Tool Life Analysis By Partial Swarm Optimisation

Tool life is one of the main factors to be considered in CNC milling machine. Prediction model and optimum values are very important for the machinist to save number of cutting tools and reduce machining time. The aim of the this paper is to develop the tool life prediction model for P20 tool ste...

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Main Authors:	M. M., Noor, K., Kadirgama, M. S. M., Sani, M. M., Rahman, M. R. M., Rejab
Format:	Conference or Workshop Item
Language:	English
Published:	2009
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://umpir.ump.edu.my/id/eprint/1449/ http://umpir.ump.edu.my/id/eprint/1449/1/2009_P_NAE09_M.M.Noor_K.Kadirgama-conference-.pdf

id	ump-1449
recordtype	eprints
spelling	ump-14492018-01-23T02:44:04Z http://umpir.ump.edu.my/id/eprint/1449/ Tool Life Analysis By Partial Swarm Optimisation M. M., Noor K., Kadirgama M. S. M., Sani M. M., Rahman M. R. M., Rejab TJ Mechanical engineering and machinery Tool life is one of the main factors to be considered in CNC milling machine. Prediction model and optimum values are very important for the machinist to save number of cutting tools and reduce machining time. The aim of the this paper is to develop the tool life prediction model for P20 tool steel with aid of statistical method and to determine the optimisation values using partial swarm optimisation (PSO) for coated carbide cutting tool under different cutting conditions. By using response surface method, first and second order models were developed with 95% confidence level. The tool life model was developed in terms of cutting speed, feed rate, axial depth and radial depth. In general, the results obtained from the mathematical model are in good agreement with that obtained from the experiment data’s. It was found that the feed rate, cutting speed, axial depth and radial depth played a major role to determine the tool life. On the other hand, the tool life increases with the reduction of cutting speed and feed rate. For end-milling of P20 tool steel, the optimum cutting speed, feed rate, axial depth and radial depth obtained from PSO are of 100 m/s, 0.1 mm/rev, 1.9596 mm and 2 mm respectively. The optimized tool life of 40.52 min was obtained using the above mentioned parameters. 2009 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/1449/1/2009_P_NAE09_M.M.Noor_K.Kadirgama-conference-.pdf M. M., Noor and K., Kadirgama and M. S. M., Sani and M. M., Rahman and M. R. M., Rejab (2009) Tool Life Analysis By Partial Swarm Optimisation. In: 6th International Conference on Numerical Analysis in Engineering (NAE2009), 15 -16 May 2009 , Lombok Island, Mataram City, West Nusa Tenggara Province, Indonesia.. . (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TJ Mechanical engineering and machinery
spellingShingle	TJ Mechanical engineering and machinery M. M., Noor K., Kadirgama M. S. M., Sani M. M., Rahman M. R. M., Rejab Tool Life Analysis By Partial Swarm Optimisation
description	Tool life is one of the main factors to be considered in CNC milling machine. Prediction model and optimum values are very important for the machinist to save number of cutting tools and reduce machining time. The aim of the this paper is to develop the tool life prediction model for P20 tool steel with aid of statistical method and to determine the optimisation values using partial swarm optimisation (PSO) for coated carbide cutting tool under different cutting conditions. By using response surface method, first and second order models were developed with 95% confidence level. The tool life model was developed in terms of cutting speed, feed rate, axial depth and radial depth. In general, the results obtained from the mathematical model are in good agreement with that obtained from the experiment data’s. It was found that the feed rate, cutting speed, axial depth and radial depth played a major role to determine the tool life. On the other hand, the tool life increases with the reduction of cutting speed and feed rate. For end-milling of P20 tool steel, the optimum cutting speed, feed rate, axial depth and radial depth obtained from PSO are of 100 m/s, 0.1 mm/rev, 1.9596 mm and 2 mm respectively. The optimized tool life of 40.52 min was obtained using the above mentioned parameters.
format	Conference or Workshop Item
author	M. M., Noor K., Kadirgama M. S. M., Sani M. M., Rahman M. R. M., Rejab
author_facet	M. M., Noor K., Kadirgama M. S. M., Sani M. M., Rahman M. R. M., Rejab
author_sort	M. M., Noor
title	Tool Life Analysis By Partial Swarm Optimisation
title_short	Tool Life Analysis By Partial Swarm Optimisation
title_full	Tool Life Analysis By Partial Swarm Optimisation
title_fullStr	Tool Life Analysis By Partial Swarm Optimisation
title_full_unstemmed	Tool Life Analysis By Partial Swarm Optimisation
title_sort	tool life analysis by partial swarm optimisation
publishDate	2009
url	http://umpir.ump.edu.my/id/eprint/1449/ http://umpir.ump.edu.my/id/eprint/1449/1/2009_P_NAE09_M.M.Noor_K.Kadirgama-conference-.pdf
first_indexed	2023-09-18T21:54:36Z
last_indexed	2023-09-18T21:54:36Z
_version_	1777413994448945152

Tool Life Analysis By Partial Swarm Optimisation

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