Effect Of Lathe Machining Parameters On Machining Characteristics Towards Mild Steel (AISI 1020) Using RSM

This project investigates the effect of lathe machining parameters on machining characteristics towards mild steel (AISI 1020) using Response Surface Method. The machining parameters selected on the experimental project are cutting speed (75m/min – 125m/min), feed rate (0.2mm/rev – 0.4mm/rev) and de...

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Main Author: Mansoor, Mohd Sufriansyah
Format: Thesis
Language:English
English
Published: 2019
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Online Access:http://eprints.utem.edu.my/id/eprint/24938/1/Effect%20Of%20Lathe%20Machining%20Parameters%20On%20Machining%20Characteristics%20Towards%20Mild%20Steel%20%28AISI%201020%29%20Using%20RSM.pdf
http://eprints.utem.edu.my/id/eprint/24938/2/Effect%20Of%20Lathe%20Machining%20Parameters%20On%20Machining%20Characteristics%20Towards%20Mild%20Steel%20%28AISI%201020%29%20Using%20RSM.pdf
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institution Universiti Teknikal Malaysia Melaka
collection UTeM Repository
language English
English
advisor Md Ali, Mohd Amran

topic T Technology (General)
TJ Mechanical engineering and machinery
spellingShingle T Technology (General)
TJ Mechanical engineering and machinery
Mansoor, Mohd Sufriansyah
Effect Of Lathe Machining Parameters On Machining Characteristics Towards Mild Steel (AISI 1020) Using RSM
description This project investigates the effect of lathe machining parameters on machining characteristics towards mild steel (AISI 1020) using Response Surface Method. The machining parameters selected on the experimental project are cutting speed (75m/min – 125m/min), feed rate (0.2mm/rev – 0.4mm/rev) and depth of cut (0.1mm-1.5mm). RSM using Box-Behnken was used to determine the most influential paremeters affected on the experimental response, investigate corelation between process parameters towards response and also to determine the optimum cutting parameters value that give minimum surface roughness and maximum material removal rate and hardness. There were 17 numbers of experiment has been conducted using the CNC lathe machine. The result collected was to optimize using RSM meanwhile P-value and R-squared were calculated using analysis of variance (ANOVA). From the result analysis obtained feed rate was the most influential parameters towards the surface roughness which contributes 53.88% of effect. Further, depth of cut and cutting speed are the most significant factor affected the material removal rate and hardness which contributes 66.78% and 37.40% of effect respectively. Interaction between process parameters was obtain and analyse towards surface roughness, material removal rate amd hardness. It found that, surface roughness value is decrease when the machine parameters at high cutting speed with low feed rate and depth of cut. Furthur, material removal rate increase when the machine parameters are at high cutting speed, feed rate and depth of cut. Meanwhile, when the machine parameters of cutting speed, feed rate and depth of cut are at middle value, the hardness value is significantly at highest value. Lastly, multiple optimization is perform and it shows that The combination of 101.2626 m/min cutting speed, 0.2444 mm/rev feed rate and the depth of 1.5 mm has a desirability of 0.6982 and the predicted values of MRR, surface roughness and hardness are 240.3743 g/min, 2.0669 µm and 44.3187 HRA respectively. Thus, all the objective of this project is achived and the optimal parameters are suceffully obtained to increase efficiency of machining process.
format Thesis
qualification_name Master of Philosophy (M.Phil.)
qualification_level Master's degree
author Mansoor, Mohd Sufriansyah
author_facet Mansoor, Mohd Sufriansyah
author_sort Mansoor, Mohd Sufriansyah
title Effect Of Lathe Machining Parameters On Machining Characteristics Towards Mild Steel (AISI 1020) Using RSM
title_short Effect Of Lathe Machining Parameters On Machining Characteristics Towards Mild Steel (AISI 1020) Using RSM
title_full Effect Of Lathe Machining Parameters On Machining Characteristics Towards Mild Steel (AISI 1020) Using RSM
title_fullStr Effect Of Lathe Machining Parameters On Machining Characteristics Towards Mild Steel (AISI 1020) Using RSM
title_full_unstemmed Effect Of Lathe Machining Parameters On Machining Characteristics Towards Mild Steel (AISI 1020) Using RSM
title_sort effect of lathe machining parameters on machining characteristics towards mild steel (aisi 1020) using rsm
granting_institution Universiti Teknikal Malaysia Melaka
granting_department Faculty of Manufacturing Engineering
publishDate 2019
url http://eprints.utem.edu.my/id/eprint/24938/1/Effect%20Of%20Lathe%20Machining%20Parameters%20On%20Machining%20Characteristics%20Towards%20Mild%20Steel%20%28AISI%201020%29%20Using%20RSM.pdf
http://eprints.utem.edu.my/id/eprint/24938/2/Effect%20Of%20Lathe%20Machining%20Parameters%20On%20Machining%20Characteristics%20Towards%20Mild%20Steel%20%28AISI%201020%29%20Using%20RSM.pdf
_version_ 1747834101284470784
spelling my-utem-ep.249382021-09-29T12:04:26Z Effect Of Lathe Machining Parameters On Machining Characteristics Towards Mild Steel (AISI 1020) Using RSM 2019 Mansoor, Mohd Sufriansyah T Technology (General) TJ Mechanical engineering and machinery This project investigates the effect of lathe machining parameters on machining characteristics towards mild steel (AISI 1020) using Response Surface Method. The machining parameters selected on the experimental project are cutting speed (75m/min – 125m/min), feed rate (0.2mm/rev – 0.4mm/rev) and depth of cut (0.1mm-1.5mm). RSM using Box-Behnken was used to determine the most influential paremeters affected on the experimental response, investigate corelation between process parameters towards response and also to determine the optimum cutting parameters value that give minimum surface roughness and maximum material removal rate and hardness. There were 17 numbers of experiment has been conducted using the CNC lathe machine. The result collected was to optimize using RSM meanwhile P-value and R-squared were calculated using analysis of variance (ANOVA). From the result analysis obtained feed rate was the most influential parameters towards the surface roughness which contributes 53.88% of effect. Further, depth of cut and cutting speed are the most significant factor affected the material removal rate and hardness which contributes 66.78% and 37.40% of effect respectively. Interaction between process parameters was obtain and analyse towards surface roughness, material removal rate amd hardness. It found that, surface roughness value is decrease when the machine parameters at high cutting speed with low feed rate and depth of cut. Furthur, material removal rate increase when the machine parameters are at high cutting speed, feed rate and depth of cut. Meanwhile, when the machine parameters of cutting speed, feed rate and depth of cut are at middle value, the hardness value is significantly at highest value. Lastly, multiple optimization is perform and it shows that The combination of 101.2626 m/min cutting speed, 0.2444 mm/rev feed rate and the depth of 1.5 mm has a desirability of 0.6982 and the predicted values of MRR, surface roughness and hardness are 240.3743 g/min, 2.0669 µm and 44.3187 HRA respectively. Thus, all the objective of this project is achived and the optimal parameters are suceffully obtained to increase efficiency of machining process. 2019 Thesis http://eprints.utem.edu.my/id/eprint/24938/ http://eprints.utem.edu.my/id/eprint/24938/1/Effect%20Of%20Lathe%20Machining%20Parameters%20On%20Machining%20Characteristics%20Towards%20Mild%20Steel%20%28AISI%201020%29%20Using%20RSM.pdf text en public http://eprints.utem.edu.my/id/eprint/24938/2/Effect%20Of%20Lathe%20Machining%20Parameters%20On%20Machining%20Characteristics%20Towards%20Mild%20Steel%20%28AISI%201020%29%20Using%20RSM.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=118038 mphil masters Universiti Teknikal Malaysia Melaka Faculty of Manufacturing Engineering Md Ali, Mohd Amran 1. Abhang, L .B., and Hameedullah, M., 2012. Optimization of Machining Parameters in Steel Turning Operation by Taguci Method. Procedia Engineering, 38, pp. 40-48. 2. Anderson, M., 1997. Design of Experiments. 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