Development Of Generative Computer-Aided Process Planning System For Lathe Machining

Computer Aided Process Planning (CAPP) is the bridge between computer-aided design (CAD) and computer-aided manufacturing (CAM). CAPP functions as the recognizer of the geometric input from CAD and analyse it into specific function for manufacturing purpose in CAM. These functions always create irre...

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Main Author:	Zubair, Ahmad Faiz
Format:	Thesis
Language:	English
Published:	2019
Subjects:	T Technology (General) TJ1-1570 Mechanical engineering and machinery
Online Access:	http://eprints.usm.my/48104/1/Development%20Of%20Generative%20Computer-Aided%20Process%20Planning%20System%20For%20Lathe%20Machining.pdf
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id	my-usm-ep.48104
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spelling	my-usm-ep.481042021-11-17T03:42:11Z Development Of Generative Computer-Aided Process Planning System For Lathe Machining 2019-09-01 Zubair, Ahmad Faiz T Technology (General) TJ1-1570 Mechanical engineering and machinery Computer Aided Process Planning (CAPP) is the bridge between computer-aided design (CAD) and computer-aided manufacturing (CAM). CAPP functions as the recognizer of the geometric input from CAD and analyse it into specific function for manufacturing purpose in CAM. These functions always create irregular data descriptions in current CAD and CAM system supply and demand. This study attempts to solve this problem by recognizing the part model’s features via its geometrical based and produce sub-delta volumes that can later be used to generate manufacturing feature-based data for CAM in a single system via generations of algorithm through open source 3D CAD modeller. To map the generated sub-delta volume and respective machining process, part model complexity (PMC) is introduced. Errors of the overall delta volume (ΔODV) were calculated and verification of the proposed PMC is done. Furthermore, to minimize unit production cost, machining parameters including cutting speed (CS), feed rate (f) and depth of cut (d) were optimized for regular form surfaces by using firefly algorithm (FA). These parameters were then useful for tooling selections and tool-path planning. The results from the automatic feature recognitions show less than 0.02% of error in comparison of algorithm overall delta volume, (ODValg) and the manual calculation ODV, (ODVmanual). To validate the generated tool-path, G-codes generated in media package file (MPF) file format and verified through CNC lathe machine. Indeed, the developed algorithm was able to determine the minimum unit production cost of lathe machining part model. Therefore, a single automatic system that able to transfer CAD data into machining readable data through CAM data had been developed. 2019-09 Thesis http://eprints.usm.my/48104/ http://eprints.usm.my/48104/1/Development%20Of%20Generative%20Computer-Aided%20Process%20Planning%20System%20For%20Lathe%20Machining.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Kejuruteraan Mekanik
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	T Technology (General) TJ1-1570 Mechanical engineering and machinery
spellingShingle	T Technology (General) TJ1-1570 Mechanical engineering and machinery Zubair, Ahmad Faiz Development Of Generative Computer-Aided Process Planning System For Lathe Machining
description	Computer Aided Process Planning (CAPP) is the bridge between computer-aided design (CAD) and computer-aided manufacturing (CAM). CAPP functions as the recognizer of the geometric input from CAD and analyse it into specific function for manufacturing purpose in CAM. These functions always create irregular data descriptions in current CAD and CAM system supply and demand. This study attempts to solve this problem by recognizing the part model’s features via its geometrical based and produce sub-delta volumes that can later be used to generate manufacturing feature-based data for CAM in a single system via generations of algorithm through open source 3D CAD modeller. To map the generated sub-delta volume and respective machining process, part model complexity (PMC) is introduced. Errors of the overall delta volume (ΔODV) were calculated and verification of the proposed PMC is done. Furthermore, to minimize unit production cost, machining parameters including cutting speed (CS), feed rate (f) and depth of cut (d) were optimized for regular form surfaces by using firefly algorithm (FA). These parameters were then useful for tooling selections and tool-path planning. The results from the automatic feature recognitions show less than 0.02% of error in comparison of algorithm overall delta volume, (ODValg) and the manual calculation ODV, (ODVmanual). To validate the generated tool-path, G-codes generated in media package file (MPF) file format and verified through CNC lathe machine. Indeed, the developed algorithm was able to determine the minimum unit production cost of lathe machining part model. Therefore, a single automatic system that able to transfer CAD data into machining readable data through CAM data had been developed.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Zubair, Ahmad Faiz
author_facet	Zubair, Ahmad Faiz
author_sort	Zubair, Ahmad Faiz
title	Development Of Generative Computer-Aided Process Planning System For Lathe Machining
title_short	Development Of Generative Computer-Aided Process Planning System For Lathe Machining
title_full	Development Of Generative Computer-Aided Process Planning System For Lathe Machining
title_fullStr	Development Of Generative Computer-Aided Process Planning System For Lathe Machining
title_full_unstemmed	Development Of Generative Computer-Aided Process Planning System For Lathe Machining
title_sort	development of generative computer-aided process planning system for lathe machining
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Kejuruteraan Mekanik
publishDate	2019
url	http://eprints.usm.my/48104/1/Development%20Of%20Generative%20Computer-Aided%20Process%20Planning%20System%20For%20Lathe%20Machining.pdf
_version_	1747821881018286080

Development Of Generative Computer-Aided Process Planning System For Lathe Machining

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