Advancing Construction Quality Management: An Integrated Evidential Reasoning and Belief Functions Framework

Transformer condition monitoring and assessment is crucial as it can be applied to evaluate its maintenance needs. The current trend is to leave critical power transformers in service uninterrupted unless the monitored parameters indicate otherwise. This ensures optimal use of the facility and uninterrupted power supply to consumers. This paper presents the evaluation of the health status of a transformer using the dissolved gas analysis (DGA), oil testing and evidential reasoning criterion. In the analysis, the dissolved gases and oil testing parameters are first normalized and then transformed into fuzzy variables using trapezoid membership function. Then from fuzzy variables, the condition assessment is transformed into a multiple-attribute decision making (MADM) problem under an evidential reasoning (ER) framework. Two case studies are evaluated using actual field data to verify the methodology. Both demonstrate the applicability of the proposed methodology. This emerges as a good logical and systematic way of assessing the maintenance needs of a power transformer using operational data.

Data fusion within the evidential reasoning framework is a well established, robust and conservative technique to fuse uncertain information from multiple sensors. A number of fusion methods within this formalism were introduced including Dempster-Shafer theory (DST) fusion, Dezert Samarandche fusion (DSmT), and Smets' transferable belief model (TBM) based fusion. However, the impact of fusion on the level of uncertainty within these techniques has not been studied in detail. While the use of Shannon entropy within the Bayesian fusion is well understood, the measures of uncertainty within the Dempster-Shafer formalism is not widely regarded. In this paper, an uncertainty based technique is proposed to quantify the evolution of DST fusion. This technique is then utilised to determine the optimal combination of sensor information to achieve the least uncertainty in the context of an aircraft identification problem using electronics support measure (ESM) sensors.

With the rapid development of science, technology and economic strength in China, the construction industry has developed vigorously. Construction safety and quality management is a systematic project. The quality of construction will directly affect the safety of people's lives and property and the stable development of society. Construction quality and safety is the key to the success of construction projects. It is the fundamental guarantee to maintain the corporate image and obtain long-term economic benefits. Safety-critical system design needs to be guided and evaluated by security analysis. Fault tree based on binary decision graph is one of the commonly used methods of safety analysis in engineering. The risk assessment is based on the risk factor and the simulation application environment design experiment is performed. Correctly handling the relationship between construction safety and quality management plays an important role in the smooth completion of engineering projects and the stable development of society.

China's construction industry, despite over 30 years of development since the reform and opening-up period, remains largely traditional, characterized by outdated construction methods and labor-intensive practices. However, with the gradual disappearance of the "demographic dividend," the industry is facing a growing labor shortage. To adapt to the demands of new urbanization, industrialization, and informatization, as well as to align with the "dual carbon" development strategy and promote construction industrialization, China has been vigorously developing prefabricated residential projects. While significant progress has been achieved under supportive policies, the industry is still in a transitional phase from traditional to industrialized construction methods, with construction quality requiring further improvement. Considering the potential of contractor’s perspectives to enhance construction quality management, this study explores the evaluation of construction quality management in prefabricated residential projects through the lens of contractors. This study systematically reviews the fundamental theories of construction quality management evaluation for prefabricated residential projects and identifies initial evaluation indicators based on the characteristics of these projects through a literature analysis method. Subsequently, expert surveys are employed to finalize the evaluation indicators, establishing a contractor-based evaluation indicator system for construction quality management. The study then applies the Analytic Hierarchy Process (AHP) to calculate the weights of indicators at both the criterion and indicator levels and develops a construction quality management evaluation model using the fuzzy matter-element analysis method. The research results of this article provide an important basis for contractors to conduct quality management evaluations.

It is generally accepted that construction quality process implementation improves construction project performance through the systematic application of quality practices. It is equally established that current quality management systems, particularly compliance management, are essential for Small and medium-enterprises (SMEs) seeking effective completion of road-building infrastructure. Despite the opportunities offered by these quality practices, there are potential pitfalls. As low-cost economies proliferate, South African construction SMEs are under increasing pressure to be more flexible and innovative. The study examines the factors affecting the quality of work produced by construction SMEs through a regulatory road building procedure, namely design, construction, and execution. A questionnaire survey was conducted among 165 SME contractors, designers, and their experience was recorded of construction quality standards and performance improvement on completed work in the public sector in South Africa. A combination of descriptive and inferential statistics was used to analyse the data. The empirical findings established that five construction quality process factors affect the quality of road infrastructure projects undertaken by construction SMEs. These factors comprise construction process and design; construction quality management at the site level; the development and implementation of quality procedures and requirements; quality benchmarking issues; continuous improvement and communication. This study is of value to designers/consultants and managers in the construction SME sector as it helps to establish the factors affecting the quality of road infrastructure projects. Managers in analogous environments may also use the results of this study as a benchmark for competitive advantage. The results also provide a guideline for the successful construction quality implementation in small and medium-sized construction projects.
 Keywords: Construction quality; Continuous improvement; Design; Performance; Quality management.

This paper reviews past work in construction quality management by examining its major components in the context of a study framework derived from ISO 9000. Emphasis is placed on determining the state-of-the-art and exploring the roles that information technology already plays as well as could play in improving the quality management function. The authors elaborate on several dimensions of the quality management view of a project in terms of how it would interact with the physical, process, cost, and as-built views of a project, which are essential to the quality management function as well as to other project management functions. This is done in a way that reflects the authors' vision of the kind of support that a computer system could offer for the tasks of identifying, predicting, analyzing, and solving quality problems in a preventive mode.Key words: construction quality management, ISO 9000, problem prevention, problem prediction, computer system.

The aim of this study is to examine the barriers to the adoption of emerging technologies for quality management in construction projects. A questionnaire was designed to examine the barriers to the adoption of emerging technologies for quality management in construction projects. Questionnaires were distributed, and 127 valid responses were elicited. Thereafter, data were analysed using descriptive and inferential statistics. The study was limited to barriers to the adoption of emerging technologies in construction quality management in Nigeria utilising a quantitative research method. The study’s findings can serve as a model for tackling similar barriers in other countries in the global south. The results of the exploratory factor analysis reveal that the critical barriers to emerging technologies in construction quality management in the Nigerian construction industry can be grouped into three principal components: institutional and regulatory, organisational, and technology and industry collaboration barriers. Understanding these findings offers a roadmap for accelerating the adoption of emerging technologies in construction quality management, leading to improved productivity, reduced rework, enhanced compliance, and sustainable industry growth. Keywords: Adoption, Barriers, Construction projects, Emerging technologies, Quality management.

Earthfill dam construction requires effective strategies to ensure structural safety, construction quality, and efficient use of time and resources. This study examines the construction strategy and implementation method of the Main Dam of the Bagong Dam Project, Indonesia, which is designed as a vertically zoned earthfill embankment with a length of 620 m, a crest width of 12 m, a crest elevation of +330 m, and a height of 82 m. The research focuses on the application of a zoning-based construction approach to improve construction efficiency under complex field condition. The results indicate that dividing the embankment into six functional zones enables systematic layer-by-layer construction and parallel work execution, resulting in a planned construction duration of 937 working days. The integration of material zoning, quality control procedures, and optimized equipment management ensured that all embankment layers achieved more than 95% of maximum dry density. Coordinated equipment utilization further improved productivity, allowing approximately 304,653 m³ of embankment work to be completed within 53 working days during critical construction stages. In addition, the implementation of a structured safety management system supported the achievement of zero-accident construction performance. These findings demonstrate that the integration of zoning strategy, systematic construction sequencing, quality management, equipment planning, and safety control significantly enhances time and cost efficiency while maintaining construction quality. The proposed approach provides a practical framework for earthfill dam construction projects in Indonesia and other regions with similar geological and climatic conditions.

With the rapid development of intelligent buildings, scientific and effective quality management is of great significance. Therefore, the study adopts drone oblique photography technology to achieve 3D modeling of intelligent construction sites, and effectively obtains ground point clouds using fabric simulation filtering algorithms. Meanwhile, using Fast RCNN (Fast Region Convolutional Neural Network) to achieve object detection during the construction process. In addition, the Plan Do Check Act (PDCA) cycle will be introduced into overall construction quality management. The research results show that the average total error rate, first level error rate, and second level error rate of the fabric simulation filtering algorithm are 6.14%, 2.01%, and 9.35%, respectively. In the safety helmet wearing detection, the detection accuracy and recall of the fast area convolutional neural network reached 89.6% and 91.8%, respectively, with a frame rate of 39.8 frames per second. In addition, in practical applications, the algorithm has a pass rate of over 88% in various engineering projects. This management strategy combines intelligent construction sites with the planning execution inspection action cycle, which has significant performance advantages and application effects, providing reliable technical support for intelligent remote building quality management.

Engineering survey is an important technology applied in the quality management of construction engineering. By conducting engineering survey, it can provide necessary data support and measurement methods for the early exploration, mid-term construction, and later acceptance quality management of construction engineering. In the process of construction quality management, how to apply the engineering measurement technology reasonably becomes an urgent problem to be solved. This article will give an overview of engineering survey, and describe the important role of it, and give some opinions and suggestions.

The construction stage of the building project is an important link that takes the longest time, the most complex technology and the greatest impact on the quality level of the green building in the whole life cycle of the building. Therefore, the first step is to start from the construction stage in order to improve the quality management level of green building and realize the maximization of green building quality and environmental, economic and social benefits. This paper focuses on the construction quality management in the whole process of green building planning, design, construction, operation and scrapping system, introduces the idea of green building engineering, studies the construction quality problems of green building, and puts forward a new construction quality management strategy and mode. The new construction quality management strategy and mode can control the quality of green building construction stage, and promote the development and promotion of green building action.

The northern coast of Mauritania presents a strategic opportunity for clean energy investment due to its remarkable potential for green hydrogen production through wind energy. To determine the best location for wind-based green hydrogen production, this paper established a Multi-Criteria Decision-Making framework (MCDM) that combines the Analytic Hierarchy Process (AHP) and Evidential Reasoning (ER) to assess five coastal sites: Nouakchott, Nouamghar, Tasiast, Boulanoir, and Nouadhibou. Four main criteria (i.e., economic, technical, environmental, and social) and twelve sub-criteria were taken into account in the assessment. To ensure reliability and contextual accuracy, the data used in this study were obtained from geographic databases, peer-reviewed literature, and structured expert questionnaires. The results indicate that site 5 (Nouadhibou) is the most suitable location for green hydrogen generation using wind energy. Sensitivity analysis confirms the robustness of the ranking results, validating the reliability of the proposed hybrid framework. The findings of this study provide critical, data-driven decision-support insights for investors and policymakers, guiding the strategic development of sustainable wind-based green hydrogen projects along Mauritania’s coastline.

With the rapid development of the machinery and the increasing complexity of the steam turbine generator set, it is a great challenge for the safe and reliable operation of the steam turbine generator set. The uncertainties of fault classification and complicated working conditions become important research fields of steam turbine generator. A probability method on the uncertainty reasoning of fault classification for steam turbine generator is proposed in this paper based on the 2D-holospectrum and Bayesian decision theory. Firstly, Bayesian decision theory is adopted for the preliminary fault estimation on actual risk loss by calculating the loss expectation of each decision. Then, the area ratio of overlap region in 2D-holospectrum and the evidence theory can give the probability of the fault. Framework and model of the uncertainty reasoning are also described in this paper. Finally, the model is verified by the experiment of the rotor vibration on test rig. The results show that the method proposed is feasible for reasoning under imperfect information condition.

Multisensor information fusion technology plays an essential role in fault diagnosis. Uncertain reasoning is the core of information fusion, and the DS evidence theory (DSE) has founded a general and popular framework for uncertainty reasoning. Under this framework, a novel information fusion method is developed in this article, to solve the problems of counterintuitive results, poor robustness, and “one-vote veto” when fusing highly conflicting evidence using DSE. We proposed a new synthetic indicator, which can effectively eliminate the conflicts between evidences. This synthetic indicator is composed of two indexes: measurement index of indirect conflicts and that of the evidence’s information itself. First, the divergence is used to measure the degree of conflict between bodies of evidence, and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) model is employed to deal with indirect conflicts. Second, the Deng entropy is utilized to quantitatively measure the uncertainty of evidences, and the relative credibility preference of the evidence is expressed by the fuzzy preference relation. Finally, the initial body of evidence frame is weighted and revised by synthetic indicator before adopting the Dempster Shafer (DS) fusion rule. The superiority of the developed method is illustrated by numerical examples and application cases. The results show that fault diagnosis using the developed information fusion method can have a higher diagnostic accuracy.

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.