Optimization of electrical discharge machining parameters of SiSiC through response surface methodology
In recent years, researchers have demonstrated increases interest in studies involving silicon carbide (SiC) materials due to several industrial applications. Extreme hardness and high brittleness properties of SiC make the machining of such material very difficult, time consuming and costly. Electr...
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| Format: | Article |
| Language: | English |
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Penerbit UTM Press
2017
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| Online Access: | http://eprints.utm.my/76764/1/AhmadMajdiAbdul2017_OptimizationofElectricalDischargeMachining.pdf |
| _version_ | 1796862568003796992 |
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| author | Aliyu, A. A. A. Rohani, J. M. Rani, A. M. A. Musa, H. |
| author_facet | Aliyu, A. A. A. Rohani, J. M. Rani, A. M. A. Musa, H. |
| author_sort | Aliyu, A. A. A. |
| collection | ePrints |
| description | In recent years, researchers have demonstrated increases interest in studies involving silicon carbide (SiC) materials due to several industrial applications. Extreme hardness and high brittleness properties of SiC make the machining of such material very difficult, time consuming and costly. Electrical discharge machining (EDM) has been regarded as the most viable method for the machining of SiC. The mechanism of EDM process is complex. Researchers have acknowledged a challenge in generating a model that accurately describes the correlation between the input parameters and the responses. This paper reports the study on parametric optimization of siliconized silicon carbide (SiSiC) for the following quality responses; material removal rate (MRR), tool wear ratio (TWR) and surface roughness (Ra). The experiments were planned using Face centered central composite design. The models which related MRR, TWR and Ra with the most significant factors such as discharge current (Ip), pulse-on time (Ton), and servo voltage (Sv) were developed. In order to develop, improve and optimize the models response surface methodology (RSM) was used. Non-linear models were proposed for MRR and Ra while linear model was proposed for TWR. The margin of error between predicted and experimental values of MRR, TWR and Ra are found within 6.7, 5.6 and 2.5% respectively. Thus, the excellent reproducibility of this experimental study is confirmed, and the models developed for MRR, TWR and Ra are justified to be valid by the confirmation tests. |
| first_indexed | 2024-03-05T20:13:35Z |
| format | Article |
| id | utm.eprints-76764 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T20:13:35Z |
| publishDate | 2017 |
| publisher | Penerbit UTM Press |
| record_format | dspace |
| spelling | utm.eprints-767642018-05-31T09:28:03Z http://eprints.utm.my/76764/ Optimization of electrical discharge machining parameters of SiSiC through response surface methodology Aliyu, A. A. A. Rohani, J. M. Rani, A. M. A. Musa, H. TJ Mechanical engineering and machinery In recent years, researchers have demonstrated increases interest in studies involving silicon carbide (SiC) materials due to several industrial applications. Extreme hardness and high brittleness properties of SiC make the machining of such material very difficult, time consuming and costly. Electrical discharge machining (EDM) has been regarded as the most viable method for the machining of SiC. The mechanism of EDM process is complex. Researchers have acknowledged a challenge in generating a model that accurately describes the correlation between the input parameters and the responses. This paper reports the study on parametric optimization of siliconized silicon carbide (SiSiC) for the following quality responses; material removal rate (MRR), tool wear ratio (TWR) and surface roughness (Ra). The experiments were planned using Face centered central composite design. The models which related MRR, TWR and Ra with the most significant factors such as discharge current (Ip), pulse-on time (Ton), and servo voltage (Sv) were developed. In order to develop, improve and optimize the models response surface methodology (RSM) was used. Non-linear models were proposed for MRR and Ra while linear model was proposed for TWR. The margin of error between predicted and experimental values of MRR, TWR and Ra are found within 6.7, 5.6 and 2.5% respectively. Thus, the excellent reproducibility of this experimental study is confirmed, and the models developed for MRR, TWR and Ra are justified to be valid by the confirmation tests. Penerbit UTM Press 2017 Article PeerReviewed application/pdf en http://eprints.utm.my/76764/1/AhmadMajdiAbdul2017_OptimizationofElectricalDischargeMachining.pdf Aliyu, A. A. A. and Rohani, J. M. and Rani, A. M. A. and Musa, H. (2017) Optimization of electrical discharge machining parameters of SiSiC through response surface methodology. Jurnal Teknologi, 79 (1). pp. 119-129. ISSN 0127-9696 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85008146353&doi=10.11113%2fjt.v79.7622&partnerID=40&md5=40149e0211b403899aa2889d839d8b9a DOI:10.11113/jt.v79.7622 |
| spellingShingle | TJ Mechanical engineering and machinery Aliyu, A. A. A. Rohani, J. M. Rani, A. M. A. Musa, H. Optimization of electrical discharge machining parameters of SiSiC through response surface methodology |
| title | Optimization of electrical discharge machining parameters of SiSiC through response surface methodology |
| title_full | Optimization of electrical discharge machining parameters of SiSiC through response surface methodology |
| title_fullStr | Optimization of electrical discharge machining parameters of SiSiC through response surface methodology |
| title_full_unstemmed | Optimization of electrical discharge machining parameters of SiSiC through response surface methodology |
| title_short | Optimization of electrical discharge machining parameters of SiSiC through response surface methodology |
| title_sort | optimization of electrical discharge machining parameters of sisic through response surface methodology |
| topic | TJ Mechanical engineering and machinery |
| url | http://eprints.utm.my/76764/1/AhmadMajdiAbdul2017_OptimizationofElectricalDischargeMachining.pdf |
| work_keys_str_mv | AT aliyuaaa optimizationofelectricaldischargemachiningparametersofsisicthroughresponsesurfacemethodology AT rohanijm optimizationofelectricaldischargemachiningparametersofsisicthroughresponsesurfacemethodology AT raniama optimizationofelectricaldischargemachiningparametersofsisicthroughresponsesurfacemethodology AT musah optimizationofelectricaldischargemachiningparametersofsisicthroughresponsesurfacemethodology |