Surface Integrity And Tool Wear Of Hardened HTCS-150 Steel (52 HRC) In Milling With Tia1n Coated Carbide

Recent development in metal stamping introduced a new die namely hardened High Thermal Conductivity Steel-150 (HTC-150). Understanding the cutting parameters, surface characteristics and cutting tool wear during machining this new die would lead to efficiency in machining operation. This research co...

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Main Author: Azhar, Anis Afuza
Format: Thesis
Language:English
English
Published: 2019
Subjects:
Online Access:http://eprints.utem.edu.my/id/eprint/24671/
https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=117643
Abstract Abstract here
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author Azhar, Anis Afuza
author_facet Azhar, Anis Afuza
author_sort Azhar, Anis Afuza
description Recent development in metal stamping introduced a new die namely hardened High Thermal Conductivity Steel-150 (HTC-150). Understanding the cutting parameters, surface characteristics and cutting tool wear during machining this new die would lead to efficiency in machining operation. This research concentrated on the finishing process in machining HTCS-150 hardened steel (52 HRC) using ball nose end mill TiAlN coated carbide insert. The purpose of this study is to develop the regression model and optimization focused on the relationship between the cutting parameters (cutting speed, feed rate and axial depth of cut) and the response (surface roughness and cutting tool wear) by using Box-Behnken approach under Response Surface Methodology (RSM) experimental design. In addition to model development, Analysis of Variance (ANOVA) was employed to identify significant factors that influenced the surface roughness and cutting tool wear. Further analysis of surface characteristics and cutting tool wear were observed under Scanning Electron Microscope (SEM). Experimental processes were carried out using Variaxis MAZAK CNC 5 axis milling, assisted by the Design Expert 10 analysis software. Ranges of cutting parameters selected were 120-130 m/min cutting speeds, 0.3-0.5 mm/tooth feed rates, 0.1-0.5 mm axial depth of cut and 0.01 mm constant radial depth of cut. The results show the model develop adequately represent the process with modeling validation runs within the 90% of prediction interval and their residual errors compared to the predicted values were less than 10%. The optimization results show that the lowest surface roughness achieved at 125 m/min cutting speed, 0.30 mm/tooth feed rate and 0.1 mm axial depth of cut. Combination of cutting parameters for the lowest cutting tool wear recorded as 130 m/min cutting speed, 0.4 mm/tooth feed rate and 0.1 mm axial depth of cut. The ANOVA analysis shows that for the surface roughness, most influenced cutting parameters was axial depth of cut followed by feed rate and cutting speed. Meanwhile, for cutting tool wear, feed rate and depth of cut recorded as most influenced cutting parameter followed by cutting speed. Observation using SEM observed that feed marks, scratch, adhered material, smeared material, and surface porosity were major defects on the machined surface. Analysis of wear characteristics presented abrasion, coating delamination, adhesion, formation of built-up edge and chipping were among failure mechanisms observed. The results from experimental provide useful information to obtain ultra-fine surface finish and decrease the cutting tool wear during machining HTCS based materials to minimize post processing activities.
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spelling utem-246712021-10-05T11:36:26Z http://eprints.utem.edu.my/id/eprint/24671/ Surface Integrity And Tool Wear Of Hardened HTCS-150 Steel (52 HRC) In Milling With Tia1n Coated Carbide Azhar, Anis Afuza TJ Mechanical engineering and machinery Recent development in metal stamping introduced a new die namely hardened High Thermal Conductivity Steel-150 (HTC-150). Understanding the cutting parameters, surface characteristics and cutting tool wear during machining this new die would lead to efficiency in machining operation. This research concentrated on the finishing process in machining HTCS-150 hardened steel (52 HRC) using ball nose end mill TiAlN coated carbide insert. The purpose of this study is to develop the regression model and optimization focused on the relationship between the cutting parameters (cutting speed, feed rate and axial depth of cut) and the response (surface roughness and cutting tool wear) by using Box-Behnken approach under Response Surface Methodology (RSM) experimental design. In addition to model development, Analysis of Variance (ANOVA) was employed to identify significant factors that influenced the surface roughness and cutting tool wear. Further analysis of surface characteristics and cutting tool wear were observed under Scanning Electron Microscope (SEM). Experimental processes were carried out using Variaxis MAZAK CNC 5 axis milling, assisted by the Design Expert 10 analysis software. Ranges of cutting parameters selected were 120-130 m/min cutting speeds, 0.3-0.5 mm/tooth feed rates, 0.1-0.5 mm axial depth of cut and 0.01 mm constant radial depth of cut. The results show the model develop adequately represent the process with modeling validation runs within the 90% of prediction interval and their residual errors compared to the predicted values were less than 10%. The optimization results show that the lowest surface roughness achieved at 125 m/min cutting speed, 0.30 mm/tooth feed rate and 0.1 mm axial depth of cut. Combination of cutting parameters for the lowest cutting tool wear recorded as 130 m/min cutting speed, 0.4 mm/tooth feed rate and 0.1 mm axial depth of cut. The ANOVA analysis shows that for the surface roughness, most influenced cutting parameters was axial depth of cut followed by feed rate and cutting speed. Meanwhile, for cutting tool wear, feed rate and depth of cut recorded as most influenced cutting parameter followed by cutting speed. Observation using SEM observed that feed marks, scratch, adhered material, smeared material, and surface porosity were major defects on the machined surface. Analysis of wear characteristics presented abrasion, coating delamination, adhesion, formation of built-up edge and chipping were among failure mechanisms observed. The results from experimental provide useful information to obtain ultra-fine surface finish and decrease the cutting tool wear during machining HTCS based materials to minimize post processing activities. 2019 Thesis NonPeerReviewed text en http://eprints.utem.edu.my/id/eprint/24671/1/Surface%20Integrity%20And%20Tool%20Wear%20Of%20Hardened%20HTCS-150%20Steel%20%2852%20HRC%29%20In%20Milling%20With%20Tia1n%20Coated%20Carbide.pdf text en http://eprints.utem.edu.my/id/eprint/24671/2/Surface%20Integrity%20And%20Tool%20Wear%20Of%20Hardened%20HTCS-150%20Steel%20%2852%20HRC%29%20In%20Milling%20With%20Tia1n%20Coated%20Carbide.pdf Azhar, Anis Afuza (2019) Surface Integrity And Tool Wear Of Hardened HTCS-150 Steel (52 HRC) In Milling With Tia1n Coated Carbide. Masters thesis, Universiti Teknikal Malaysia Melaka. https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=117643
spellingShingle TJ Mechanical engineering and machinery
Azhar, Anis Afuza
Surface Integrity And Tool Wear Of Hardened HTCS-150 Steel (52 HRC) In Milling With Tia1n Coated Carbide
thesis_level Master
title Surface Integrity And Tool Wear Of Hardened HTCS-150 Steel (52 HRC) In Milling With Tia1n Coated Carbide
title_full Surface Integrity And Tool Wear Of Hardened HTCS-150 Steel (52 HRC) In Milling With Tia1n Coated Carbide
title_fullStr Surface Integrity And Tool Wear Of Hardened HTCS-150 Steel (52 HRC) In Milling With Tia1n Coated Carbide
title_full_unstemmed Surface Integrity And Tool Wear Of Hardened HTCS-150 Steel (52 HRC) In Milling With Tia1n Coated Carbide
title_short Surface Integrity And Tool Wear Of Hardened HTCS-150 Steel (52 HRC) In Milling With Tia1n Coated Carbide
title_sort surface integrity and tool wear of hardened htcs 150 steel 52 hrc in milling with tia1n coated carbide
topic TJ Mechanical engineering and machinery
url http://eprints.utem.edu.my/id/eprint/24671/
https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=117643
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