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Title: Modernisation of fault detection for diagnosis routines in elevators
Authors: Opeyemi, Olalere Isaac 
Issue Date: 2018
Maintenance of elevators has become critical in ensuring continued operation by preventing
excessive wear and breakdown. Maintenance greatly affects elevator downtime and uptime, hence
the need for modernising elevator maintenance to stay abreast of other competitors. This research
focuses on the modernisation of maintenance in elevator systems to reduce breakdowns through
scheduled maintenance via remote condition monitoring for fault detection using the Internet of
Things (IoT) technology. The monthly scheduled maintenance policy for the elevator system,
however, increased the downtime of the system due to lengthy response time to attend to elevator
breakdowns. This research therefore adopts remote monitoring of the elevator system’s condition
for early detection of malfunctioning and faults notification for a just-in-time maintenance
The parameters which could indicate a fault, deterioration, or damage of the elevator system were
identified. The methodology embraced building and configuring an electronic monitoring device
which comprises of the sensors, LED light, a voltage source, breadboard, jumper wires and an IoT
microcontroller. The microcontroller is programmed to monitor temperature, 3 axial vibration, and
acoustics parameters of the elevator system. Data and fault notifications are sent to a registered
email for remote monitoring access on the cloud. The IoT devices and controller make use of any
back up system which can be accessed in the cloud as a secondary storage system for the data
being read by the sensors and notification updates. The back-up system used in this research is
electronic mail. The read data from the machine was posted, together with the fault notification in
cases of malfunctioning of the condition, to an email cloud server.
The results show that remote condition monitoring of the elevator system is a better maintenance
approach as it reduces the downtime of the elevator system through just-in-time fault notification,
trend monitoring for fault troubleshooting and also diagnosis of fault from historical events. This
is indicated by a considerable reduced response time, (81%) as compared to the initial state of the
system, with a total response time of 45.4 hours for the 6 fault notifications experienced during the
condition monitoring unlike 240 hours for 4 breakdowns before modernising the maintenance
approach. Five of the six breakdowns experience were indicated by both vibration and acoustics
parameters which shows they are complimentary in fault diagnosis. An optimised limit for each
parameter was also derived using control chart for variables analysis.
Submitted in fulfilment of the requirements for the degree of Master of Engineering: Industrial Engineering, Durban University of Technology, Durban, South Africa, 2018.
Appears in Collections:Theses and dissertations (Engineering and Built Environment)

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