Enhancing Knowledge Capture and Reuse for Offsite Construction Through A Container-Based Knowledge Approach

Offsite construction (OSC) requires an integrated design and delivery system. Reusing prior OSC knowledge is paramount to the success of new OSC projects. However, a gap remains in managing and reusing this knowledge across the broader industry. The challenge lies in the fragmented nature of project-based organisations with isolated knowledge systems, which often lack integration and advanced capabilities for knowledge-based collaboration. This paper proposes a novel framework that leverages cutting-edge knowledge-based methods and artificial intelligence (AI) technologies to create a container-based knowledge system (CBKS) that can enhance knowledge capture and reuse towards collaborative OSC. Specifically, the semantic web stack is adopted to construct multimodal knowledge containers for both human users and AI agents. In addition, GPT-4o, a large language model (LLM), is embedded into the knowledge system for better knowledge querying, matching and retrieving. By using this framework, constructed modular knowledge units can integrate product, process and organisation factors to address specific OSC problems. To evaluate the technical feasibility of the proposed framework, a prototype is developed and illustrated through a modular connection design. This illustrative case study demonstrates how knowledge is captured for product representation under manufacturing and assembly constraints, enabling its reuse in different projects. Moreover, the usefulness of GPT-4o for enhancing this process is also tested.