With the rapid development of digital technologies, intelligent construction has become a core driving force for the transformation and upgrading of the engineering industry. This study focuses on the integrated application of intelligent construction technologies (including BIM, IoT, AI, and digital twins) in engineering design and construction management, and explores the performance optimization path. Through literature review, case study and empirical analysis, the key technical points, application bottlenecks and performance evaluation indicators of intelligent technology integration are identified. The results show that the integrated application of intelligent technologies can significantly improve design efficiency, reduce construction risks and enhance project performance. Finally, targeted optimization strategies are proposed from the aspects of technical integration, management mechanism and talent training. This study provides theoretical support and practical guidance for the high-quality development of the engineering industry under the intelligent transformation background.

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The fragmentation between engineering design and construction management has long plagued the industry, leading to inefficiencies, cost overruns, and quality risks. With the advancement of digital twin (DT) technology, there is enormous potential to achieve intelligent integration of these two phases. This study proposes a DT-enabled systematic framework for integrating engineering design and construction management. First, it reviews the evolution of integration technologies and the application status of DT in the construction industry. Then, the framework‘s architecture, including the physical entity layer, virtual mirror layer, data transmission layer, and application service layer, is elaborated. Key integration mechanisms such as real-time data synchronization, collaborative decision-making, and dynamic process optimization are also analyzed. Finally, the framework is validated through a large-scale infrastructure project. Results show that the framework reduces design iteration time by 32%, construction rework rate by 28%, and project cost by 15%. This research provides a theoretical basis and practical guidance for promoting the intelligent transformation of engineering design and construction management.

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Engineering projects are characterized by long lifecycles, complex environments, and numerous uncertain factors, leading to diverse risks in the design, construction, operation, and maintenance phases. Traditional risk management methods suffer from discontinuous data, delayed risk perception, and inadequate dynamic response capabilities, failing to meet the requirements of full-lifecycle risk control. Digital Twin (DT) technology, with its advantages of virtual-real mapping, real-time data interaction, and dynamic simulation, provides a new approach to addressing these challenges. This study proposes a DT-driven full-lifecycle risk management framework for engineering projects. First, it systematically sorts out the risk characteristics of each phase of the engineering project lifecycle and the limitations of traditional risk management. Then, the framework‘s architecture, including the physical entity layer, virtual twin layer, data integration layer, risk management service layer, and application terminal layer, is constructed and elaborated. Key technologies such as multi-source data fusion, real-time risk monitoring, dynamic risk assessment, and intelligent risk response under the DT framework are also analyzed. Finally, the feasibility and effectiveness of the framework are verified through a case study of a large-scale urban rail transit project. Results indicate that the framework can improve risk identification accuracy by 42%, reduce risk response time by 35%, and lower the loss caused by risks by 28%. This research enriches the theory of engineering project risk management and provides practical guidance for realizing intelligent and refined risk control throughout the project lifecycle.

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Against the backdrop of global carbon neutrality commitments, the engineering design and construction industry, as a major carbon emitter, faces an urgent task of low-carbon transformation. This study focuses on the prominent problems in traditional collaborative management that hinder low-carbon development, such as disjointed low-carbon goals between design and construction phases, insufficient sharing of carbon emission data, and lack of systematic low-carbon decision-making mechanisms. By integrating low-carbon technology tools and collaborative management theories, the study constructs a low-carbon-oriented collaborative management framework covering the whole process of design, construction and commissioning. Through empirical research on three typical engineering projects (green commercial building, prefabricated residential community, and urban renewal project), the effectiveness and applicability of the framework are verified. The results show that the proposed framework can effectively reduce project carbon emissions by 18%-25%, improve the efficiency of low-carbon technology application by 30%, and enhance the synergy of low-carbon goal implementation among multiple participants. This study enriches the theoretical system of engineering collaborative management under the low-carbon background, and provides practical paths and technical support for the low-carbon transformation of the engineering industry.

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With the deep integration of digital technologies and the engineering industry, digital transformation has become an inevitable trend in promoting the high-quality development of engineering design and construction management. This study focuses on the collaborative management bottlenecks in the traditional engineering design and construction process, such as information asymmetry, poor process synergy, and low decision-making efficiency. By exploring the application of digital technologies such as Building Information Modeling (BIM), Internet of Things (IoT), and cloud computing, it proposes an innovative collaborative management framework based on digital twins. Through empirical research on multiple large-scale engineering projects, the effectiveness and feasibility of the framework are verified. The results show that the digital twin-driven collaborative management model can significantly improve information sharing efficiency, optimize resource allocation, and reduce project risks. This study provides theoretical support and practical guidance for the digital transformation of engineering design and construction collaborative management, and enriches the research results in the field of engineering management under the digital economy background.

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