A study of Taguchi optimization method for identifying optimum surface roughness in CNC face milling of cobalt-based alloy (stellite 6)

Bagci, Eyup; Aykut, Şeref

doi:10.1007/s00170-005-2616-y

Cited by 117 publications

(56 citation statements)

References 12 publications

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“…Davim has studied the difference between processing conditions of turn bench and surface roughness formation of glass-fiber-reinforced and non-reinforced PA66 polyamide materials. In some studies, the processing of rough metals, such as cobalt alloy, and change in their cutting parameters are analyzed or optimized by using techniques such as the Taguchi method on the experimental results of Bagci, E et al & Aykut, S et al [1,2]. The observation of surface roughness values by using optimization methods and predictions based on artificial mind techniques can be made.…”

Section: Literature Surveymentioning

confidence: 99%

Optimization Technique For Surface Roughness Prediction in Turning Operation

Ojha¹,

Yadav²,

Yadav

2015

SIJSMS

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Section: Literature Surveymentioning

confidence: 99%

Optimization Technique For Surface Roughness Prediction in Turning Operation

Ojha¹,

Yadav²,

Yadav

2015

SIJSMS

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“…With the highest speed, lowest feed rate and highest radial rake angle of the cutting conditions scale, the GA technique recommends the best minimum surface roughness value. For end milling also, to modeling surface roughness different tools are used like RSM (Alauddin et al 1996;Mansour and Abdalla 2002;Wang and Chang 2004;Oktem et al 2005;Reddy and Rao 2005;Reddy and Rao 2006b;Routara et al 2009), Taguchi analysis (Yang and Chen 2001;Lin 2002;Ghani et al 2004;Bagci and Aykut 2006), ANN (Tsai et al 1999;Balic and Korosec 2002;Benardos and Vosniakos 2002;El-Sonbaty et al 2008;Öktem 2009;Zain et al 2010b). From the literature survey, it is seen that most of literatures deal with conventional roughness parameters to describe surface roughness and also in the study, three machining parameters viz.…”

Section: Review Of Roughness Study In Machiningmentioning

confidence: 99%

“…From the literature survey, it is seen that most of literatures deal with conventional roughness parameters to describe surface roughness and also in the study, three machining parameters viz. spindle speed, feed rate and depth of cut are the most common machining parameters (Fuh and Wu 1995;Lou et al 1998;Tsai et al 1999;Yang and Chen 2001;Lin 2002;Ghani et al 2004;Wang and Chang 2004;Bagci and Aykut 2006;Zhang and Chen 2007;Routara et al 2009). …”

Section: Review Of Roughness Study In Machiningmentioning

confidence: 99%

Fundamental Consideration

Sahoo¹,

Barman²,

Davim³

2011

Fractal Analysis in Machining

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The importance and usefulness of fractal dimension in describing surface roughness over the conventional roughness parameters are presented in this chapter. The fundamental of fractal dimension and the methodology for evaluation of fractal dimension are also discussed. Literature survey is carried out for four different types of machining processes and shows that there is scarcity of literatures which deal with fractal description of surface roughness. Fundamentals of design of experiments and response surface methodology are also discussed. IntroductionSurfaces are irregular though they may look like very smooth. When the surfaces are magnified, the irregularities become prominent. This is true for the machining surfaces as well. In a material removal process such as machining, unwanted material is removed and altered surface topography is obtained. The surface generated consists of inherent irregularities left by the cutting tool, which are commonly defined as surface roughness. Such a surface is composed of a large number of length scales of superimposed roughness that are generally characterized by the standard deviation of surface peaks. Three statistical characteristics are generally used to describe the structure of machined surface topography: texture, waviness and roughness. The texture determines the anisotropic property of the surface. The waviness reflects the reference profile (or surface). The surface roughness is formed by the micro deformation during the machining process.Surface roughness plays an important role. It has large impact on the mechanical properties like fatigue behavior, corrosion resistance, creep life, etc.It also affects other functional attributes of machine components like friction, wear, light reflection, heat transmission, lubrication, electrical conductivity, etc. Surface roughness may depend on various factors like machining parameters, work-piece materials, cutting tool properties, cutting phenomenon, etc. In a review P. Sahoo et al.,

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“…A large number of experimental works have to be carried out when the number of the process parameters increases. To solve this problem, the Taguchi method uses a special design of orthogonal arrays to study the entire parameter space with only a small number of experiments [6]. This study will utilize the Taguchi Design methodology.…”

Section: Introductionmentioning

confidence: 99%

Investigation on Influence of Speed, Feed and DOC on Surface Roughness in Turning of EN-24 and EN-31 under Dry and Wet Conditions

Katgeri¹

2014

IJIRSET

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ABSTRACT:The objective of this study is to develop a better understanding of the effects of spindle speed, cutting feed rate and depth of cut on the surface roughness and to build a suitable mathematical model. Such an understanding can provide insight into the problems of controlling the finish of machined surfaces when the process parameters are adjusted to obtain a certain responses like surface finish and power consumption. Also, the demand for high quality and fully automated production focuses attention on the surface condition of the product, especially the roughness of the machined surface, because of its effect on product appearance, function, and reliability. For these reasons it is important to maintain consistent tolerances and surface finish. Also, the quality of the machined surface is useful in diagnosing the stability of the machining process, power consumption, MRR, progressive tool wear, cutting tool chatter, etc.

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A study of Taguchi optimization method for identifying optimum surface roughness in CNC face milling of cobalt-based alloy (stellite 6)

Cited by 117 publications

References 12 publications

Optimization Technique For Surface Roughness Prediction in Turning Operation

Optimization Technique For Surface Roughness Prediction in Turning Operation

Fundamental Consideration

Investigation on Influence of Speed, Feed and DOC on Surface Roughness in Turning of EN-24 and EN-31 under Dry and Wet Conditions

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