Prefabricated construction (PC) is an increasingly popular construction approach that offers numerous benefits, including greater efficiency, improved safety, and reduced material waste. However, this approach also introduces a new set of quality risks due to the complex process of off-site prefabrication, transportation, and on-site assembly. Currently, quality management (QM) in PC is mainly conducted through manual efforts that rely on human experience and established standards. This approach can be both inefficient and susceptible to human bias, which can lead to quality issues. To address these concerns, this study proposes a knowledge engineering-based framework that utilizes knowledge modeling and reasoning to enable intelligent QM. The framework consists of four layers: data acquisition, knowledge generation, knowledge storage, and value-added application. The proposed framework was applied to a case scenario, and the results showed that the open information stored in the knowledge base can guide the quality control process, and vice versa, enabling the quality control process to promote the updating of the knowledge base.