Multi-Objective Optimisation of CNC Milling Process for Al 6061 using Modified NSGA-II

Multi-Objective Optimisation of CNC Milling Process for Al 6061 using Modified NSGA-II

Computer numerical controlled (CNC) growth has revolutionised the manufacturing sectors by changing the way people work. In milling process, it has contributed to the higher productivity and better quality of the products. Although a lot of researches have been done on how to improve the process, th...

Full description

Bibliographic Details
Main Authors: M. F. F., Ab Rashid, N. M. Zuki, N. M., A. N. M., Rose
Format: Conference or Workshop Item
Language:English
English
Published: 2016
Subjects:
TJ Mechanical engineering and machinery
Online Access:http://umpir.ump.edu.my/id/eprint/14765/
http://umpir.ump.edu.my/id/eprint/14765/1/Multi-objective%20optimisation%20of%20CNC%20milling%20process%20for%20Al%206061.pdf
http://umpir.ump.edu.my/id/eprint/14765/7/fkm-2016-mff-Multi-Objective%20Optimisation%20Of%20CNC%20Milling.pdf
id ump-14765
recordtype eprints
spelling ump-147652018-04-27T07:22:26Z http://umpir.ump.edu.my/id/eprint/14765/ Multi-Objective Optimisation of CNC Milling Process for Al 6061 using Modified NSGA-II M. F. F., Ab Rashid N. M. Zuki, N. M. A. N. M., Rose TJ Mechanical engineering and machinery Computer numerical controlled (CNC) growth has revolutionised the manufacturing sectors by changing the way people work. In milling process, it has contributed to the higher productivity and better quality of the products. Although a lot of researches have been done on how to improve the process, the process improvement does not stop there because of evolving materials, methods and technologies. This paper presents a multi-objective optimisation of CNC milling process in order to achieve desired surface roughness and minimise machining time for Al 6061. A full factorial experiment has been conducted to model surface roughness by controlling three variables; spindle speed, feed rate and depth of cut. Multi-objective optimisation has been performed using modified Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) with two levels crossover. The optimisation result concluded that the modified NSGA-II was able to converge to Pareto-optimal, but having difficulties to spread solutions in wider range. 2016 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/14765/1/Multi-objective%20optimisation%20of%20CNC%20milling%20process%20for%20Al%206061.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/14765/7/fkm-2016-mff-Multi-Objective%20Optimisation%20Of%20CNC%20Milling.pdf M. F. F., Ab Rashid and N. M. Zuki, N. M. and A. N. M., Rose (2016) Multi-Objective Optimisation of CNC Milling Process for Al 6061 using Modified NSGA-II. In: 20th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2016), 5-7 September 2016 , York, United Kingdom. pp. 1-8.. (Unpublished)
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
M. F. F., Ab Rashid
N. M. Zuki, N. M.
A. N. M., Rose
Multi-Objective Optimisation of CNC Milling Process for Al 6061 using Modified NSGA-II
description Computer numerical controlled (CNC) growth has revolutionised the manufacturing sectors by changing the way people work. In milling process, it has contributed to the higher productivity and better quality of the products. Although a lot of researches have been done on how to improve the process, the process improvement does not stop there because of evolving materials, methods and technologies. This paper presents a multi-objective optimisation of CNC milling process in order to achieve desired surface roughness and minimise machining time for Al 6061. A full factorial experiment has been conducted to model surface roughness by controlling three variables; spindle speed, feed rate and depth of cut. Multi-objective optimisation has been performed using modified Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) with two levels crossover. The optimisation result concluded that the modified NSGA-II was able to converge to Pareto-optimal, but having difficulties to spread solutions in wider range.
format Conference or Workshop Item
author M. F. F., Ab Rashid
N. M. Zuki, N. M.
A. N. M., Rose
author_facet M. F. F., Ab Rashid
N. M. Zuki, N. M.
A. N. M., Rose
author_sort M. F. F., Ab Rashid
title Multi-Objective Optimisation of CNC Milling Process for Al 6061 using Modified NSGA-II
title_short Multi-Objective Optimisation of CNC Milling Process for Al 6061 using Modified NSGA-II
title_full Multi-Objective Optimisation of CNC Milling Process for Al 6061 using Modified NSGA-II
title_fullStr Multi-Objective Optimisation of CNC Milling Process for Al 6061 using Modified NSGA-II
title_full_unstemmed Multi-Objective Optimisation of CNC Milling Process for Al 6061 using Modified NSGA-II
title_sort multi-objective optimisation of cnc milling process for al 6061 using modified nsga-ii
publishDate 2016
url http://umpir.ump.edu.my/id/eprint/14765/
http://umpir.ump.edu.my/id/eprint/14765/1/Multi-objective%20optimisation%20of%20CNC%20milling%20process%20for%20Al%206061.pdf
http://umpir.ump.edu.my/id/eprint/14765/7/fkm-2016-mff-Multi-Objective%20Optimisation%20Of%20CNC%20Milling.pdf
first_indexed 2023-09-18T22:18:53Z
last_indexed 2023-09-18T22:18:53Z
_version_ 1777415522132951040

Similar Items