Track: Reliability and Maintenance

Abstract

Nowadays machinery condition monitoring is a comprehensive technique through which information about predicted failures could be extracted. This leads to improve reliability program such as time-based preventive maintenance. Without such improvement, this type of maintenance would lead to un-expected down time and thus more hidden costs of production. Machinery condition monitoring is necessary for any plant that strives to achieve its production goals. There are various condition monitoring techniques such as vibration analysis, thermographic analysis, ultrasonic detection, oil analysis and wear particle analysis. Wear particle analysis is considered a vital tool for condition monitoring in many lubricated machines. The main objective of this work is to apply condition-based maintenance using wear particle analysis for an industrial gearbox. The targeted gearbox is considered a crucial equipment attached to a carpet weaving machine, which is supposed to have the minimum possible sudden shutdown. The gearbox is Elasto-hydrodynamically lubricated and was conducted for monitoring through six months of sampling interval. Periodic samples of lubricant were taken and analyzed through spectrometer and laser net fines (LNF) equipment where elemental and Ferrographical analyses are applied respectively. Recommendations were addressed for better performance of the gearbox.