The objective of this project is to develop proactive condition monitored mechanical systems through:
- Development of sensors using novel multi-material additive manufacturing and 3D printing technologies
- Development of proactive decision-making software to recommend condition based maintenance actions based on the customized sensors.
Figure. 1: Failure Modes and Effect Analysis (FMEA), Finite Element Analysis (FEA), Multilayer Perceptron Artificial Neural Network and the temperature sensor design were investigated to develop the customized 3D printed sensors based on failure mechanisms of components.
The key benefits arising from this project are:
- Pre-emptive maintenance before the break down of a component to enable for safe and reliable travel with minimum disruptions
- Machine Learning algorithms to minimise false alarms and and also provides sharper diagnoses.
- Production of integrated sensors which enables organic condition monitoring capabilities.