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Title: An integrated approach to tool life management
Author: Ahmed, Zinah
ISNI:       0000 0004 7962 1351
Awarding Body: Cardiff University
Current Institution: Cardiff University
Date of Award: 2018
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Tool wear is a complex phenomenon occurring in all metal cutting processes. It reduces dimensional accuracy, impairs the surface integrity of the component and can have profound effects on the overall quality of the machined workpiece. Tool condition monitoring methods can be broadly split based on the source of signals collected by sensors into direct and indirect methods. In real life, it is not simple to model or predict. This thesis considers current shortcomings in applied approaches to tool management to demonstrate the need for more accurate assessment of tool condition and particularly remaining tool life. In this study, two kinds of indirect acquisition methods were used to estimate the tool wear. The post process method utilises the measurement of component geometry using a Coordinate Measure Machine. The in-process method utilises the acquisition and analysis of the applied spindle load from which tool wear can be estimated. A series of tests were conducted based upon the machining of a set of cylindrical holes. Two different diameter tools, 10 mm and 16 mm end mills, were used. The CMM acquired component geometry was used to calculate the tool wear indirectly. The method was proved to provide a good indication of the tool wear behaviour. In particular the approach is shown to be helpful for identifying the important change in the rate of tool wear. The developed online monitoring system, using the spindle motor load signal, is introduced in this thesis. It provides a practical method for detecting the progression of flank wear during machining. The results concluded that the signal amplitudes are increased when the flank wear increases. High cutting speed cause the flank wear to form quickly and shorten the tool life. This is an efficient and low-cost method that, with further development and testing, can be used in the real machining industry to predict the actual wear in the cutting tool.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available