Influence of Dry-Wet Machining Conditions on Surface Roughness of 6082-T6 Aluminum Alloy in Milling Process

Year 2020, Volume: 8 Issue: 2, 222 - 229, 26.05.2020

Neslihan Özsoy , Murat Ozsoy

https://doi.org/10.21541/apjes.594277

Abstract

In present study the optimum processing conditions were detected by exploring the surface roughness of the 6082-T6 aluminum alloy during milling, depending on the feed per tooth (0.03, 0.05, 0.07, 0.09 mm/tooth), spindle speed (1000,1500, 2000, 2500 rpm) and cooling type (air, liquid) parameters. Experiments designed according to Taguchi’s L16 orthogonal array. With the help of Signal/Noise ratios, the appropriate levels of the parameters have been determined to reduce the surface roughness value to the smallest value. The optimized machining conditions for surface roughness were observed 0.03 mm/tooth of feed per tooth and 2500 rpm of spindle speed and cooling by liquid. Variance and regression analysis were also made in the study. It was obtained that feed per tooth was the dominant parameter on surface roughness according to the analysis results. As last step, confirmation tests were carried out to check the success of the study. 

Keywords

Optimization, Surface roughness, Taguchi method, ANOVA, Milling of Aluminum Alloy

6082-T6 Alüminyum Alaşımlı Malzemenin Frezelenmesinde Sıvı ve Hava Soğutmalı İşleme Koşullarının Yüzey Pürüzlülüğüne Etkisi

Abstract

Bu çalışmada, 6082-T6 alüminyum alaşımının yüzey pürüzlülüğü, diş başı ilerleme (0,03 mm/diş, 0,05 mm/diş, 0,07 mm/diş, 0,09 mm/diş), devir sayısı (1000 dev/dak, 1500 dev/dak, 2000 dev/dak, 2500 dev/dak) ve soğutma tipi (hava, sıvı) parametrelerine bağlı olarak optimum koşullar belirlenmiştir. Taguchi yöntemi ile tasarlanan deneyler L16 ortogonal dizisine göre planlandı ve deneysel sonuçların değerlendirilmesinde sinyal/gürültü (S/N) oranları kullanıldı. S/N oranlarının yardımıyla, yüzey pürüzlülüğü değerini en küçük değere düşürmek için parametrelerin uygun seviyeleri belirlenmiştir. Yüzey pürüzlülüğü için optimize edilmiş işleme koşullarında diş başı ilerleme için 0,03 mm/diş, devir sayısı için 2500 ve soğutma tipi olarak sıvı ile soğutma gözlendi. Araştırmada ayrıca varyans ve regresyon analizi yapılmıştır. Analiz sonuçlarına göre diş başı ilerlemenin yüzey pürüzlülüğü üzerinde en etkili parametre olduğu elde edildi. Son adım olarak, optimizasyonun başarısını kontrol etmek için doğrulama testleri yapıldı.

Keywords

Optimizasyon, Yüzey pürüzlülüğü, Taguchi yöntemi, Varyans analizi, Alüminyum alaşım frezeleme

References

• [1]. I. Asilturk, S. Neseli, M.A. Ince, “Optimization of parameters affecting surface roughness of Co28Cr6Mo medical material during CNC lathe machining by using the taguchi and RSM methods”, Measurement, vol.78, pp. 120-128, 2016.
• [2]. S. Ozturk, “Application of theTaguchi method for surface roughness predictions in the turning process” ,Materials Testing, vol. 58, no.3, pp. 782-787, 2016.
• [3]. A. Uysal, “Surface roughness in nano fluid minimum quantity lubrication milling of AISI 430 ferritic stainless steel”, Journal of Testing and Evaluation, vol. 45, pp. 933-939, 2017.
• [4]. F. A. Akhavan , S. Safian , A. S. Alizadeh , I. M. Hasbullah, “Statistical analysis, modeling and optimization of thrust force and surface roughness in high-speed drilling of Al–Si alloy”, Proc IMechE, Part B: J Engineering Manufacture, vol. 227, no.6, pp. 808-820, 2013.
• [5]. R. Junxue, Z. Jinhua , Z. Jingwen, “Analysis and optimization of cutter geometric parameters for surface integrity in milling titanium alloy using a modified grey–Taguchi method” Proc IMechE, Part B: J Engineering Manufacture, vol. 230, no.11, pp. 2114-2128, 2016.
• [6]. T. Somkiat , T. Prae , R. Suthas, “A wavelet approach to predict surface roughness in ball-end milling”, Proc IMechE, Part B: J Engineering Manufacture, vol.231, no.14, pp. 2468-2478, 2017.
• [7]. Z. Zhang, C. Chen, D. Kirby, “Surface roughness optimization in an end-milling operation using the Taguchi design method”, Journal of Materials Processing Technology, vol.184, pp.233-239, 2007.
• [8]. M. Nalbant, H. Gokkaya, G. Sur, “Application of Taguchi method in the optimization of cutting parameters for surface roughness in turning”,Materials and Design, vol. 28, pp.1379-1385, 2007.
• [9]. T. Kıvak, “Optimization of surface roughness and flank wear using the taguchi method in milling of hadfield steel with PVD and CVD coated inserts”, Measurement, vol.50, pp.19-28, 2014.
• [10]. M. Gunay, “Optimization with Taguchi method of cutting parameters and tool nose radius in machining of AISI 316L Steel”, Journal of the Faculty of Engineering and Architecture of Gazi University, vol.28, no.3, pp.437-444, 2013.
• [11]. R. Cakiroglu, A. Acir, “Taguchi optimization method of tool chip interface temperature depending on the cutting parameters in drilling operations” Electronic Journal of Machine Technologies, vol.10, pp.73-86, 2013.
• [12]. N. Tosun, C. Kuru, E. Altintas, O. E. Erdin, “ Investigation of surface roughness in milling with air and conventional cooling method” Journal of the Faculty of Engineering and Architecture of Gazi University, vol. 25, no.1, pp. 141-146, 2010.
• [13]. F. Kahraman, “Optimization of cutting parameters for surface roughness in turning of studs manufactured from AISI 5140 steel using the Taguchi method”, Materials Testing, vol.59, no.1, pp.77-80, 2017.
• [14]. A. V. Vishnu, M. V. Ramana, K.B.G. Tilak, “Experimental investigations of process parameters influence on surface roughness in turning of EN-353 alloy steel under different machining environments”, Materials Today: Proceedings, vol.5, pp.4192-4200, 2018.
• [15]. D. Behnam, T. Ahmadreza Hosseini,”Cutting forces and surface roughness in wet machining of inconel alloy 738 with coated carbide tool” Proc IMechE, Part B: J Engineering Manufacture, vol.230, no.2, pp. 215-226, 2016.
• [16]. K. Emel, B. Ozcelik, “Optimization of machining parameters during micro-milling of Ti6Al4V titanium alloy and inconel 718 materials using Taguchi method”, Proc IMechE, Part B: J Engineering Manufacture, vol.230, no.2, pp.228-242, 2017.
• [17]. A. M. Pinar, S. Filiz, B. S. Unlu, “A Comparison of cooling methods in the pocket milling of AA5083-H36 alloy via Taguchi method”, The International Journal of Advanced Manufacturing Technology, vol.83, pp.1431-1440, 2016.
• [18]. D. C. Mongomery, Design and analysis of experiments, 5th. Arizona: John Wiley&Sons, 2001.
• [19]. K. Palanikumar, “Experimental investigation and optimization in drilling GFRP composites”, Measurement, vol. 44, pp. 2138-2148, 2011.
• [20]. I. Asilturk, H. Akkus, “Determining the effect of cutting parameters on surface roughness in hard turning using the Taguchi method”, Measurement, vol.44, pp.1697-1704, 2011.
• [21]. K. R. Roy, A primer on the Taguchi method. 1th. New York: Van Nostrand Reinhold, 1990.
• [22]. ISO 1302:2002. Geometrical Product Specifications (GPS)-Indication of surface texture in technical product documentation.
• [23]. M.H. Cetin, B. Ozcelik, E. Kuram, E. Demirbas, “ Evaluation of vegetable based cutting fluids with extreme pressure and cutting parameters in turning of AISI 304L by Taguchi method”, Journal of Cleaner Production, vol.19, pp.2049-2056, 2011.
• [24]. F. Kara, “Taguchi optimization of surface roughness and flank wear during the turning of DIN 1.2344 tool steel”, Materials Testing, vol.59, no.10, pp.903-908, 2017.
• [25]. B. Bhuvnesh, R. Kumar, K. S. Pradeep, “Effect of machining parameters on surface roughness in end milling of AISI 1019 steel”, Proc IMechE, Part B: J Engineering Manufacture, vol.228, no.5, pp.704-714, 2014.
• [26]. N. Mandal, B. Doloi, B. Mondal, R. Das, “Optimization of flank wear using zirconia toughened alumina (ZTA) cutting tool Taguchi method and regression analysis”, Measurement, vol.44, pp.2149-2155, 2011.
• [27]. G.H.V. Babu, K. Venkatarao, C.H. Ratnam, “Multi-response optimization in orthogonal turn milling by analyzing tool vibration and surface roughness using response surface methodology” Proc IMechE, Part B: J Engineering Manufacture, vol.231, no.12, pp.2084-2093, 2017.