| Yazarlar (3) |
Dr. Öğr. Üyesi Erman ZURNACI
Kastamonu Üniversitesi, Türkiye |
Sabri Uzuner
Düzce Üniversitesi, Türkiye |
|
Engin Nas
Türkiye |
| Özet |
| Optimizing energy consumption in machining processes is critical for achieving sustainable manufacturing. This study introduces an Automation-Supported measurement approach that integrates a custom power analyzer with real-time data logging and visualization capabilities to accurately measure energy usage during CNC (computer numerical control) operations. Statistical comparisons were conducted using the independent samples t-test and Taguchi analysis to evaluate the effectiveness of the proposed method against traditional measurement techniques. The results revealed that there is a statistically significant difference (p < 0.05) in the current measurements across X, Z, and spindle motors between the proposed and conventional methods. The advanced method based on automation reduced the error rate in measuring spindle motor power consumption due to the selection of processing parameters from 34.17% to 2.7%. Additionally, Taguchi analysis demonstrated that the measurement method influenced the optimization of machining parameters, with S/N ratio improvements observed. These findings confirm that the proposed method enhances energy efficiency, reduces environmental impact, and supports sustainable manufacturing practices. |
| Anahtar Kelimeler |
| automation | energy consumption | energy efficiency | machining parameter optimization | measurement method |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | SSCI, AHCI, SCI, SCI-Exp dergilerinde yayımlanan tam makale |
| Dergi Adı | Machines |
| Dergi ISSN | 2075-1702 Wos Dergi Scopus Dergi |
| Dergi Tarandığı Indeksler | SCI-Expanded |
| Dergi Grubu | Q2 |
| Makale Dili | İngilizce |
| Basım Tarihi | 01-2025 |
| Cilt No | 13 |
| Sayı | 2 |
| Sayfalar | 1 / 20 |
| Doi Numarası | 10.3390/machines13020148 |
| Makale Linki | https://www.mdpi.com/2075-1702/13/2/148# |
| Atıf Sayıları |
