Optimization of electrical discharge machine on mild steel AISI 1020 by using grey relational analysis
This report deals with machining workpiece mild steel AISI 1020 using electrical discharge machining (EDM). The objective of this thesis is to optimize the surface roughness (SR), electrode wear ratio (EWR) and material removal rate (MRR) by using grey relational analysis (GRA) with orthogonal array...
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| Format: | Undergraduates Project Papers |
| Language: | English |
| Published: |
2010
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| Online Access: | http://umpir.ump.edu.my/id/eprint/1391/1/Optimization%20of%20electrical%20discharge%20machine%20on%20mild%20steel%20AISI%201020%20by%20using%20grey%20relational%20analysis.pdf |
| _version_ | 1825821113865732096 |
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| author | Abdul Rahim, Asas |
| author_facet | Abdul Rahim, Asas |
| author_sort | Abdul Rahim, Asas |
| collection | UMP |
| description | This report deals with machining workpiece mild steel AISI 1020 using electrical discharge machining (EDM). The objective of this thesis is to optimize the surface roughness (SR), electrode wear ratio (EWR) and material removal rate (MRR) by using grey relational analysis (GRA) with orthogonal array (OA) and to discuss on the significant result by using analysis of variance (ANOVA). The machining of mild steel AISI 1020 steel workpiece was perform using the EDM machine AQ55L (ATC) and the analysis done using equation for GRA and STATISTICA software for ANOVA. In this study, the machining parameters, namely workpiece polarity, pulse off time, pulse on time, peak current, servo voltage and dielectric fluid are optimized. A grey relational grade obtained from the grey relational analysis is used to solve the EDM process with the multiple performance characteristics. Optimal machining parameters can then be determined by the grey relational grade as the performance index. Based from the result, the most significant parameter that effect the MRR, EWR and SR was the peak current while significant parameter was workpiece polarity. Experimental results have shown that machining performance in the EDM process can be improved effectively through this approach |
| first_indexed | 2024-03-06T11:36:39Z |
| format | Undergraduates Project Papers |
| id | UMPir1391 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T11:36:39Z |
| publishDate | 2010 |
| record_format | dspace |
| spelling | UMPir13912023-10-19T06:26:41Z http://umpir.ump.edu.my/id/eprint/1391/ Optimization of electrical discharge machine on mild steel AISI 1020 by using grey relational analysis Abdul Rahim, Asas TJ Mechanical engineering and machinery This report deals with machining workpiece mild steel AISI 1020 using electrical discharge machining (EDM). The objective of this thesis is to optimize the surface roughness (SR), electrode wear ratio (EWR) and material removal rate (MRR) by using grey relational analysis (GRA) with orthogonal array (OA) and to discuss on the significant result by using analysis of variance (ANOVA). The machining of mild steel AISI 1020 steel workpiece was perform using the EDM machine AQ55L (ATC) and the analysis done using equation for GRA and STATISTICA software for ANOVA. In this study, the machining parameters, namely workpiece polarity, pulse off time, pulse on time, peak current, servo voltage and dielectric fluid are optimized. A grey relational grade obtained from the grey relational analysis is used to solve the EDM process with the multiple performance characteristics. Optimal machining parameters can then be determined by the grey relational grade as the performance index. Based from the result, the most significant parameter that effect the MRR, EWR and SR was the peak current while significant parameter was workpiece polarity. Experimental results have shown that machining performance in the EDM process can be improved effectively through this approach 2010-12 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/1391/1/Optimization%20of%20electrical%20discharge%20machine%20on%20mild%20steel%20AISI%201020%20by%20using%20grey%20relational%20analysis.pdf Abdul Rahim, Asas (2010) Optimization of electrical discharge machine on mild steel AISI 1020 by using grey relational analysis. Faculty of Mechanical Engineering, Universiti Malaysia Pahang. |
| spellingShingle | TJ Mechanical engineering and machinery Abdul Rahim, Asas Optimization of electrical discharge machine on mild steel AISI 1020 by using grey relational analysis |
| title | Optimization of electrical discharge machine on mild steel AISI 1020 by using grey relational analysis |
| title_full | Optimization of electrical discharge machine on mild steel AISI 1020 by using grey relational analysis |
| title_fullStr | Optimization of electrical discharge machine on mild steel AISI 1020 by using grey relational analysis |
| title_full_unstemmed | Optimization of electrical discharge machine on mild steel AISI 1020 by using grey relational analysis |
| title_short | Optimization of electrical discharge machine on mild steel AISI 1020 by using grey relational analysis |
| title_sort | optimization of electrical discharge machine on mild steel aisi 1020 by using grey relational analysis |
| topic | TJ Mechanical engineering and machinery |
| url | http://umpir.ump.edu.my/id/eprint/1391/1/Optimization%20of%20electrical%20discharge%20machine%20on%20mild%20steel%20AISI%201020%20by%20using%20grey%20relational%20analysis.pdf |
| work_keys_str_mv | AT abdulrahimasas optimizationofelectricaldischargemachineonmildsteelaisi1020byusinggreyrelationalanalysis |