Process modelling and simulation for prediction of chip morphology during machining of stainless steel / Lafishahzreen Maharam

Machining process is one of the famous technique to remove material from surface workpiece that will also produce chip during machining. This process hard to understand because involved the interaction between two materials in a complicated dynamic process. There are many effort around the world to...

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Main Author: Maharam, Lafishahzreen
Format: Student Project
Language:English
Published: 2017
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/53898/1/53898.PDF
https://ir.uitm.edu.my/id/eprint/53898/
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spelling my.uitm.ir.538982021-12-02T02:49:29Z https://ir.uitm.edu.my/id/eprint/53898/ Process modelling and simulation for prediction of chip morphology during machining of stainless steel / Lafishahzreen Maharam Maharam, Lafishahzreen Machine shops and machine shop practice Machine tools and machining Abrading machinery. Grinding, lapping, etc. Sharpening Machining process is one of the famous technique to remove material from surface workpiece that will also produce chip during machining. This process hard to understand because involved the interaction between two materials in a complicated dynamic process. There are many effort around the world to understand these complex phenomenon. In order to understand behaviour of this cutting process, too many waste was produced due to a lot of trial and error in experimental activities. Suitable selections of parameter and condition play significant role to get desire result of cutting process. One of the fastest way to understand this cutting process is by using Finite Element Method (FEM). FEM is a useful and powerful tool to predict the machining process behaviour that hard to obtain and analyse using experimental methods. In this study, the 3D model of turning process of Stainless Steel 316L (workpiece) using tungsten carbide, WC (cutting tool) was developed by FEM software ABAQUS. Three different velocity of cutting tool which are 185,415 and 660 (m/min) was carried out as manipulated variables. FEM is a reliable method for quick change of variables like in real situation without producing a physical sample. In this work, the simulation of cutting process was conducted to examine the chip morphology and their stress distribution in the workpiece. Then, chip morphology was compared with previous study and look the gap between these two techniques. From the results obtained, developed model was successfully produced similar chip morphology produced by experiments. 2017-07 Student Project NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/53898/1/53898.PDF ID53898 Maharam, Lafishahzreen (2017) Process modelling and simulation for prediction of chip morphology during machining of stainless steel / Lafishahzreen Maharam. [Student Project] (Unpublished)
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Machine shops and machine shop practice
Machine tools and machining
Abrading machinery. Grinding, lapping, etc. Sharpening
spellingShingle Machine shops and machine shop practice
Machine tools and machining
Abrading machinery. Grinding, lapping, etc. Sharpening
Maharam, Lafishahzreen
Process modelling and simulation for prediction of chip morphology during machining of stainless steel / Lafishahzreen Maharam
description Machining process is one of the famous technique to remove material from surface workpiece that will also produce chip during machining. This process hard to understand because involved the interaction between two materials in a complicated dynamic process. There are many effort around the world to understand these complex phenomenon. In order to understand behaviour of this cutting process, too many waste was produced due to a lot of trial and error in experimental activities. Suitable selections of parameter and condition play significant role to get desire result of cutting process. One of the fastest way to understand this cutting process is by using Finite Element Method (FEM). FEM is a useful and powerful tool to predict the machining process behaviour that hard to obtain and analyse using experimental methods. In this study, the 3D model of turning process of Stainless Steel 316L (workpiece) using tungsten carbide, WC (cutting tool) was developed by FEM software ABAQUS. Three different velocity of cutting tool which are 185,415 and 660 (m/min) was carried out as manipulated variables. FEM is a reliable method for quick change of variables like in real situation without producing a physical sample. In this work, the simulation of cutting process was conducted to examine the chip morphology and their stress distribution in the workpiece. Then, chip morphology was compared with previous study and look the gap between these two techniques. From the results obtained, developed model was successfully produced similar chip morphology produced by experiments.
format Student Project
author Maharam, Lafishahzreen
author_facet Maharam, Lafishahzreen
author_sort Maharam, Lafishahzreen
title Process modelling and simulation for prediction of chip morphology during machining of stainless steel / Lafishahzreen Maharam
title_short Process modelling and simulation for prediction of chip morphology during machining of stainless steel / Lafishahzreen Maharam
title_full Process modelling and simulation for prediction of chip morphology during machining of stainless steel / Lafishahzreen Maharam
title_fullStr Process modelling and simulation for prediction of chip morphology during machining of stainless steel / Lafishahzreen Maharam
title_full_unstemmed Process modelling and simulation for prediction of chip morphology during machining of stainless steel / Lafishahzreen Maharam
title_sort process modelling and simulation for prediction of chip morphology during machining of stainless steel / lafishahzreen maharam
publishDate 2017
url https://ir.uitm.edu.my/id/eprint/53898/1/53898.PDF
https://ir.uitm.edu.my/id/eprint/53898/
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score 13.18916