Alüminyum 6061 T651 alaşımının delme işleminde kesme parametrelerinin optimizasyonu = Optimization of cutting parameters during drilling ofaluminum 6061 T651 alloy

Abstract

Alüminyum ve alaşımları son yüzyılda büyük bir popülerlik kazanmış ve kullanımları hızla artmıştır. Alüminyum, diğer demir esaslı metallere göre çok daha kolay şekil verilebilen, üç kat daha az ağırlığa ve korozyon direncine sahip bir malzemedir. Bu özellikleri nedeniyle kullanım alanları çok çeşitlenmiştir. Bu artan kullanım, alüminyum alaşımları üzerinde çalışmaların artmasına ve alaşım kompozisyonlarının araştırılmasının önünü açmıştır. Delme, tüm işleme işlemleri arasında en yaygın kullanılan yöntemdir ve metal işleme operasyonlarının yaklaşık %25-33'ünü oluşturur. Delme, mekanik bileşenlerin ve yapıların montajında genellikle en iyi seçenek olan çok önemli bir işlemdir. Bu çalışmanın amacı alüminyum 6061 T651 alaşımının delme işlemi sırasındaki kesme parametrelerinin optimize değerlerini tespit etmektir. Kesme parametreleri soğutma yöntemi, ilerleme miktarı ve kesme hızı olarak belirlenmiştir. Kesme hızı olarak (75,95,115) m/dk, ilerleme hızı olarak (0,5/0,7/0,9) mm/diş ve soğutma yöntemi olarak kuru soğutma, hava soğutma, sıvı soğutma seçilmiştir. Deney tasarımı Taguchi L27(3^3) sistemine göre yapılmıştır. Deneyde 8 mm çapında HSSE-Co5 yüksek hız çeliğinden yapılmış matkap kullanılmıştır. Deneyler TAKSAN TMC-700V dik işleme merkezinde yapılmıştır. NI xDAQ-9188 veri toplama ünitesinden alınan veriler FlexLogger yazılımı ile işlenmiştir. Alınan verilerdeki gereksiz gürültüler excel yazılında üstel düzeltme yöntemi uygulanarak minimize edilmiştir. Minitab 19 programı ile elde edilen veriler işlenerek varyans analizleri, regresyon analizleri ve Taguchi optimizasyonları yapılmıştır. En optimize değeri bulabilmek için ise yanıt yüzey metodu yöntemi kullanılmıştır. Varyans analizi sonuçları incelendiğinde kesme hızı parametresinin kesme kuvveti üzerindeki etkisi %38,8'dir. Bu değer parametreler arasındaki en etkili değerdir. Diş başı ilerleme miktarının etki oranı %28,57, soğutma yönteminin etki oranı ise %24,46 olarak tespit edilmiştir. Varyans analizi sonuçlarına göre hata etki oranı %8,19'dur. Bu çalışmanın sonucunda farklı soğutma yöntemleri ile yapılan deneylerde; kesme hızı parametresinin optimize edilmiş değeri 75 m/dk olarak, diş başı ilerleme miktarı optimize edilmiş değeri 0,05 mm/diş, soğutma yönteminin optimize edilmiş değeri ise sıvı soğutma olduğu yanıt yüzey yöntemi ile belirlenmiştir.

Aluminum and aluminum alloys have gained significant popularity in the last century, and their use has rapidly increased. Aluminum is a material that can be easily shaped compared to other iron-based metals, with one-third the weight and excellent corrosion resistance. Due to these properties, its applications have significantly diversified. The growing usage has led to increased research on aluminum alloys and exploration of alloy compositions. Among all machining processes, drilling is most widely used method, constituting approximately 25-33% of metal machining operations. Drilling is a crucial operation, often the best choice, in assembling mechanical components and structures. Optimizing drilling parameters, such as cutting forces, can be achieved through various approaches, including theoretical calculations, experimental methods, and computer-aided finite element analysis. A literature review reveals that the experimental method is more prevalent than other techniques, and the accuracy of alternative methods is often evaluated by comparing their results to experimental data. This prevalence of the experimental method is attributed to its ability to provide more precise results, as it closely simulates real-world processing conditions compared to theoretical or computer-based methods. In all engineering disciplines, ensuring a safe working environment and achieving long-lasting, high-quality, and cost-effective products and systems require accurately and precisely measuring all forces affecting cutting tools and machinery. While theoretical stress values are established, they often do not align with the values obtained in practical applications. Therefore, it is essential to experimentally analyze and measure these forces. Aluminum 6061-T651 is a popular material for structural and aerospace applications due to its excellent strength-to-weight ratio, good machinability, and high corrosion resistance. However, drilling this material can be challenging due to its low thermal conductivity, high ductility, and susceptibility to hardening. Researchers have investigated the optimization of drilling parameters, including cutting speed, cooling methods, feed rate, and drill bit geometry, to enhance the efficiency and quality of the drilling process. This study aims to find the optimized cutting parameters during the drilling process of aluminum 6061-T651 alloy. The cutting parameters selected include cutting speed, feed rate, and cooling method. Cutting speeds of (75, 95, 115) m/min, feed rates of (0.5, 0.7, 0.9) mm/rev, and cooling methods such as dry, air, and liquid were chosen. The experimental design was conducted based on the Taguchi L27(3^3) system. An 8 mm diameter HSSE-Co5 high-speed steel drill bit was used in the experiments, which were carried out on a TAKSAN TMC-700V vertical machining center. Data collected from the NI xDAQ-9188 data acquisition unit were processed using the FlexLogger software. Unnecessary noise in the collected data was minimized using the exponential correction method in Microsoft Excel. Data obtained from Minitab 19 software were subjected to variance analysis, regression analysis, and Taguchi optimizations. To find the most optimized value, the response surface methodology was employed. Utilizing the maximum cutting force values, a series of optimization techniques, including Taguchi optimization, analysis of variance (ANOVA), and regression analysis, were applied to reduce the cutting forces. Nonetheless, it was observed that solely minimizing the maximum cutting force increased production time. Given that an increase in manufacturing time could adversely affect operational costs, multiple response optimizations, explicitly employing the response surface methodology, were conducted. These optimizations aimed to collectively minimize the maximum cutting force. All statistical analyses were carried out using Minitab 19 software. In Taguchi optimization, the selection of the optimal parameter levels is based on an assessment of the experimental results. This assessment, referred to as the performance criterion, is conducted using a metric known as the signal-to-noise ratio (S/N). The specific equation employed for calculating the signal-to-noise ratio depends on the problem's objective. In the context of this study, where the aim is to minimize cutting forces, the signal-to-noise ratios were computed using the smaller-the-better type as the target. In the analysis of variance, the impact (effect ratio) of the experimental parameters on the respective outputs is assessed through an evaluation of the dependent variable results obtained in the experiments. The experimental parameters, whose effects on the outputs are identified, are then analyzed to provide insights for problem-solving. The mathematical models developed in regression analysis estimate the dependent variable output based on the independent variable inputs. The predictive accuracy of these mathematical models varies depending on the chosen regression model. The predictive capabilities of the constructed mathematical models can be understood by considering the coefficient of determination (R^2). As the value of R^2 increases, the predictive performance of the mathematical model improves. The Response Surface Method (RSM) is a widely employed technique in various scientific disciplines and across diverse industrial sectors. The response expression signifies the dependent variable under investigation. RSM is utilized to identify influential parameters affecting the response, ascertain optimal parameter settings for one or multiple responses, and establish mathematical models that elucidate the relationship between the response and independent variables. In alignment with these objectives, processes or issues can be optimized. The process of determining the optimal parameter settings for a response using RSM is referred to as response optimization. In instances where multiple responses are involved, the optimization conducted is termed multi-response optimization. When examining the results of the variance analysis, it is observed that the cutting speed parameter has the highest impact, accounting for 38.8% of the variation in cutting force. This value represents the most influential parameter among the studied factors. The feed rate effect ratio per tooth is 28.57%, while the cooling method has an effect ratio of 24.46%. The variance analysis results show that the error effect ratio is 8.19%. As a result of this study, through multi-response optimization, experiments with different cooling methods determined the optimized values for the cutting parameters as follows: a cutting speed of 75 m/min, a feed rate per tooth of 0.05 mm/rev, and the optimal cooling method being liquid cooling.