الفهرس 
AbstractOnly 14 pages are availabe for public view
 |  | from | 126 |  |  |
| | | from | 126 | | |
Abstract
Maintenance management procedures are essential for achieving high industrial productivities and low expenditure cost. A major part of the cost in any production process is expended during maintenance of the operated equipment. To ensure plant reliability and improve equipment availability, a certain, clear, and effective maintenance policy has been implemented in this study as a part of applying the condition based maintenance technique, the core of predictive maintenance philosophy. In particular, this study explains how to use vibration parameters in the machinery failure diagnosis by collecting vibration readings and performing analysis of this data. The proposed maintenance methodology and its procedures have been implemented through a realistic case study. Through this case study, vibration readings have been obtained from an industrial air blower located in urea fertilizer production plant at Ain-Sokhna, Egypt. The equipment is acting as an air atomization blower during formation process of urea granules. It is considered the main and more critical equipment in the production facilities as its breakdown lead to complete shutdown of the production process. The proposed methodology has been organized in certain phases; starting with the setting of measuring instrumentation for data acquisition. Vibration data gathering from various determined locations of the blower and drive electric motor bearings in different directions. After that, feeding acquired data to the supporting vibration database analysis software on PC and following it up periodically until detection of high values or any unusual behavior. Evaluating of the resulted overall vibration data conducted according to vibrations severity chart of the international standard (ISO 10816- 1). Vibration data analysis performed on the basis of spectral plot, frequencies against amplitude. The spectral analysis was used to analyze blower vibrations to predict faults, their causes and consequences to determine the time of machine shutdown and required maintenance before failure. Vibration overall values and spectrum compared based on initial conditions, troubleshooting, and after carrying-out corrective action.