An enhancement of integrated fuzzy-topsis to improve machining surface roughness

Machining is defined as a process to remove material in the form of chips using single or multiple wedge-shaped cutting tools to produce the desired shape. This process has successfully produced a closer dimensional accuracy and surface finish to meet the industrial demands. However, it is difficult...

Full description

Saved in:

Bibliographic Details
Main Author:	Mohd. Adnan, Mohd. Ridhwan Hilmi
Format:	Thesis
Language:	English
Published:	2014
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://eprints.utm.my/id/eprint/41588/1/MohdRidhwanHilmiMFSKSM2014.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-utm-ep.41588
record_format	uketd_dc
spelling	my-utm-ep.415882017-09-05T06:00:12Z An enhancement of integrated fuzzy-topsis to improve machining surface roughness 2014-02 Mohd. Adnan, Mohd. Ridhwan Hilmi TJ Mechanical engineering and machinery Machining is defined as a process to remove material in the form of chips using single or multiple wedge-shaped cutting tools to produce the desired shape. This process has successfully produced a closer dimensional accuracy and surface finish to meet the industrial demands. However, it is difficult to find the optimal machining parameter values that yield the minimum surface roughness (Ra) values to meet technical specifications for end milling and laser assisted machining (LAM). Thus, this research proposed the integration of Fuzzy Logic (FL) and Technique for Order Preference by Similarity to Ideal Situation (TOPSIS) to predict minimum Ra values and find the optimal machining parameters. In the proposed Fuzzy-TOPSIS model, initially FL is used to consider correct membership functions, linguistic terms and rules. Then, TOPSIS uses the weighted values obtained to handle instabilities in FL with advanced inference methods and rank the FL results by applying the obtained fuzzy intervals. The integration of Fuzzy-TOPSIS model has successfully reduced Ra values by 0.066µm for end milling and 0.112µm for LAM. Upon achieving the minimum values, a precise combination of optimal machining parameters can be obtained. These results reveal that the Fuzzy-TOPSIS model is capable of improving the quality of finished products during machining processes. 2014-02 Thesis http://eprints.utm.my/id/eprint/41588/ http://eprints.utm.my/id/eprint/41588/1/MohdRidhwanHilmiMFSKSM2014.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Computing Faculty of Computing
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TJ Mechanical engineering and machinery
spellingShingle	TJ Mechanical engineering and machinery Mohd. Adnan, Mohd. Ridhwan Hilmi An enhancement of integrated fuzzy-topsis to improve machining surface roughness
description	Machining is defined as a process to remove material in the form of chips using single or multiple wedge-shaped cutting tools to produce the desired shape. This process has successfully produced a closer dimensional accuracy and surface finish to meet the industrial demands. However, it is difficult to find the optimal machining parameter values that yield the minimum surface roughness (Ra) values to meet technical specifications for end milling and laser assisted machining (LAM). Thus, this research proposed the integration of Fuzzy Logic (FL) and Technique for Order Preference by Similarity to Ideal Situation (TOPSIS) to predict minimum Ra values and find the optimal machining parameters. In the proposed Fuzzy-TOPSIS model, initially FL is used to consider correct membership functions, linguistic terms and rules. Then, TOPSIS uses the weighted values obtained to handle instabilities in FL with advanced inference methods and rank the FL results by applying the obtained fuzzy intervals. The integration of Fuzzy-TOPSIS model has successfully reduced Ra values by 0.066µm for end milling and 0.112µm for LAM. Upon achieving the minimum values, a precise combination of optimal machining parameters can be obtained. These results reveal that the Fuzzy-TOPSIS model is capable of improving the quality of finished products during machining processes.
format	Thesis
qualification_level	Master's degree
author	Mohd. Adnan, Mohd. Ridhwan Hilmi
author_facet	Mohd. Adnan, Mohd. Ridhwan Hilmi
author_sort	Mohd. Adnan, Mohd. Ridhwan Hilmi
title	An enhancement of integrated fuzzy-topsis to improve machining surface roughness
title_short	An enhancement of integrated fuzzy-topsis to improve machining surface roughness
title_full	An enhancement of integrated fuzzy-topsis to improve machining surface roughness
title_fullStr	An enhancement of integrated fuzzy-topsis to improve machining surface roughness
title_full_unstemmed	An enhancement of integrated fuzzy-topsis to improve machining surface roughness
title_sort	enhancement of integrated fuzzy-topsis to improve machining surface roughness
granting_institution	Universiti Teknologi Malaysia, Faculty of Computing
granting_department	Faculty of Computing
publishDate	2014
url	http://eprints.utm.my/id/eprint/41588/1/MohdRidhwanHilmiMFSKSM2014.pdf
_version_	1747816577033568256

An enhancement of integrated fuzzy-topsis to improve machining surface roughness

Similar Items