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    Comparison of Automation-Supported and Conventional Methods for Measuring Energy Consumption in Computer Numerical Control Machining
    (Mdpi, 2025) Zurnaci, Erman; Uzuner, Sabri; Nas, Engin
    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.
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    Investigation of wear and surface quality of raw AISI H13 hot work tool steel in electro-discharge machining machine
    (Sage Publications Inc, 2025) Nas, Engin; Zurnaci, Erman; Gueltekin, Sidika Yildirim
    Electrical discharge machining is a thermal erosion method that can be processed independently of the material's mechanical properties and the workpiece's geometry. Electrical discharge machining processing parameters directly affect the material's surface morphology and processing quality. This study investigated the effects of electrical discharge machining process parameters on the machining quality of AISI H13 hot work tool steel. Electrode material, pulse current and pulse on time were determined as factors for the experimental study. As a methodology, Taguchi L27 (3 x 3 x 3) full-factorial experimental design was used to optimise the effect of process parameters on surface roughness (Ra), processing time, crater diameter and material removal amount, which were identified as output parameters. The optimum factor levels were determined using Taguchi-based signal-to-noise ratio (S/N) criteria to optimise the output parameters. In addition, the analysis of variance results revealed that the pulse current was the most influential parameter for Ra, T and crater diameter. Conversely, the electrode material was the most noteworthy factor in material wear. The experimentation revealed that when the pulse current and pulse on time were increased, the processing time decreased, but the surface quality deteriorated. Moreover, linear and quadratic regression analyses were utilised to forecast the experiment's outcomes. The predicted and measured values exhibited excellent agreement.