Abstract:The present study investigated the effects of the control factors of cutting speed, feed rate and depth of cut on the response variables of cutting force (Fc) and surface roughness (Ra) in the dry turning of 15-5 PH martensitic stainless steel. Using PVD TiAlN-AlCrO-and CVD TiCN-Al2O3-TiN-coated carbide-cutting-tool inserts, a number of turning experiments were conducted via the L18 (2 1 ×3 3 ) Taguchi mixed orthogonal array. The machining parameters were optimized using signal-to-noise ratio (S/N) and analysi… Show more
“…(S/N) the ratio has been calculated according to Taguchi's (Smaller-The-Better) approach which aims to minimize Surface Roughness according to Eq. (1) [13]. Table III shows Taguchi orthogonal L 16 Array and Experimental Results.…”
Section: Taguchi Approach and Experimental Design Methodsmentioning
In this paper, Analysis Of Variance (ANOVA), Artificial Neural Network (ANN), and Genetic Algorithm (GA) have been studied to predict the effect of milling parameters on the Surface Roughness (Ra) during machining of mild steel alloy. The milling experiments carried out based on the Taguchi design of experiments method using (L16) orthogonal array with 3 factors and 4 levels. The influence of three independent variables such as spindle speed (910, 930, 960, and 1000 rpm), feed rate (93, 95, 98, and 102 mm/min), and Tool Diameter (8, 10, 12, and 14 mm) on the Surface Roughness (Ra) were tested and analyzed with (ANOVA) to predict the response which indicates that spindle speed was the most significant factor effecting on Surface Roughness (Ra). Artificial Neural Network (ANN) and numerical methods are used widely for modeling and predict the performance of manufacturing technologies. Neural Network technique with 2 hidden layers, 10 neurons size, 1000 epochs, and Trainlm transfer function is used to predict the result. The Genetic Algorithm (GA) has been utilized to find optimal cutting conditions during a milling process.
From the results, the optimal value of spindle speed is (930 rpm), feed-rate is (95 mm/min) and tool diameter is (8 mm). This network structure is capable of predicting the Surface Roughness (Ra) well to optimize the milling parameters. Artificial Neural Network (ANN) predicted results indicate good agreement between the experimental and the predicted values.
“…(S/N) the ratio has been calculated according to Taguchi's (Smaller-The-Better) approach which aims to minimize Surface Roughness according to Eq. (1) [13]. Table III shows Taguchi orthogonal L 16 Array and Experimental Results.…”
Section: Taguchi Approach and Experimental Design Methodsmentioning
In this paper, Analysis Of Variance (ANOVA), Artificial Neural Network (ANN), and Genetic Algorithm (GA) have been studied to predict the effect of milling parameters on the Surface Roughness (Ra) during machining of mild steel alloy. The milling experiments carried out based on the Taguchi design of experiments method using (L16) orthogonal array with 3 factors and 4 levels. The influence of three independent variables such as spindle speed (910, 930, 960, and 1000 rpm), feed rate (93, 95, 98, and 102 mm/min), and Tool Diameter (8, 10, 12, and 14 mm) on the Surface Roughness (Ra) were tested and analyzed with (ANOVA) to predict the response which indicates that spindle speed was the most significant factor effecting on Surface Roughness (Ra). Artificial Neural Network (ANN) and numerical methods are used widely for modeling and predict the performance of manufacturing technologies. Neural Network technique with 2 hidden layers, 10 neurons size, 1000 epochs, and Trainlm transfer function is used to predict the result. The Genetic Algorithm (GA) has been utilized to find optimal cutting conditions during a milling process.
From the results, the optimal value of spindle speed is (930 rpm), feed-rate is (95 mm/min) and tool diameter is (8 mm). This network structure is capable of predicting the Surface Roughness (Ra) well to optimize the milling parameters. Artificial Neural Network (ANN) predicted results indicate good agreement between the experimental and the predicted values.
“…Among the authors whose works in the field of material removal must be mentioned and who made a significant contribution in the introduction of new methods of optimization, the Taguchi methods are the papers from the group [9][10][11][12]. In these works, the authors perform optimization of parameters in order to minimize the output characteristics of the cutting process.…”
This paper examines the influence of the cutting parameters on the cutting forces and the surface roughness at the face milling process when machining aluminum alloy 7075 is obtained by the new SSM casting process. The parameters of the milling process are the cutting speed, the feed per tooth and the depth of cut. The experiments were performed according to the Taguchi method according to the L9 plan and the factors varied at three levels. For analysis of the effects of these parameters S/N ratio is used. In addition, ANOVA analysis was performed, i.e. analysis of the variance of the selected parameters. The analysis of the results shows that the optimal combination for the cutting force is the choice of a minimum level for all tested parameters. In contrast, for average arithmetic roughness, the optimal processing regime is achieved with minimum values for cutting speed and feed per tooth, whilst it is preferable to choose the cutting depth at the median level for the observed range. In addition, the study shows that the Taguchi method is suitable for solving the problem, where the research was carried out with a minimum number of tests compared to a full factorial experimental plan.
“…Ancak belirli bir değerin üzerindeki kesme hızları takım aşınması meydana getireceğinden ötürü kesme kuvvetlerinde artışa sebep olacağı belirtilmiştir [15 ve 16]. Her iki kaplama türünde de ilerleme oranının ve kesme derinliğinin artırılmasıyla kesme kuvvetlerinin arttığı vurgulanmıştır [14][15][16][17]. Yapılan çalışmalar incelendiğinde, genel olarak CVD kaplamalı takımların bu malzemelerin işlenmesinde kullanıldığı görülmektedir.…”
Section: Introductionunclassified
“…Genel olarak literatür incelendiğinde, PVD ve CVD kaplamalı takımlar ile işleme esnasında kesme hızının artışı ile kesme kuvvetlerinde azalma olduğu belirtilmiştir [13][14][15]. İşleme verimliğinin artırılması için kesme hızının artışının önemi araştırmacılar tarafından vurgulanmıştır.…”
Çökelme sertleşmesi ile yaşlandırılmış paslanmaz çelikler, diğer paslanmaz çelik türlerine göre daha üstün özelliklere sahiptir. Bu üstün özeliklerin en önemlileri mekanik ve termal özelliklerdir. 17-4 PH paslanmaz çeliği; nükleer endüstriden havacılık endüstrisine kadar birçok alanda tercih edilmektedir. Bu çalışmada, 17-4 PH paslanmaz çeliğinin farklı kaplama türlerine sahip kesici takımlar ile işlenmesi sırasında, işleme parametrelerinin esas kesme ve ilerleme kuvvetlerine olan etkileri incelenmiştir. İşlenebilirlik çalışmaları, CNC torna tezgahında gerçekleştirilmiş olup, dörder farklı kesme hızı, ilerleme oranı ve kesme derinliği işleme parametreleri olarak belirlenmiştir. Kesici takım olarak aynı geometriye sahip, PVD ve CVD kaplamalı takımlar kullanılmıştır. Deneylerin uygulanması için seçilmiş değişkenlere Taguchi L16 ortogonal dizini uygulanarak deney sayısı en aza indirgenmiştir. Elde edilen sonuçların etkili bir biçimde yorumlanması, esas kesme ve ilerleme kuvvetleri açısından en etkin parametrelerin belirlenmesi için varyans analizi (ANOVA) uygulanmıştır. Yapılan deneysel çalışmaların sonucunda 17-4 PH paslanmaz çelikleri için esas kesme ve ilerleme kuvvetleri açısından optimum kesme parametrelerinin tayini gerçekleştirilmiştir. Sonuç olarak, her iki kaplama türünde ilerleme oranı ve kesme derinliği esas kesme ve ilerleme kuvveti değerlerinde artışa neden olmuştur. Kesme hızının artışı ile her iki kaplama türünde de esas kesme kuvveti değerlerinde %8,05 ile %25,24 arasında azalma görülmüştür. Ancak PVD kaplamalı takımlarda artan kesme hızı ile ilerleme kuvveti değerlerinde %0,97 ile %3,18 arasında azalma, CVD kaplamalı takımlarda ise %2,78 ile %7,11 arasında artış olduğu belirlenmiştir.
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