Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.706041
Title: Unsupervised monitoring of machining processes
Author: McLeay, T. E.
ISNI:       0000 0004 6062 5459
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2016
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Abstract:
Machining processes, such as milling, drilling, turning and grinding, concern the removal of material from a workpiece using a cutting tool. These processes are sensitive to parameters such as cutting tool properties, workpiece materials, coolant application, machine selection, fixturing and cutting parameters. The focus of the work in this thesis is to devise a method to monitor the changing conditions of a machining process over time in order to detect faulty machining conditions and diagnose fault types and causes. A key aim of this thesis is to develop a monitoring regime that has minimal cost of implementation and upkeep in a production environment, therefore an unsupervised monitoring system which applies non-intrusive sensing hardware is proposed.
Supervisor: Sharman, A. ; Turner, M. S. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.706041  DOI: Not available
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