2 sonuçlar
Arama Sonuçları
Listeleniyor 1 - 2 / 2
Öğe Optimization and evaluation of dry and minimum quantity lubricating methods on machinability of AISI 4140 using Taguchi design and ANOVA(SAGE Journals, 2020-07-05) Gürbüz, Hüseyin; Gönülaçar, Yunus EmreIn this work, it is aimed to study the effects of dry machining and minimum quantity lubrication application on machinability in turning AISI 4140 steel by utilizing different cutting parameters. Also, this study contains effects and optimization of cutting conditions (dry and minimum quantity lubricating), feed rate, and cutting speed on surface roughness (Ra) and main cutting forces (Fc) determined by employing the Taguchi method. At the end of experiments, it was established that compared to dry machining operations, minimum quantity lubricating significantly reduced cutting tool wear, while Fc and Ra decreased in general. Analyses of variance, regression analysis, signal-to-noise ratio, and orthogonal array were employed to analyze the effects and contributions of independent variables on dependent variables. The optimum levels of the dependent variables for reducing Fc and Ra using signal-to-noise rates were established. According to signal-to-noise ratios, minimum quantity lubricating had a more important effect on Fc and Ra than dry machining. The optimal conditions for Fc and Ra were at 0.16 mm/rev feed rate, 125 m/min cutting speed at minimum quantity lubricating. Analysis of variance results demonstrated that the feed rate is the most influential independent variable on Fc (93.976 %) and Ra (89.352 %). Validation test results exhibited that the Taguchi method and regression analysis were highly achieved methods in the optimization of independent variables for dependent variables. Taguchi optimization technique and regression analysis obtained from Fc (R2Tag. = 0.972 and R2Rag. = 0.997) and Ra (R2Tag. = 0.985 and R2Rag. = 0.996) measurements match really well with the experimental dataÖğe Sine-cosine algorithm-based optimization for automatic voltage regulator system(SAGE, 2019-04-01) Hekimoğlu, BaranA novel design method, sine-cosine algorithm (SCA) is presented in this paper to determine optimum proportional-integral-derivative (PID) controller parameters of an automatic voltage regulator (AVR) system. The proposed approach is a simple yet effective algorithm that has balanced exploration and exploitation capabilities to search the solutions space effectively to find the best result. The simplicity of the algorithm provides fast and high-quality tuning of optimum PID controller parameters. The proposed SCA-PID controller is validated by using a time domain performance index. The proposed method was found efficient and robust in improving the transient response of AVR system compared with the PID controllers based on Ziegler-Nichols (ZN), differential evolution (DE), artificial bee colony (ABC) and bio-geography-based optimization (BBO) tuning methods.
