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Experimental and response surface methodology investigation of cast material obtained by melting and recycling of chips

Yıl 2021, Cilt: 17 Sayı: 3, 267 - 273, 27.09.2021
https://doi.org/10.18466/cbayarfbe.898972

Öz

In this study, it is aimed to draw attention to the new materials and recycling produced by the melt-casting process of chips in industry. For this purpose, the aluminum 5000 series material with 90 HB hardness was turned. The chips obtained by turning were melted in our own melting furnace and molded as a cylinder. The hardness value of the material obtained by casting method was measured as 95 HB. Materials were examined by surface microscopy. Experimental design, analysis of surface roughness values of normal and cast material, regression equations, coefficients of determination, optimum point, cutting parameters interaction graphs were carried out with response surface methodology (RSM). It was concluded that the surface roughness values decreased in the casting material. In order to determine this reduction, the surfaces of the chips and materials were examined. In prediction experiments, it was observed that the RSM model yielded 90% reliability.

Destekleyen Kurum

Amasya University Scientific Research Projects Coordination Unit

Proje Numarası

FMB-BAP 18-0316

Teşekkür

This study was supported by Amasya University Scientific Research Projects Coordination Unit with the project of FMB-BAP 18-0316.

Kaynakça

  • Akbulut H., Içaga Y., Gürer C. 2003. The Possibility of Recycle of Waste Agregates in the Asphalt Pavement and CEN Standards. III National Kırmataş Symposium, 3-4.
  • Akar M. 2018. Casting errors and design methods for prevention, Pamukkale University Graduate School of Natural and Applied Sciences.
  • Cooper D. R., Song J., Gerard R. 2018. Metal recovery during melting of extruded machining chips. Journal of Cleaner Production; 200: 282-292.
  • Jirang C. U. I., Roven H. J. 2010. Recycling of automotive aluminum. Transactions of Nonferrous Metals Society of China; 20: 11: 2057-2063.
  • Martínez V.P., Torres J.T., Valdes A.F. 2017. Recycling of aluminum beverage cans for metallic foams manufacturing. Journal of Porous Materials; 24: 3: 707-712.
  • Gürbüz M. 2018. Effect of the cold working on mechanical properties of aluminum produced from waste beverage cans. Journal of Science and Engineering; 20: 58: 28-35.
  • Özel T., Karpat Y. 2005. Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks. International Journal of Machine Tools and Manufacture; 45: 467-479.
  • Gupta M.K., Sood P.K. 2016. Optimizing multi characterstics in machining of AISI 4340 steel using Taguchi’s approach and utility concept. Journal of The Institution of Engineers (India): Series C; 97: 63-69.
  • Kopac J., Bahor M., Soković M. 2002. Optimal machining parameters for achieving the desired surface roughness in fine turning of cold pre-formed steel workpieces. International Journal of Machine Tools and Manufacture; 42: 707-716.
  • Sahoo P. 2011. Optimization of turning parameters for surface roughness using RSM and GA. Advances in Production Engineering and Management; 6: 197-208.
  • Tzeng C.J., Lin Y.H., Yang Y.K., Jeng M.C. 2009. Optimization of turning operations with multiple performance characteristics using the Taguchi method and grey relational analysis. Journal of Materials Processing Technology; 209: 2753-2759.
  • Bhattacharya A., Das S., Majumder P., Batish A. 2009. Estimating the effect of cutting parameters on surface finish and power consumption during high speed machining of AISI 1045 steel using Taguchi design and ANOVA. Production Engineering; 3: 31-40.
  • Kurt M., Bagci E., Kaynak Y. 2009. Application of Taguchi methods in the optimization of cutting parameters for surface finish and hole diameter accuracy in dry drilling processes. The International Journal of Advanced Manufacturing Technology; 40: 458-469.
  • Bensouilah H., Aouici H., Meddour I., Yallese M.A., Mabrouki T., Girardin F. 2016. Performance of coated and uncoated mixed ceramic tools in hard turning process. Measurement; 82: 1-18.
  • Noordin M.Y., Venkatesh V.C., Sharif S., Elting S., Abdullah A. 2004. Application of response surface methodology in describing the performance of coated carbide tools when turning AISI 1045 steel. Journal of Materials Processing Technology; 145: 46-58.
  • Akkus H. 2018. Optimising the effect of cutting parameters on the average surface roughness in a turning process with the Taguchi method. Materiali in Tehnologije; 52: 6: 781-785
Yıl 2021, Cilt: 17 Sayı: 3, 267 - 273, 27.09.2021
https://doi.org/10.18466/cbayarfbe.898972

Öz

Proje Numarası

FMB-BAP 18-0316

Kaynakça

  • Akbulut H., Içaga Y., Gürer C. 2003. The Possibility of Recycle of Waste Agregates in the Asphalt Pavement and CEN Standards. III National Kırmataş Symposium, 3-4.
  • Akar M. 2018. Casting errors and design methods for prevention, Pamukkale University Graduate School of Natural and Applied Sciences.
  • Cooper D. R., Song J., Gerard R. 2018. Metal recovery during melting of extruded machining chips. Journal of Cleaner Production; 200: 282-292.
  • Jirang C. U. I., Roven H. J. 2010. Recycling of automotive aluminum. Transactions of Nonferrous Metals Society of China; 20: 11: 2057-2063.
  • Martínez V.P., Torres J.T., Valdes A.F. 2017. Recycling of aluminum beverage cans for metallic foams manufacturing. Journal of Porous Materials; 24: 3: 707-712.
  • Gürbüz M. 2018. Effect of the cold working on mechanical properties of aluminum produced from waste beverage cans. Journal of Science and Engineering; 20: 58: 28-35.
  • Özel T., Karpat Y. 2005. Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks. International Journal of Machine Tools and Manufacture; 45: 467-479.
  • Gupta M.K., Sood P.K. 2016. Optimizing multi characterstics in machining of AISI 4340 steel using Taguchi’s approach and utility concept. Journal of The Institution of Engineers (India): Series C; 97: 63-69.
  • Kopac J., Bahor M., Soković M. 2002. Optimal machining parameters for achieving the desired surface roughness in fine turning of cold pre-formed steel workpieces. International Journal of Machine Tools and Manufacture; 42: 707-716.
  • Sahoo P. 2011. Optimization of turning parameters for surface roughness using RSM and GA. Advances in Production Engineering and Management; 6: 197-208.
  • Tzeng C.J., Lin Y.H., Yang Y.K., Jeng M.C. 2009. Optimization of turning operations with multiple performance characteristics using the Taguchi method and grey relational analysis. Journal of Materials Processing Technology; 209: 2753-2759.
  • Bhattacharya A., Das S., Majumder P., Batish A. 2009. Estimating the effect of cutting parameters on surface finish and power consumption during high speed machining of AISI 1045 steel using Taguchi design and ANOVA. Production Engineering; 3: 31-40.
  • Kurt M., Bagci E., Kaynak Y. 2009. Application of Taguchi methods in the optimization of cutting parameters for surface finish and hole diameter accuracy in dry drilling processes. The International Journal of Advanced Manufacturing Technology; 40: 458-469.
  • Bensouilah H., Aouici H., Meddour I., Yallese M.A., Mabrouki T., Girardin F. 2016. Performance of coated and uncoated mixed ceramic tools in hard turning process. Measurement; 82: 1-18.
  • Noordin M.Y., Venkatesh V.C., Sharif S., Elting S., Abdullah A. 2004. Application of response surface methodology in describing the performance of coated carbide tools when turning AISI 1045 steel. Journal of Materials Processing Technology; 145: 46-58.
  • Akkus H. 2018. Optimising the effect of cutting parameters on the average surface roughness in a turning process with the Taguchi method. Materiali in Tehnologije; 52: 6: 781-785
Toplam 16 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Harun Akkuş 0000-0002-9033-309X

Harun Yaka 0000-0003-4859-9609

Proje Numarası FMB-BAP 18-0316
Yayımlanma Tarihi 27 Eylül 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 17 Sayı: 3

Kaynak Göster

APA Akkuş, H., & Yaka, H. (2021). Experimental and response surface methodology investigation of cast material obtained by melting and recycling of chips. Celal Bayar Üniversitesi Fen Bilimleri Dergisi, 17(3), 267-273. https://doi.org/10.18466/cbayarfbe.898972
AMA Akkuş H, Yaka H. Experimental and response surface methodology investigation of cast material obtained by melting and recycling of chips. CBUJOS. Eylül 2021;17(3):267-273. doi:10.18466/cbayarfbe.898972
Chicago Akkuş, Harun, ve Harun Yaka. “Experimental and Response Surface Methodology Investigation of Cast Material Obtained by Melting and Recycling of Chips”. Celal Bayar Üniversitesi Fen Bilimleri Dergisi 17, sy. 3 (Eylül 2021): 267-73. https://doi.org/10.18466/cbayarfbe.898972.
EndNote Akkuş H, Yaka H (01 Eylül 2021) Experimental and response surface methodology investigation of cast material obtained by melting and recycling of chips. Celal Bayar Üniversitesi Fen Bilimleri Dergisi 17 3 267–273.
IEEE H. Akkuş ve H. Yaka, “Experimental and response surface methodology investigation of cast material obtained by melting and recycling of chips”, CBUJOS, c. 17, sy. 3, ss. 267–273, 2021, doi: 10.18466/cbayarfbe.898972.
ISNAD Akkuş, Harun - Yaka, Harun. “Experimental and Response Surface Methodology Investigation of Cast Material Obtained by Melting and Recycling of Chips”. Celal Bayar Üniversitesi Fen Bilimleri Dergisi 17/3 (Eylül 2021), 267-273. https://doi.org/10.18466/cbayarfbe.898972.
JAMA Akkuş H, Yaka H. Experimental and response surface methodology investigation of cast material obtained by melting and recycling of chips. CBUJOS. 2021;17:267–273.
MLA Akkuş, Harun ve Harun Yaka. “Experimental and Response Surface Methodology Investigation of Cast Material Obtained by Melting and Recycling of Chips”. Celal Bayar Üniversitesi Fen Bilimleri Dergisi, c. 17, sy. 3, 2021, ss. 267-73, doi:10.18466/cbayarfbe.898972.
Vancouver Akkuş H, Yaka H. Experimental and response surface methodology investigation of cast material obtained by melting and recycling of chips. CBUJOS. 2021;17(3):267-73.