Investigation of Power Consumption in the Machining of S960QL Steel by Finite Elements Method
Abstract
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References
- Kant, G. and Sangwan, K. S., Prediction and optimization of machining parameters for minimizing power consumption and surface roughness in machining, Journal of Cleaner Production, (2014), 83 pp. 151-164.
- Sangwan, K. S., Development of a multi criteria decision model for justification of green manufacturing systems, Int. J. Green. Econ., (2011), no. 5, pp. 285-305.
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- Korkmaz, M. E. and Günay, M., Finite Element Modelling of Cutting Forces and Power Consumption, Arabian Journal for Science and Engineering, 43, (2018), pp. 4863-4870.
- Composeco-Negrete, C., Optimization of cutting parameters for minimizing energy consumption in turning of AISI 6061 T6 using Taguchi methodology and ANOVA, J. Clean. Prod., 53, (2013), pp. 195-203.
- Black, J. T. and Kohser, R. A., DeGarmo’s Materials and Processes in Manufacturing, 11th edition, John Wiley&Sons, Hoboken, 2013.
- Coşkun, M., Çiftçi, İ. and Demir, H., AISI P20S Kalıp Çeliğinin İşlenebilirliğinin İncelenmesi, İmalat Teknolojileri ve Uygulamaları, 2, (2021), 2, pp. 1-9.
- Uzun, M., Usca, Ü. A., Kuntoğlu, M. and Gupta, M. K., Influence of tool path strategies on machining time, tool wear, and surface roughness during milling of AISI X210Cr12 steel, The International Journal of Advanced Manufacturing Technology, (2022), pp. 1-12.
Details
Primary Language
English
Subjects
Mechanical Engineering
Journal Section
Research Article
Authors
Rüstem Binali
*
0000-0003-0775-3817
Türkiye
Süleyman Yaldız
0000-0003-0931-9643
Türkiye
Süleyman Neşeli
0000-0003-1553-581X
Türkiye
Publication Date
June 30, 2022
Submission Date
February 1, 2022
Acceptance Date
March 28, 2022
Published in Issue
Year 2022 Volume: 12 Number: 1
Cited By
Evaluation of Machining Parameters Affecting Cutting Forces in Dry Turning of GGG50 Ductile Cast Iron
Türk Doğa ve Fen Dergisi
https://doi.org/10.46810/tdfd.1210013İşlenmesi Zor Malzemelerin Tornalanması İçin En Uygun İşleme Sıcaklıklarının Makine Öğrenmesi İle Belirlenmesi
İmalat Teknolojileri ve Uygulamaları
https://doi.org/10.52795/mateca.1463257Machining of AISI 52100 Steel: Statistical Insights into Dry Environment with Variable Tool Nose Radius
Doğu Fen Bilimleri Dergisi
https://doi.org/10.57244/dfbd.1708389Statistical Investigation of Power Consumption in Dry Turning of Stir-Cast Al7075-SiC-Gr Metal Matrix Composites
Materials Science Forum
https://doi.org/10.4028/p-4ejiGLA machine learning based approach for investigation of dry and MQL environments while turning stainless steels
İmalat Teknolojileri ve Uygulamaları
https://doi.org/10.52795/mateca.1870698
