الفهرس 
Machine Health MonitoringOnly 14 pages are availabe for public view
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Abstract
Practical vibration analysis is a tool to identify and predict failure in rotating machinery. Implementing vibration analysis could lead to better machine efficiency; reduce downtime and eliminating mechanical or electrical failures.
Using signal-processing methods to extract the fault features from the collecting sensor data. Hence, analyzing the signature of the fault features, machine faults will
be detected and diagnosed. The Present study is to prove that Machine Health and availability achievement is easier by using Machine Health Monitoring system; the scope will be on Tissue Paper Mill focusing on Forming Roll bearings by monitoring fault progress during operation to avoid any unwanted vibration that could lead to production loss or a severe damage or bad product quality.
Forming roll consists of a symmetric rotor supported on two similar bearings that is derived by motor gearbox system. Modeling is used to get the dynamic characteristics of the rotor bearing system. Finite element method, solid work and Ansys are conducted to extract forming roll modal parameters, which would help to
avoid operational risk under speed varying condition. Hybrid approach is
conducted as well to simplify modelling of complex system in order to study the torsional oscillation that could affect forming roll shell and paper quality as well. A
comparison of three maintenance strategies such as Run to failure “RTF” , Preventive Maintenance “PM” and condition based maintenance “CBM” is conducted based on cost calculation of “labor and materials”, production loss “time, speed, quality”, and any additional damage which proves that condition based Maintenance “CBM” is the most cost effective strategy for our study. Our case study of Forming Roll focuses on Bearings as one of the most critical mechanical components, which is subjected to higher load, and sometimes insufficient lubrication. Applying Condition Monitoring and Fault Diagnosis are very essential to ensure safe operation and reduce cost.
In the past the portable data-collectors being used to measure vibration levels at various points. Nowadays Machinery Health Monitoring system becoming essential
for continual monitoring of tissue paper rolls bearings to avoid any sudden fault developing before next time scheduled. Using different Vibration Analysis techniques combined with the good knowledge of Failure Modes and Effects Analysis “FMEA“ will help decision maker taking the right action on the right time. Through this study, various Vibration Analysis techniques such as Spectrum, Time Waveform and Impact Demodulation are used to support Decision-Making.
The present study proved that Impact Demod is a useful technique to specify faulty bearing source location and severity, while “Time Waveform” or “Spectrum Analysis” techniques can detect fault progress but couldn‟t distinguish the source location for similar bearings. Based on Impact Demod technique, only the higher
severity faulty bearing was exchanged and the other one postponed for next
planned shutdown. Consequently, the machine Availability and Health achieved by removing the bearing fault, decreasing the floor level and reducing vibration impact around 100 % through continuous condition monitoring.