Zapisane w:
| Główni autorzy: | , , , |
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| Format: | Recurso digital |
| Język: | |
| Wydane: |
Zenodo
2025
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| Hasła przedmiotowe: | |
| Dostęp online: | https://doi.org/10.5281/zenodo.14923987 |
| Etykiety: |
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Spis treści:
- <p><em><span>This study presents an empirical approach to estimate the coefficients of cutting force in turning processes. Cutting forces play crucial role in machining, affecting tool life, surface finish and overall productivity. Accurate estimation of cutting force coefficients is essential for optimizing machining parameters. Using experimental data from turning operation on AISI 1045 (steel) a regression model was developed to predict cutting force coefficients. A design matrix was constructed by applying the CCD. Response Surface Methodology (RSM) in design expert software was used to run the regression model. Analysis of Variance (ANOVA) was used to determine the significance of the model and its parameters. The results showed that cutting speed, feed rate, and depth of cut significantly influence cutting force. The result also revealed 8.68, 10.87 and 10.12 are the coefficients of cutting speed, feed rate and depth of cut respectively. Also, high R<sup>2</sup> value of 0.8337 of the plot of predicted and actual values indicates the model can accurately predict cutting force with low values of variance inflation factors (VIFs) between 1.0 – 1.02 (less than 10). The proposed empirical model provides a practical tool for cutting force coefficients, enabling machinists to optimize turning process parameters for improved efficiency and productivity.</span></em></p>