Knowledge Management in Construction Quality Management: Current State, Challenges, and Future Directions
本文通过混合综述法分析了87篇文献，梳理了建筑质量管理中知识管理的关键技术（如BIM、本体、自然语言处理）和应用领域，提出了一个实施框架，并讨论了未来方向如数字孪生和大语言模型。
Construction quality management (CQM), as one of the major activities in construction project management, relies heavily on knowledge. Unfortunately, the knowledge of CQM is diverse in format and scattered in different stakeholders within the whole construction processes. Therefore, knowledge management (KM) of CQM is underinvestigated. To offering a comprehensive view of KM in CQM, this article employed a mixed review method to critically review 87 related articles. The results indicate 1) building information modeling, ontology, and natural language processing are identified as critical technologies in KM, 2) expert system and decision support, structural health monitoring, and project management are the major application domains. This article conducts an in-depth analysis of the literature based on the three phases of quality control: pre-construction, in-construction, and post-construction. The results are discussed to critically assess the critical technologies in KM. A framework is proposed to guide the effective implementation of KM in CQM, alongside a discussion of the current challenges and opportunities. The article further identifies potential development directions for KM in CQM, including total quality management, digital twins, development of large language models, construction of “No-cost” KM platforms, uniform evaluation and standardization mechanisms, tacit knowledge capture, and confidentiality and security. A novel paradigm for knowledge-driven quality management decision-making is first introduced. This article offers a comprehensive perspective on the application of KM in CQM, which will significantly enhance the effectiveness of CQM implementation in the future.