Optimization of abrasive machining of ductile cast iron using water based ZnO nanoparticles : a support vector machine approach
This project presents the optimization of abrasive machining of ductile cast iron using water based ZnO nanoparticles. This study were carried out to investigate the performance of grinding machine of ductile cast iron based on response surface methodology (RSM), to develop optimization model for gr...
| Main Author: | |
|---|---|
| Format: | Undergraduates Project Papers |
| Language: | English |
| Published: |
2012
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/4945/ http://umpir.ump.edu.my/id/eprint/4945/1/Optimization%20of%20abrasive%20machining%20of%20ductile%20cast%20iron%20using%20water%20based%20ZnO%20nanoparticles%20a%20support%20vector%20machine%20approach.pdf |
| _version_ | 1848817502056873984 |
|---|---|
| author | Mohd Syah Waliyullah Ad-Dahlawi, Mat Razali |
| author_facet | Mohd Syah Waliyullah Ad-Dahlawi, Mat Razali |
| author_sort | Mohd Syah Waliyullah Ad-Dahlawi, Mat Razali |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | This project presents the optimization of abrasive machining of ductile cast iron using water based ZnO nanoparticles. This study were carried out to investigate the performance of grinding machine of ductile cast iron based on response surface methodology (RSM), to develop optimization model for grinding parameters using support vector machine (SVM) and to investigate the effect of water based ZnO nanoparticles in grinding machine. Analysis of variance has been carried out to check the adequacy of the experimental results. The mathematical modeling has been developed using response surface methodology to investigate the performance of grinding machine of ductile cast iron. The optimization model of grinding parameter was developed and the effect of water based ZnO nanoparticles was investigated. From the obtained results, the optimum parameter for grinding model is 30m/min table speed and 40μm depth of cut. The quality of product was determined by output criteria that are minimum temperature rise, minimum surface roughness and maximum material removal rate. Based on prediction data from RSM shows that 2nd order gives the good performance of grinding machine with the significant p-value of analysis of variance that is below than 0.05 and support with R-square value nearly 0.99. Based on the support vector machine (SVM) results, high depth of cut and low table speed gives high quality of product. It shows that SVM result is acceptable since the results was the same as obtained results from response surface methodology (RSM) and can be used to optimize the grinding machine. The results also shows that water based ZnO nanoparticles as a nanocoolant give impact to the temperature rise. It gives temperature rise almost zero compared to conventional coolant. High temperature rise will affect the surface roughness of product, so that it is very efficiency to choose water based ZnOnano particles as a nanocoolant. As the conclusion, the results obtained from this project can be used to optimize the precision grinding machine to get high quality of product using water based ZnO nanoparticles. |
| first_indexed | 2025-11-15T01:22:47Z |
| format | Undergraduates Project Papers |
| id | ump-4945 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T01:22:47Z |
| publishDate | 2012 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-49452023-10-19T04:12:01Z http://umpir.ump.edu.my/id/eprint/4945/ Optimization of abrasive machining of ductile cast iron using water based ZnO nanoparticles : a support vector machine approach Mohd Syah Waliyullah Ad-Dahlawi, Mat Razali TJ Mechanical engineering and machinery This project presents the optimization of abrasive machining of ductile cast iron using water based ZnO nanoparticles. This study were carried out to investigate the performance of grinding machine of ductile cast iron based on response surface methodology (RSM), to develop optimization model for grinding parameters using support vector machine (SVM) and to investigate the effect of water based ZnO nanoparticles in grinding machine. Analysis of variance has been carried out to check the adequacy of the experimental results. The mathematical modeling has been developed using response surface methodology to investigate the performance of grinding machine of ductile cast iron. The optimization model of grinding parameter was developed and the effect of water based ZnO nanoparticles was investigated. From the obtained results, the optimum parameter for grinding model is 30m/min table speed and 40μm depth of cut. The quality of product was determined by output criteria that are minimum temperature rise, minimum surface roughness and maximum material removal rate. Based on prediction data from RSM shows that 2nd order gives the good performance of grinding machine with the significant p-value of analysis of variance that is below than 0.05 and support with R-square value nearly 0.99. Based on the support vector machine (SVM) results, high depth of cut and low table speed gives high quality of product. It shows that SVM result is acceptable since the results was the same as obtained results from response surface methodology (RSM) and can be used to optimize the grinding machine. The results also shows that water based ZnO nanoparticles as a nanocoolant give impact to the temperature rise. It gives temperature rise almost zero compared to conventional coolant. High temperature rise will affect the surface roughness of product, so that it is very efficiency to choose water based ZnOnano particles as a nanocoolant. As the conclusion, the results obtained from this project can be used to optimize the precision grinding machine to get high quality of product using water based ZnO nanoparticles. 2012-06 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/4945/1/Optimization%20of%20abrasive%20machining%20of%20ductile%20cast%20iron%20using%20water%20based%20ZnO%20nanoparticles%20a%20support%20vector%20machine%20approach.pdf Mohd Syah Waliyullah Ad-Dahlawi, Mat Razali (2012) Optimization of abrasive machining of ductile cast iron using water based ZnO nanoparticles : a support vector machine approach. Faculty of Mechanical Engineering, Universiti Malaysia Pahang. |
| spellingShingle | TJ Mechanical engineering and machinery Mohd Syah Waliyullah Ad-Dahlawi, Mat Razali Optimization of abrasive machining of ductile cast iron using water based ZnO nanoparticles : a support vector machine approach |
| title | Optimization of abrasive machining of ductile cast iron using water based ZnO nanoparticles : a support vector machine approach |
| title_full | Optimization of abrasive machining of ductile cast iron using water based ZnO nanoparticles : a support vector machine approach |
| title_fullStr | Optimization of abrasive machining of ductile cast iron using water based ZnO nanoparticles : a support vector machine approach |
| title_full_unstemmed | Optimization of abrasive machining of ductile cast iron using water based ZnO nanoparticles : a support vector machine approach |
| title_short | Optimization of abrasive machining of ductile cast iron using water based ZnO nanoparticles : a support vector machine approach |
| title_sort | optimization of abrasive machining of ductile cast iron using water based zno nanoparticles : a support vector machine approach |
| topic | TJ Mechanical engineering and machinery |
| url | http://umpir.ump.edu.my/id/eprint/4945/ http://umpir.ump.edu.my/id/eprint/4945/1/Optimization%20of%20abrasive%20machining%20of%20ductile%20cast%20iron%20using%20water%20based%20ZnO%20nanoparticles%20a%20support%20vector%20machine%20approach.pdf |