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This research develops a reference architecture and functional model for intelligent monitoring and fault diagnosis of large complex automated systems in manufacturing and logistics. This reference architecture organises the monitoring and diagnosis functions in a modified hierarchical manner with multiple levels, and is therefore easily scalable to meet growing requirements of different application scenarios. The architecture is efficient as it allows problems to be quickly dealt with closer to their sources; therefore minimising intra-level data communication and messaging. Similarly the proposed functional model for monitoring and diagnosis unit can be adopted (i.e., scaled up or down) to suit the needs of the application, and indeed it fits well into the proposed reference architecture. A successful case of applying the proposed architecture and model is presented which serves to illustrate how they can be implemented in real-life to solve a class of monitoring and diagnosis problems for large automated systems typically found in manufacturing and logistics.