reveals a persistent prioritisation of cost and programme over quality management in construction project. Furthermore, feedback from construction professionals present a number of improvement areas that must be addressed to improve quality. These include increased training and competency investment, overhauling quality behaviours, providing greater quality leadership direction and reshaping the way clients govern schemes.Research limitations/implicationsThere are limitations to this paper that require noting. Firstly, the survey was conducted within one principal contractor with varying levels of knowledge across multiple sectors. Secondly, the case study was from one major highways scheme; therefore, the generalisability of the findings is limited. It is suggested that a similar exercise is undertaken in other sectors to uncover similar improvement avenues.Practical implicationsThe implications of this study calls for quality to be re-evaluated at project, company, sector and government levels to overhaul how quality is delivered. Furthermore, the paper identifies critical learning outcomes for the construction sector to take forward, including the need to reassess projects to ensure they are appropriately equip with competent personnel under a vetted, progressive training programme, share collaborative behaviours that value quality delivery on an equal standing to safety, programme and cost and tackle the inappropriate resource dilemmas projects finding themselves in through clear tendering and accurate planning. In addition, before making erratic decisions, projects must assess the risk profiling of proceed without approved design details and include the client in the decision-making process. Moreover, the findings call for a greater collaborative environment between the construction team and quality management department, rather than being seen as obstructive (i.e. compliance based policing). All of these must be driven by leadership to overhaul the way quality is managed on schemes. The findings demonstrate the importance and impact from open-ended survey response data studies to enhance quantitative outcomes and help provide strengthened proposals of improvement.Originality/valueThis paper addresses the highly sensitive area of quality failure outcomes and interrogates them via an industry survey within a major UK contractor for feedback. Unique insights are gained into how industry professionals perceive quality in construction. From previous research, this has been largely missing and offers a valuable addition in understanding the “quality status quo” from those delivering schemes.

A Simple Analysis of the Quality, Cost, and Safety Management of Basic Construction in Universities

With the continuous development of higher education, both national and local governments have increased their investment in the construction of higher education infrastructure. There are various types of buildings that universities need to build, and most of the infrastructure construction in universities is sustainable. This leads universities to not only focus on the engineering construction itself, but also pay attention to the relationship between the engineering and the normal operation of existing campuses in infrastructure construction and management. This article analyzes the current focus of infrastructure management in universities from three aspects: quality, cost, safety, and civilization.

Civil Engineering Construction Quality and Safety Management

Civil Engineering Construction Quality and Safety Management

Simulating Microscale Urban Airflow and Pollutant Distributions Based on Computational Fluid Dynamics Model: A Review.

Urban surfaces exert profound influences on local wind patterns, turbulence dynamics, and the dispersion of air pollutants, underscoring the critical need for a thorough understanding of these processes in the realms of urban planning, design, construction, and air quality management. The advent of advanced computational capabilities has propelled the computational fluid dynamics model (CFD) into becoming a mature and widely adopted tool to investigate microscale meteorological phenomena in urban settings. This review provides a comprehensive overview of the current state of CFD-based microscale meteorological simulations, offering insights into their applications, influential factors, and challenges. Significant variables such as the aspect ratio of street canyons, building geometries, ambient wind directions, atmospheric boundary layer stabilities, and street tree configurations play crucial roles in influencing microscale physical processes and the dispersion of air pollutants. The integration of CFD with mesoscale meteorological models and cutting-edge machine learning techniques empowers high-resolution, precise simulations of urban meteorology, establishing a robust scientific basis for sustainable urban development, the mitigation of air pollution, and emergency response planning for hazardous substances. Nonetheless, the broader application of CFD in this domain introduces challenges in grid optimization, enhancing integration with mesoscale models, addressing data limitations, and simulating diverse weather conditions.

Preventing fatal accidents in construction through the management of barriers

The research presented in this article addresses the construction industry's need for a real-time safety performance indicator for use in managing the risk of fatal accidents. It involves the development and testing of an indicator of the availability of barriers against fatal accidents when carrying out construction work. In designing the indicator, knowledge and experience from different fields have been utilized including classic barrier theory, barrier management in major-accident hazard industries, quality management, and safety performance measurement in construction. The main aim of the research has been to evaluate the barrier indicator in practical use. The evaluation is based on results from field tests of the barrier indicator at two construction sites and on data from fatal accidents in the construction industry. It provided support for the assumption in the design of the barrier indicator that a few types of hazards dominate the statistics of fatal accidents. The field tests demonstrated the usefulness of the barrier indicator, both in checking the status of the barriers in individual construction activities and in measuring the overall standard of barriers against fatal accidents on the construction site. The possibilities and limitations of the method are discussed based on general criteria for assessing safety performance indicators. Another aim has been to use the experiences from the field tests as input to the design of a method for barrier management through the phases of a construction project. This work resulted in a model that integrates the barrier indicator and underlying methods and tools into a barrier management system. There is significant potential for effective barrier management by integrating the indicator and associated methods and tools into the management systems in the construction industry utilizing digital technology.

Identification and analysis of influencing factors on construction quality management for rural drinking water safety projects

Abstract Exploring the influencing factors of construction quality management is the key to ensuring the quality of rural drinking water safety projects. Based on grounded theory, the influencing factors were identified and 65 relevant staff were selected by the objective sampling method for in-depth interviews to obtain the original data. In this study, 34 initial concepts, 18 main categories, and five core categories were collected and extracted for the rural drinking water project's safety engineering and construction quality management evaluation system. Furthermore, the incremental model of influencing factors on construction quality management performance of rural drinking water safety projects was established by the Decision-Making Trial and Evaluation Laboratory–Interpretive Structural Modeling (DEMATEL-ISM) model. Through calculation and analysis, the key influencing factors of construction quality management performance of rural drinking water safety projects were identified as controls on common quality problems, quality specification implementation, leadership level, acceptance management, design disclosure and modification, and human environment. Countermeasures and suggestions are proposed to improve the construction quality management performance of rural drinking water safety construction projects.

Applying Deep Learning and Single Shot Detection in Construction Site Image Recognition

A construction site features an open field and complexity and relies mainly on manual labor for construction progress, quality, and field management to facilitate job site coordination and productive results. It has a tremendous impact on the effectiveness and efficiency of job site supervision. However, most job site workers take photos of the construction activities. These photos serve as aids for project management, including construction history records, quality, and schedule management. It often takes a great deal of time to process the many photos taken. Most of the time, the image data are processed passively and used only for reference, which could be better. For this, a construction activity image recognition system is proposed by incorporating image recognition through deep learning, using the powerful image extraction ability of a convolution neural network (CNN) for automatic extraction of contours, edge lines, and local features via filters, and feeding feature data to the network for training in a fully connected way. The system is effective in image recognition, which is in favor of telling minute differences. The parameters and structure of the neural network are adjusted for using a CNN. Objects like construction workers, machines, and materials are selected for a case study. A CNN is used to extract individual features for training, which improves recognizability and helps project managers make decisions regarding construction safety, job site configuration, progress control, and quality management, thus improving the efficiency of construction management.

QUALITY MANAGEMENT PLATFORM INSPIRED DURING COVID-19 PANDEMIC FOR USE BY SUBCONTRACTORS IN PRIVATE HOUSING PROJECTS

Due to the COVID-19 pandemic in Taiwan, many construction sites must limit the number of people on the jobsite or conduct work independently to avoid the spread of COVID-19. The quality of construction may be in doubt with unclear job handover, especially when workers have COVID-19 infection that should be isolated immediately. On top of that, first-level subcontractor self-inspections are crucial parts of construction process management, and neglecting inspection processes can lead to construction errors and poor quality. To improve current quality inspection methods for private projects, a literature analysis was conducted to identify construction quality management issues that are faced in private housing projects. In-depth interviews with small and medium-sized subcontractors of private housing projects were performed to understand the quality management methods that they use in practice. Next, improvement measures for quality management were formulated and a simplified checklist for private project subcontractors, based on the practical feedback obtained, was created. Finally, the AppSheet platform was used to develop an inspection application for construction, and a subcontractor was invited to confirm its feasibility. The paperless design avoids redundant human contact, and the results of this study greatly facilitate construction practice, particularly during the pandemic. The main contribution of this study is its investigation of the procedures that are used by private project subcontractors to inspect their work for quality management; its results can serve as a reference for academics in evaluating construction quality management levels and improving the management of work by subcontractors to promote safety and health.

Relationship among Safety, Quality and Productivity in Construction Projects

Construction is thought to be the most dangerous business due to its unique nature. To reduce risks and boost productivity in the construction industry, quality and safety management is required. The research examines productivity, quality, and safety in terms of their participation in and effects on the execution of building projects. Safety is given first priority throughout construction, with a focus on hazard detection and the prevention of workplace injuries and accidents. There is an examination and provision of the legislation requiring safety programs, training, and obligation to safety standards. Underlined the significance of safety issues at the design stage. The research also discusses safety of building and the importance of building codes in preventing structural failure, as well as factors that influence building failure and techniques for preventing them. The paper introduces quality through the lens of recent total quality management. Quality control, quality management, quality assurance, and Six Sigma concepts are addressed with examples in relation to building quality and structural integrity. Finally, concepts of productivity are provided, with an emphasis that good project management reduce productivity losses and the use of lean construction and lean Six Sigma methods to complement them. Finally, the report summarizes the relationship among safety, quality, and productivity.

Production and construction quality management system of prefabricated buildings based on BIM technology

In order to improve the efficiency of quality management of prefabricated building production and construction, a quality management model and system design method of prefabricated building production and construction based on building information modelling (BIM) technology are proposed. The BIM big data of prefabricated building production and construction quality management is collected by using internet of things technology to build BIM information database. The method of fuzzy parameter fusion and performance tracking recognition is used to realise BIM data scheduling and feature distributed fusion. Through rough set feature matching and autocorrelation feature fusion, the model information is optimised and analysed by big data, and the optimal control and convergence judgment of prefabricated component production and construction quality management are realised. The simulation results show that this method has high degree of information fusion and strong resource scheduling ability in the production and construction quality management of prefabricated components.

Integrating Building Information Modelling (BIM) and Artificial Intelligence (AI) for Smart Construction Schedule, Cost, Quality, and Safety Management: Challenges and Opportunities

Integrating Building Information Modelling (BIM) and Artificial Intelligence (AI) for Smart Construction Schedule, Cost, Quality, and Safety Management: Challenges and Opportunities

Critical factors influencing learning from quality failures in the construction of grid infrastructure

PurposeQuality failures in grid infrastructure construction would cause large-scale collapses in power supply and additional expenditures by reworks and repairs. Learning from quality failures (LFQF) extracts experience from previous quality events and converts them into preventive measures to reduce or eliminate future construction quality issues. This study aims to investigate the influence factors of LFQF in the construction of grid infrastructure.Design/methodology/approachThe related factors of LFQF, including quality management (QM) practices, quality rectification, and individual learning, were identified by reviewing literature about organizational learning and extracting experience from previous failures. A questionnaire survey was distributed to the grid companies in North, Northeast, Northwest, East, Central, and Southwest China. 381 valid responses collected and analyzed using structural equation modeling (SEM) to test the influence of these factors on LFQF.FindingsThe SEM results support that QM practices positively affect individual learning and LFQF. Quality rectification indirectly impacts LFQF via individual learning, while the results did not support the direct link between quality rectification and LFQF.Practical implicationsThe findings strengthen practical insights into extracting experience from poor-quality issues and continuous improvement. The contributory factors of LFQF found in this study benefit the practitioners by taking effective measures to enhance organizational learning capability and improve the long-term construction quality performance in the grid infrastructure industry.Originality/valueExisting research about the application of LFQF still stays at the explorative and conceptual stage. This study investigates the related factors of LFQF, including QM practices, quality rectification, and individual learning, extending the model development of learning from failures (LFF) in construction QM.

Technology and Management Applied in Construction Engineering Projects

The current Special Issue is a digest of 13 published articles that referred to the following scientific and professional areas: construction project management and quality management in construction engineering and supervision; cost discount and the financial control of construction projects; multi-criteria feasibility studies of investment enterprises; the qualitative and quantitative research of engineering buildings by probabilistic and fuzzy sets approach; multidiscipline expertise investigations of buildings that significantly differ in structure and use.

Thoughts on Strengthening the Quality Management of Municipal Engineering Road and Bridge Construction

Thoughts on Strengthening the Quality Management of Municipal Engineering Road and Bridge Construction

Analysis of Construction Quality and Safety Management of Water Conservancy and Hydropower Engineering

Analysis of Construction Quality and Safety Management of Water Conservancy and Hydropower Engineering

Municipal Road and Bridge Construction Technology and Quality Management Measures

Municipal Road and Bridge Construction Technology and Quality Management Measures