A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization

Nooraziah Ahmad, Tiagrajah V. Janahiraman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

AISI 1045 steel is one of the most widely used steel in the manufacturing industry. In order to have the best quality of turned AISI 1045 steel product, surface roughness is being considered as output parameter. The two purposes of this research are to model the surface roughness using response surface methodology and to compare the different types of optimization approaches in order to identify the optimum surface roughness with particular combination of cutting parameters in turning operation. The result obtained from this study showed that the values from RSMs' prediction are 99.3% similar to the experimental values. While, particle swarm optimization give the lowest surface roughness when compared to Taguchi method and genetic algorithm and it can optimize faster than genetic algorithm.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE Conference on System, Process and Control, ICSPC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages129-133
Number of pages5
ISBN (Electronic)9781467376556
DOIs
Publication statusPublished - 18 May 2016
EventIEEE Conference on System, Process and Control, ICSPC 2015 - Bandar Sunway, Malaysia
Duration: 19 Dec 201520 Dec 2015

Other

OtherIEEE Conference on System, Process and Control, ICSPC 2015
CountryMalaysia
CityBandar Sunway
Period19/12/1520/12/15

Fingerprint

Taguchi Method
Taguchi methods
Surface Roughness
Machining
Particle swarm optimization (PSO)
Particle Swarm Optimization
Steel
Genetic algorithms
Surface roughness
Genetic Algorithm
Optimization
Response Surface Methodology
Manufacturing Industries
Lowest
Optimise
Prediction
Output
Industry

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Control and Optimization
  • Control and Systems Engineering

Cite this

Ahmad, N., & V. Janahiraman, T. (2016). A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization. In Proceedings - 2015 IEEE Conference on System, Process and Control, ICSPC 2015 (pp. 129-133). [7473572] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SPC.2015.7473572
Ahmad, Nooraziah ; V. Janahiraman, Tiagrajah. / A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization. Proceedings - 2015 IEEE Conference on System, Process and Control, ICSPC 2015. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 129-133
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abstract = "AISI 1045 steel is one of the most widely used steel in the manufacturing industry. In order to have the best quality of turned AISI 1045 steel product, surface roughness is being considered as output parameter. The two purposes of this research are to model the surface roughness using response surface methodology and to compare the different types of optimization approaches in order to identify the optimum surface roughness with particular combination of cutting parameters in turning operation. The result obtained from this study showed that the values from RSMs' prediction are 99.3{\%} similar to the experimental values. While, particle swarm optimization give the lowest surface roughness when compared to Taguchi method and genetic algorithm and it can optimize faster than genetic algorithm.",
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Ahmad, N & V. Janahiraman, T 2016, A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization. in Proceedings - 2015 IEEE Conference on System, Process and Control, ICSPC 2015., 7473572, Institute of Electrical and Electronics Engineers Inc., pp. 129-133, IEEE Conference on System, Process and Control, ICSPC 2015, Bandar Sunway, Malaysia, 19/12/15. https://doi.org/10.1109/SPC.2015.7473572

A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization. / Ahmad, Nooraziah; V. Janahiraman, Tiagrajah.

Proceedings - 2015 IEEE Conference on System, Process and Control, ICSPC 2015. Institute of Electrical and Electronics Engineers Inc., 2016. p. 129-133 7473572.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - AISI 1045 steel is one of the most widely used steel in the manufacturing industry. In order to have the best quality of turned AISI 1045 steel product, surface roughness is being considered as output parameter. The two purposes of this research are to model the surface roughness using response surface methodology and to compare the different types of optimization approaches in order to identify the optimum surface roughness with particular combination of cutting parameters in turning operation. The result obtained from this study showed that the values from RSMs' prediction are 99.3% similar to the experimental values. While, particle swarm optimization give the lowest surface roughness when compared to Taguchi method and genetic algorithm and it can optimize faster than genetic algorithm.

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Ahmad N, V. Janahiraman T. A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization. In Proceedings - 2015 IEEE Conference on System, Process and Control, ICSPC 2015. Institute of Electrical and Electronics Engineers Inc. 2016. p. 129-133. 7473572 https://doi.org/10.1109/SPC.2015.7473572