On site data gathering by a collaborative network to assess durability, reliability, service life, and maintenance performance

Any maintenance service could benefit from automatic and intelligent fault detection and diagnostics (intelligent AFDDs) to monitor building systems. Here, a system for FCUs (fan coils) is tailor-made to take full advantage of Collaborative Networking 4.0. Big data is collected by interconnected Internet of Things sensors and transferred to the cloud after local intelligence has identified which data is really significant for cloud transmission: to avoid network overload, anomaly detection and fault diagnostics are entrusted to local intelligence, cloud sending only out-of-range data and a very low-frequency sampling for standard data. By feeding the network with only the relevant processed data and sharing the information at each level, the resulting AFDD system becomes a collaborative network capable of extending the diagnostic process to the entire building, making it accessible through integration into an appropriate BIM model. Real-time data monitoring is vital to managing the facility maintenance service sustainably, but collecting big data on a wide scale enables other possibilities. For example, component service life rating to support a procurement service, and maintenance effectiveness by comparing the after-service values with the data recorded at the component’s acceptance.