Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.582910
Title: Design and analysis of the internally cooled smart cutting tools with the applications to adaptive machining
Author: Bin Che Ghani, Saiful Anwar
Awarding Body: Brunel University
Current Institution: Brunel University
Date of Award: 2013
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Abstract:
Adaptive machining with internally cooled smart cutting tools is a smart solution for industrial applications, which have stringent manufacturing requirements such as contamination free machining (CFM), high material removal rate, low tool wear and better surface integrity. The absence of cutting fluid in CFM causes the cutting tool and the workpiece subject to great thermal loads owing to higher friction and adhesion, and as a result may increase the levels of tool wear drastically. The increase in cutting temperature may influence the chip morphology which in return producing metal chips in unfavourable ribbon or snarl forms. CFM is difficult to be realized as contaminants can be in various forms in the machining operation and to avoid them totally requires a very tight controlled condition. However, the ecological, economical and technological demands compel the manufacturing practitioners to implement environmentally clean machining process (ECMP). Machining with innovative cooling techniques such as heat pipe, single-phase microduct, cryogenic or minimum quantity lubrication (MQL) has been intensely researched in recent years in order to reduce the cutting temperature in ECMP, thus enabling the part quality, the tool life and the material removal rate achieved in ECMP at least equate or surpass those obtained in conventional machining. On the other hand, the reduction of cutting temperature by using these techniques is often superfluous and is adverse to the produced surface roughness as the work material tends to inherent brittle and hard property at low temperature. Open cooling system means the machining requires a constant cooling supply and it does not provide a solution for process condition feedback as well.This Ph.D. project aims to investigate the design and analysis of internally cooled cutting tools and their implementation and application perspectives for smart adaptive machining in particular. Circulating the water based cooling fluid in a closed loop circuit contributes to sustainable manufacturing. The advantage of reducing cutting temperature from localized heat at the tool tip of an internally cooled cutting tool is enhanced with the smart features of the tool, which is trained by real experimental data, to cognitively vary the coolant flow rate, cutting feed rate or/and cutting speed to control the critical machining temperature as well as optimum machining conditions. Environmental friendly internal micro-cooling can avoid contamination of generated swarf which can also reduce the cutting temperature and thus reduce tool wear, increase machining accuracy and optimize machining economics. Design of the smart cutting tool with internal micro-cooling not only takes into account of the environmental aspects but also justifies with its ability to reduce the machining cost. Reduction of production cost can be achieved with the lower consumption of cooling fluid and improved machining resources/ energy efficiency. The models of structural, heat transfer, computational fluid dynamics (CFD) and tool life provide useful insight of the performance of the internally cooled smart cutting tool. Experimental validation using the smart cutting tool to machine titanium, steel and aluminium, indicates that the application of internally cooled smart cutting tools in adaptive machining can improve machining performance such as cutting temperature, cutting forces and surface quality generated. The useful tool life span is also extended significantly with internally cooled smart cutting tools in comparison to the tool life in conventional machining. The internally cooled smart cutting tool has important implications in the application to ECMP particularly by overcoming the stigma of high uncontrollable cutting temperature with the absence of cooling fluid.
Supervisor: Cheng, K.; Bateman, R. Sponsor: Brunel University
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.582910  DOI: Not available
Keywords: Intelligent manufacturing ; Adaptive control ; Smart cutting tool ; Smart machining
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