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Currently, building owners rely on lift servicing companies to carry out periodic and adhoc maintenance to ensure lift breakdowns are kept to a minimum level. Very often, when lift breakdowns happen and ad hoc repairs are done which will cause disruption of services to our users.
With the advancement of IOT sensors and artificial intelligence, we are looking for these technologies to be used to carry out predictive maintenance to the lift systems, so that ad hoc repairs arising from lift breakdown could be minimised . Lift is given as an example but building owners are interested to have a predictive maintenance system for other M&E equipment as well.
The lift monitoring system should reduce disruptive/emergency repairs, improve the safety of lift users, improve reliability of the lifts and reduce downtime of the lifts.
Use the gathered data for analysis and development of machine learning capability to predict lift failure.
Similar metrics would apply for successful predictive maintenance solutions for other M&E equipment.