Optimization of cutting parameters on drill bit temperature in drilling by Taguchi method

Çakıroğlu, Ramazan; Acır, Adem

doi:10.1016/j.measurement.2013.06.046

Cited by 70 publications

(29 citation statements)

References 14 publications

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“…System design, b. Parameter design, and c. Tolerance design. The parameter design is the most important stage [17]. According to the number of levels of the control factors, the most appropriate mixed orthogonal array L 18 (2 1 × 3 3 ) was selected for the present work.…”

Section: Taguchi Methods and Design Of Experimentsmentioning

confidence: 99%

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Optimization of Process Parameters During End Milling and Prediction of Work Piece Temperature Rise

Bhirud¹,

Gawande²

2017

Archive of Mechanical Engineering

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During the machining processes, heat gets generated as a result of plastic deformation of metal and friction along the tool-chip and tool-work piece interface. In materials having high thermal conductivity, like aluminium alloys, large amount of this heat is absorbed by the work piece. This results in the rise in the temperature of the work piece, which may lead to dimensional inaccuracies, surface damage and deformation. So, it is needed to control rise in the temperature of the work piece. This paper focuses on the measurement, analysis and prediction of work piece temperature rise during the dry end milling operation of Al 6063. The control factors used for experimentation were number of flutes, spindle speed, depth of cut and feed rate. The Taguchi method was employed for the planning of experimentation and L 18 orthogonal array was selected. The temperature rise of the work piece was measured with the help of K-type thermocouple embedded in the work piece. Signal to noise (S/N) ratio analysis was carried out using the lower-the-better quality characteristics. Depth of cut was identified as the most significant factor affecting the work piece temperature rise, followed by spindle speed. Analysis of variance (ANOVA) was employed to find out the significant parameters affecting the work piece temperature rise. ANOVA results were found to be in line with the S/N ratio analysis. Regression analysis was used for developing empirical equation of temperature rise. The temperature rise of the work piece was calculated using the regression equation and was found to be in good agreement with the measured values. Finally, confirmation tests were carried out to verify the results obtained. From the confirmation test it was found that the Taguchi method is an effective method to determine optimised parameters for minimization of work piece temperature.

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Section: Taguchi Methods and Design Of Experimentsmentioning

confidence: 99%

“…In the case of other machining operations, R. Çakiroğlu et al [17], have carried out experimentation for optimization of the cutting parameters for reducing the drill bit temperature during drilling of Al 7075 work piece. The cutting speed, feed rate and cutting tool (uncoated and coated carbide drills) were used as control factors.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Process Parameters During End Milling and Prediction of Work Piece Temperature Rise

Bhirud¹,

Gawande²

2017

Archive of Mechanical Engineering

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“…It is the first machining operation performed in hole cutting process. Drilling is a thermo-mechanical process in which heat is generated due to friction and plastic deformation of the work piece material so temperature at the cutting zone increases because of heat generation and accumulation [24]. Due to which the drilling process is rather familiar as a complex machining process for advance materials.…”

Section: B Parametric Optimization Of a Drilling Processmentioning

confidence: 99%

State-Of-The-Art Optimization Techniques for Complex Machining Processes: A Review

Trivedi¹

2017

IJRASET

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The main objective in machining operation is to produce a product with high quality and competitive price. Machining of advance materials is an important topic in current researchers on manufacturing processes. To determine an optimum cutting parameters is the prime requirement in the machinability study of super alloys. To improve quality of machined surface, the cutting tool must have its ability to retain severe cutting conditions all the times. To keep tool in a good condition, parametric optimization of spindle speed, feed rate, tool geometry is on the top priority. The industry has a demand of new materials like super alloys which are hard in nature and are difficult to machine. Effective machining without compromise product surface quality by specific manufacturing processes showed a new direction to the industrial world. Many conventional and unconventional manufacturing processes are used by the industrial sectors like marine, nuclear, petrochemical, aerospace, medical etc. These processes are having many process parameters and to select particular parameter is very critical task as it has considerable impact on process performance. As the process parameters are in large, random selection of parameters will not give desired output. If the desired objectives are in a large number, then it is very crucial situation. The advance optimization techniques can handle such situation effectively for process parametric optimization. In this paper, advance optimization techniques of parametric optimization for complex manufacturing processes have been discussed.

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“…Davim (2003) applied the Taguchi techniques to investigate the cutting characteristics of MMC (A356/20/SiCp-T6) using PCD cutting tools. On top of that, Abhang and Çakıroğlu (Abhang and Hameedullah, 2012;Çakıroğlu and Acır, 2013) applied the Taguchi method in optimization of machining parameters in steel turning operation and optimization of cutting parameters on drill bit temperature in drilling respectively.…”

Section: Taguchi Approachmentioning

confidence: 99%

Parameter Settings for New Generational Genetic Algorithms for Solving Global Optimization Problems

Lim¹,

Sulaiman²,

Mustapha³

et al. 2015

Journal of Computer Science

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This study operates within experimental design with two main tools of Taguchi method namely orthogonal array and signal to noise ratio to discover the optimal parameter settings for newly proposed generational genetic algorithms; they are Laplace Crossover-Scale Truncated Pareto Mutation (LX-STPM) and Rayleigh Crossover-Scale Truncated Pareto Mutation (RX-STPM). It concluded that GA parameter settings are algorithms and problems dependent.

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Optimization of cutting parameters on drill bit temperature in drilling by Taguchi method

Cited by 70 publications

References 14 publications

Optimization of Process Parameters During End Milling and Prediction of Work Piece Temperature Rise

Optimization of Process Parameters During End Milling and Prediction of Work Piece Temperature Rise

State-Of-The-Art Optimization Techniques for Complex Machining Processes: A Review

Parameter Settings for New Generational Genetic Algorithms for Solving Global Optimization Problems

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