Impacts & Benefits: (1) To speed up the production planning of modular integrated construction (MiC), which involves massive sub-contractors and suppliers in the factory; (2) To improve the dynamic scheduling capacity with dynamic risks and demands in MiC mass production; (3) To allow non-professionals to operate and interact on the production schedule without knowledge of complex scheduling model and software; (4) To keep in line with the initiatives of the 2022 and 2023 policy address, which strengthen the supply chain of the MiC and enhance collaboration with the GBA and optimize the MiC supply chain. Research Aim: To develop large language models (LLM) and knowledge graphs (KGs) enabled IoT-BIM platform for MiC production scheduling. Key Objectives with Innovations: (1) To adaptively construct the multi-source heterogeneous graph knowledge base (GKB) of production information elements (PIE); (2) To establish the configurator of scheduling models through the synergy of large language models (LLM) and knowledge graphs (KG) for initial schedule generation; (3) To develop an LLM-driven multi-agent system for rescheduling; (4) To develop natural language-based interfaces for integrating LLM-KG with IoT-BIM platform.