Abstract:
One third of all maintenance costs are wasted as a result of unnecessary or improper maintenance activities since unlike production and manufacturing problems, maintenance receives little attention, which explains why the productivity of textile machineries like the speed frame machine suffers due to high end breaks which are mainly as a result of the tendency of the flyer to vibrate during production which stems from anomalies of parts like the bolster pinions, gears, the flyer spindle pinions and rolling bearings. To tackle this issue, this paper proposes a Reliability Centered maintenance based Early Warning System for a Zinser 660 speed frame machine. One of the most powerful algorithmic tools for vibration analysis is the time synchronous average (TSA).
Time synchronous averaging is a signal processing technique that extracts periodic waveforms from noisy data. The TSA is well suited for gearbox analysis, where it allows the vibration signature of the gear under analysis to be separated from other gears and noise sources in the gearbox that are not synchronous with that gear. With this, it is easier to distinguish between a healthy and unhealthy speed frame machine by inspecting the waveform thus giving the maintenance crew ample time to decide on the maintenance strategy to solve that specific anomaly.
The decision on whether to recommend this Early Warning System will be based on performing a cost benefit analysis of implementing the system.
Keywords: Reliability Centered Maintenance; Zinser 660 speed frame machine; Early Warning Systems; Time Synchronous Averaging.
