Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach
This study was carried out to study the effects of using nanofluids as abrasive machining coolants. The objective of this study is to investigate the performance of grinding of ductile iron based on response surface method and to develop optimization model for grinding parameters using artificial ne...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English English |
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Asian Research Publishing Network (ARPN)
2016
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| Online Access: | http://umpir.ump.edu.my/id/eprint/11169/ http://umpir.ump.edu.my/id/eprint/11169/1/Optimization%20of%20Abrasive%20Machining%20of%20Ductile%20Cast%20Iron%20Using%20Tio2%20Nanoparticles-%20A%20Multilayer%20Perceptron%20Approach.pdf http://umpir.ump.edu.my/id/eprint/11169/7/fkm-2015-mmrahman-abrasive.pdf |
| _version_ | 1848818941021913088 |
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| author | M. M., Rahman K., Kadirgama M. M., Noor D., Ramasamy |
| author_facet | M. M., Rahman K., Kadirgama M. M., Noor D., Ramasamy |
| author_sort | M. M., Rahman |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | This study was carried out to study the effects of using nanofluids as abrasive machining coolants. The objective of this study is to investigate the performance of grinding of ductile iron based on response surface method and to develop optimization model for grinding parameters using artificial neural network technique. The abrasive machining process selected was surface grinding and it was carried out two different coolants which are conventional coolant and titanium dioxide nanocoolant. The selected inputs variables are table speed, depth of cut and type of grinding pattern which are single pass and multiple pass. The selected output parameters are temperature rise, surface roughness and material removal rate. The ANOVA test has been carried out to check the adequacy of the developed mathematical model. The second order mathematical model for MRR, surface roughness and temperature rise are developed based on response surface method. The artificial neural network model has been developed and analysis the performance parameters of grinding processes using two different types of coolant including the conventional as well as TiO2 nanocoolant. The obtained results shows that nanofluids as grinding coolants produces the better surface finish, good value of material removal rate and acts effectively on minimizing grinding temperature. The developed ANN model can be used as a basis of grinding processes. |
| first_indexed | 2025-11-15T01:45:39Z |
| format | Article |
| id | ump-11169 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T01:45:39Z |
| publishDate | 2016 |
| publisher | Asian Research Publishing Network (ARPN) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-111692018-09-06T01:56:42Z http://umpir.ump.edu.my/id/eprint/11169/ Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach M. M., Rahman K., Kadirgama M. M., Noor D., Ramasamy TJ Mechanical engineering and machinery This study was carried out to study the effects of using nanofluids as abrasive machining coolants. The objective of this study is to investigate the performance of grinding of ductile iron based on response surface method and to develop optimization model for grinding parameters using artificial neural network technique. The abrasive machining process selected was surface grinding and it was carried out two different coolants which are conventional coolant and titanium dioxide nanocoolant. The selected inputs variables are table speed, depth of cut and type of grinding pattern which are single pass and multiple pass. The selected output parameters are temperature rise, surface roughness and material removal rate. The ANOVA test has been carried out to check the adequacy of the developed mathematical model. The second order mathematical model for MRR, surface roughness and temperature rise are developed based on response surface method. The artificial neural network model has been developed and analysis the performance parameters of grinding processes using two different types of coolant including the conventional as well as TiO2 nanocoolant. The obtained results shows that nanofluids as grinding coolants produces the better surface finish, good value of material removal rate and acts effectively on minimizing grinding temperature. The developed ANN model can be used as a basis of grinding processes. Asian Research Publishing Network (ARPN) 2016 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/11169/1/Optimization%20of%20Abrasive%20Machining%20of%20Ductile%20Cast%20Iron%20Using%20Tio2%20Nanoparticles-%20A%20Multilayer%20Perceptron%20Approach.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/11169/7/fkm-2015-mmrahman-abrasive.pdf M. M., Rahman and K., Kadirgama and M. M., Noor and D., Ramasamy (2016) Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach. ARPN Journal of Engineering and Applied Sciences, 11 (4). pp. 2529-2534. ISSN 1819-6608. (Published) http://www.arpnjournals.org/jeas/research_papers/rp_2016/jeas_0216_3679.pdf |
| spellingShingle | TJ Mechanical engineering and machinery M. M., Rahman K., Kadirgama M. M., Noor D., Ramasamy Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach |
| title | Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach |
| title_full | Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach |
| title_fullStr | Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach |
| title_full_unstemmed | Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach |
| title_short | Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach |
| title_sort | optimization of abrasive machining of ductile cast iron using tio2 nanoparticles: a multilayer perceptron approach |
| topic | TJ Mechanical engineering and machinery |
| url | http://umpir.ump.edu.my/id/eprint/11169/ http://umpir.ump.edu.my/id/eprint/11169/ http://umpir.ump.edu.my/id/eprint/11169/1/Optimization%20of%20Abrasive%20Machining%20of%20Ductile%20Cast%20Iron%20Using%20Tio2%20Nanoparticles-%20A%20Multilayer%20Perceptron%20Approach.pdf http://umpir.ump.edu.my/id/eprint/11169/7/fkm-2015-mmrahman-abrasive.pdf |