Zaina, Nurezayana and Mohd Zain, Azlan and A. Aziz, Mohamad Firdaus and A. Mostafa, Salama and Mat Deris, Ashanira and Abd Warif, Nor and S. Shahrom, Muhammad Ammar (2024) Multiple Polynomial Regression Model for Predicting Surface Roughness of Titanium Alloy in Electrical Discharge Machining. Fusion: Practice and Applications, 15 (2). pp. 165-172.
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Abstract
This study investigated the experimental work of titanium alloy in the die-sinking electrical discharge (EDM) machining process to enhance surface integrity (surface roughness) by applying regression-based modeling. Furthermore, a multiple polynomial regression (MPR) model was developed to predict surface roughness responses under optimized conditions. The effects of EDM parameters, such as pulse-on time (ON), pulse-off time (OFF), peak current (IP), and servo voltage (SV), on surface roughness were studied. The experiment was conducted using a two-level full factorial design with four center points. Roughness was measured using a surface roughness tester (Formtracer SJ-301). The significant cutting parameters for surface roughness were determined using analysis of variance (ANOVA). The results showed that increasing the servo voltage significantly reduced the surface roughness by 46.48%. The developed model also predicted surface roughness values lower than those observed in the experimental data, with an R2 value of 0.608.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Regression; Polynomial Regression; Surface roughness; Electrical discharge machining; titanium alloy. |
| Subjects: | T Technology > TJ Mechanical engineering and machinery |
| Divisions: | Faculty of Computer Science and Information Technology > FSKTM |
| Depositing User: | Mr. Mohamad Zulkhibri Rahmad |
| Date Deposited: | 19 Mar 2025 00:23 |
| Last Modified: | 19 Mar 2025 00:23 |
| URI: | http://eprints.uthm.edu.my/id/eprint/12557 |
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