Surface roughness analysis and optimization for the CNC milling process by the desirability function combined with the response surface methodology
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Ugur Esme
Abstract
The present study is aimed for an optimization strategy for the CNC pocket millingprocess based on the desirability function approach (DFA) combined with the response surface methodology (RSM). Firstly, the milling parameters such as cutting speed, feed rate and depth of cut are designed using the rotatable central composite design (CCD). The AISI 1050 medium carbon steel is machined by a flat end 8 mm high speed steel (HSS) tool on a zigzag cutting path under air flow condition. The influence of milling parameters is examined. Secondly, the model for the surface roughness, as a function of milling parameters, is obtained using the RSM. Finally, the power and adequacy of the quadratic mathematical model has been proven by the analysis of variance (ANOVA) method. The results indicate that the feed rate is the dominant factor affecting the surface roughness, which is minimized when the feed rate and depth of cut are set to the experimental range. A high correlation coefficient of R2 = 0.99 has been obtained between the predicted and the experimental surface roughness. This reveals that the prediction system established in this study produces satisfactory results with an improved performance compared to other models in the literature. The enhanced method proposed in this study can be readily applied to different metal cutting processes with greater confidence.
Kurzfassung
Die diesem Beitrag zugrunde liegende Studie zielt darauf ab, eine Optimierungsstrategie im CNC-Taschenfräsprozess basierend auf dem Erwünschtheitsfunktionsansatz (Desireability Function Approach – DFA) kombiniert mit der Antwortoberflächen-Methode (Response Surface Methodology – RSM) zu entwickeln. Zunächst wurden hierzu die Fräsparameter, wie die Schnittgeschwindigkeit, die Vorschubrate und die Schnitttiefe mittels rotierendem zentralen Kompositdesign (Central Composite Design – CCD) bestimmt. Der AISI 1050 Stahl mit mittlerem Kohlenstoffgehalt wurde hierzu mit einem 8 mm dicken HSS-Werkzeug im Zick-Zack-Vorschub unter Luftkühlung bearbeitet. Dabei wurde der Einfluss der Fräsparameter untersucht. Danach wurde ein Modell für die Oberflächenrauheit als Funktion der Fräsparameter mittels RSM bestimmt. Schließlich wurde die Leistungsfähigkeit und die Adäquanz des quadaratischen mathematischen Modells mittels Varianzanalyse (ANOVA) geprüft. Die Ergebnisse zeigen, dass die Vorschubrate der dominierende Faktor hinsichtlich des Einflusses auf die Oberflächenrauheit ist, die minimiert wird, wenn die Vorschubrate und die Schnitttiefe auf Werte des experimentellen Rahmens gesetzt werden. Ein hoher Korrelationskoeffizient von R2 = 0.99 zwischen der vorhergesagten und der experimentell bestimmten Oberflächenrauheit wurde ermittelt. Daraus ergibt sich, dass das in dieser Studie hergeleitete Vorhersagesystem befriedigende Ergebnisse liefert und eine verbesserte Performanz gegenüber anderen Modellen in der Literatur aufweist. Das verbesserte und in dieser Studie vorgeschlagene Verfahren kann sofort auf verschiedene Metallfräsprozesse mit größerer Konfidenz angewendet werden.
References
1 B. C.Routara, A. K.Sahoo, A. K.Parida, P. C.Padhi: Response surface methodology and genetic algorithm used to optimize the cutting condition for surface roughness parameters in CNC turning, Procedia Engineering38 (2012), pp. 1893–190410.1016/j.proeng.2012.06.232Search in Google Scholar
2 B.Buldum, A.Şık, U.Eşme, M. K.Külekci, Y.Kazançoğlu: Use of Grey-Taguchi method for the optimization of oblique turning process of AZ91D magnesium alloy, Materials Testing54 (2012), pp. 779–78510.3139/120.110392Search in Google Scholar
3 J. P.Fabricio, P. P.Anderson, P. B.Pedro, F. J.Roberto, B. S.Messias: Optimization of radial basis function neural network employed for prediction of surface roughness in hard turning process using Taguchi's orthogonal arrays, Expert Systems with Applications39 (2012), pp. 7776–778710.1016/j.eswa.2012.01.058Search in Google Scholar
4 P. G.Benardos, G. C.Vosniakos: Prediction of surface roughness in CNC machining: A review, International Journal of Machine Tools and Manufacture43 (2003), pp. 833–84410.1016/S0890-6955(03)00059-2Search in Google Scholar
5 T.Özel, Y.Karpat: Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks, International Journal of Machine Tools and Manufacture45 (2005), pp. 467–47910.1016/j.ijmachtools.2004.09.007Search in Google Scholar
6 B.Ozcelik, M.Bayramoglu: The statistical modeling of surface roughness in high-speed flat end milling, International Journal of Machine Tools and Manufacture46 (2006), pp. 1395–140210.1016/j.ijmachtools.2005.10.005Search in Google Scholar
7 D. K.Baek, T. J.Ko, H. S.Kim: Optimization of feed rate in a face milling operation using a surface roughness model, International Journal of Machine Tools and Manufacture41 (2001), pp. 451–46210.1016/S0890-6955(00)00039-0Search in Google Scholar
8 G.Peigne, H.Paris, D.Brissaud: Surface shape prediction in high speed milling, International Journal of Machine Tools and Manufacture44 (2004), pp. 1567–157610.1016/j.ijmachtools.2004.06.005Search in Google Scholar
9 P.Franco, M.Estrems, F.Fuara: Influence of radial and axial run outs on surface roughness in face milling with round insert cutting tools, International Journal of Machine Tools and Manufacture44 (2004), pp. 1555–156510.1016/j.ijmachtools.2004.06.007Search in Google Scholar
10 H. A.Kishawy, M.Dumitrescu, E. G.Ng, M. A.Elbestawi: Effect of coolant strategy on tool performance, chip morphology and surface quality during high-speed machining of A356 aluminum alloy, International Journal of Machine Tools and Manufacture45 (2005), pp. 219–22710.1016/j.ijmachtools.2004.07.003Search in Google Scholar
11 A. Mariade SouzaJr., W. F.Salesb, S. C.Santosc, A. R.Machadod: Performance of single Si3N4 and mixed Si3N4CPCBN wiper cutting tools applied to high speed face milling of cast iron, International Journal of Machine Tools and Manufacture45 (2005), pp. 335–34410.1016/j.ijmachtools.2004.08.006Search in Google Scholar
12 S. H.Ryua, D.Ki, C.Chong, N.Chu: Roughness and texture generation on end milled surfaces, International Journal of Machine Tools and Manufacture46 (2006), pp. 404–41210.1016/j.ijmachtools.2005.05.010Search in Google Scholar
13 A. L.Mantle, D. K.Aspinwall: Surface integrity of a high speed milled gamma titanium aluminide, Journal of Materials Processing Technology118 (2001), pp. 143–15010.1016/S0924-0136(01)00914-1Search in Google Scholar
14 M. Y.Wang, H. Y.Chang: Experimental study of surface roughness in slot end milling, International Journal of Machine Tools and Manufacture44 (2004), pp. 51–5710.1016/j.ijmachtools.2003.08.011Search in Google Scholar
15 S. J.Lou, J. C.Chen: In-process surface roughness recognition (ISRR) system in end milling operations, International Journal Advanced Manufacturing Technology15 (1999), pp. 200–20910.1007/s001700050057Search in Google Scholar
16 C.Gologlu, N.Sakarya: The effects of cutter path strategies on surface roughness of pocket milling of 1.2738 steel based on Taguchi method, Journal of Materials Processing Technology206 (2008), pp. 7–1510.1016/j.jmatprotec.2007.11.300Search in Google Scholar
17 P. G.Benardos, G. C.Vosniakos: Prediction of surface roughness in CNC face milling using neural networks and Taguchi's design of experiments, Robotics and Computer Integrated Manufacturing18 (2002), pp. 343–354 10.1016/S0736-5845(02)00005-4Search in Google Scholar
18 K. AkmalShamsuddin, A. R.Ab-Kadir, M. H.Osman: A comparison of milling cutting path strategies for thin-walled aluminum alloys fabrication, International Journal of Engineering and Science2 (2013), pp. 1–8Search in Google Scholar
19 Y. M.Ertakin, Y.Kwon, T. L.Tseng: Identification of common sensory features for the control of CNC milling operations under varying cutting conditions, International Journal of Machine Tools and Manufacture43 (2003), pp. 897–90410.1016/S0890-6955(03)00087-7Search in Google Scholar
20 I.Asiltürk, S.Neseli: Multi-response optimisation of CNC turning parameters via Taguchi method-based response surface analysis, Measurement45 (2012), pp. 785–79410.1016/j.measurement.2011.12.004Search in Google Scholar
21 M.Aloufi, T. J.Kazmierski: A response surface modelling approach to performance optimisation of kinetic energy harvesters, IJRRCS simulation, Benchmarking and Modeling of Systems and Communication Networks (2011), pp. 1–8Search in Google Scholar
22 Z.Li, X.Liang: Vibro-acoustic analysis and optimization of damping structure with response surface method, Materials and Design28 (2007), pp. 1999–200710.1016/j.matdes.2006.07.006Search in Google Scholar
23 M. C.Kathleen, Y. K.Natalia, R.Jeff: Response Surface Methodology, Center for Computational Analysis of Social and Organizational Systems (CASOS), Technical Report, USA (2004)Search in Google Scholar
24 R. H.Myers, C. M.Douglas, C. M.Anderson-Cook: Process and Product Optimization Using Designed Experiments, 3rd edition, John Wiley & Sons, Inc.New York, USA (2009)Search in Google Scholar
25 M.Demirel, B.Kayan: Application of response surface methodology and central composite design for the optimization of textile dye degradation by wet air oxidation, International Journal of Industrial Chemistry3 (2012), pp. 1–1010.1186/2228-5547-3-24Search in Google Scholar
26 S. S.Moghaddam, M. R. AlaviMoghaddam, M.Arami: Coagulation/flocculation process for dye removal using sludge from water treatment plant: Optimization through response surface methodology, Journal of Hazardous Materials175 (2010), pp. 651–65710.1016/j.jhazmat.2009.10.058Search in Google Scholar PubMed
27 B.Kayan, B.Gözmen: Degradation of acid red 274 using H2O2 in subcritical water: Application of response surface methodology, Journal of Hazardous Materials201 (2012), pp. 100–10610.1016/j.jhazmat.2011.11.045Search in Google Scholar PubMed
28 R. H.Myers: Response Surface Methodology, Allyn and Bacon, Boston, USA (1971)Search in Google Scholar
29 C. L.Lim, N.Morad, T. T.Teng, I.Norli: Chemical oxygen demand (COD) reduction of a reactive dye wastewater using H2O2/pyridine/Cu(II) system, Desalination278 (2011), pp. 26–3010.1016/j.desal.2011.04.069Search in Google Scholar
30 A.Sagbas: Analysis and optimization of surface roughness in the ball burnishing process using response surface methodology and desirability function, Advances in Engineering Software42 (2011), pp. 992–99810.1016/j.advengsoft.2011.05.021Search in Google Scholar
31 http://www.itl.nist.gov/div898/handbook/pri/section5/pri5322.htmSearch in Google Scholar
32 A.Aggarwal, H.Singh, P.Kumar, M.Sing: Optimization of multiple quality characteristics for CNC turning under cryogenic cutting environment using desirability function, Journal of Materials Processing Technology205 (2008), pp. 42–5010.1016/j.jmatprotec.2007.11.105Search in Google Scholar
33 R. H.Myers, D. C.Montgomery: Response Surface Methodology: Process and Product Optimization Using Designed Experiments, John Wiley & Sons Inc.New York, USA (2002)Search in Google Scholar
© 2015, Carl Hanser Verlag, München
Articles in the same Issue
- Inhalt/Contents
- Inhalt
- Fachbeiträge/Technical Contributions
- A simple procedure for estimating SN-lines for crack initiation from SN-lines for total failure*
- Modellbasierte Korrelation zwischen dem elektrischen Widerstand und der Versetzungsstruktur des ermüdungsbeanspruchten ICE-Radstahls R7
- Effect of cobalt on the aging kinetics and the properties of a CuCoNiBe alloy
- Effect of heat treatment on microstructure and mechanical properties of Fe-5Cr-1.4B alloy
- Interface characterization of friction welded low carbon steel and copper alloys
- Field test methods for aluminum gas cylinders
- Application of the Taguchi method for parameter optimization of the surface grinding process
- A discrete dislocation technique for fatigue microcracks (Part I)
- A discrete dislocation technique for fatigue microcracks (Part II)
- Synchrotron X-ray CT of rose peduncles – evaluation of tissue damage by radiation*
- Surface roughness analysis and optimization for the CNC milling process by the desirability function combined with the response surface methodology
- Design, manufacture and analysis of composite epoxy material with embedded silicon carbide (SiC) and alumina (Al2O3) nanoparticles/fibers
- Performance of organic and inorganic substances as inhibitors for chloride-induced corrosion in concrete
- Fillet welding of austenitic stainless steel using the double channel shielding gas method with cored wire
- Applying quadraphonic transmission ultrasonic defectoscopy on standard aluminum materials
- Kalender/Calendar
- Kalender
Articles in the same Issue
- Inhalt/Contents
- Inhalt
- Fachbeiträge/Technical Contributions
- A simple procedure for estimating SN-lines for crack initiation from SN-lines for total failure*
- Modellbasierte Korrelation zwischen dem elektrischen Widerstand und der Versetzungsstruktur des ermüdungsbeanspruchten ICE-Radstahls R7
- Effect of cobalt on the aging kinetics and the properties of a CuCoNiBe alloy
- Effect of heat treatment on microstructure and mechanical properties of Fe-5Cr-1.4B alloy
- Interface characterization of friction welded low carbon steel and copper alloys
- Field test methods for aluminum gas cylinders
- Application of the Taguchi method for parameter optimization of the surface grinding process
- A discrete dislocation technique for fatigue microcracks (Part I)
- A discrete dislocation technique for fatigue microcracks (Part II)
- Synchrotron X-ray CT of rose peduncles – evaluation of tissue damage by radiation*
- Surface roughness analysis and optimization for the CNC milling process by the desirability function combined with the response surface methodology
- Design, manufacture and analysis of composite epoxy material with embedded silicon carbide (SiC) and alumina (Al2O3) nanoparticles/fibers
- Performance of organic and inorganic substances as inhibitors for chloride-induced corrosion in concrete
- Fillet welding of austenitic stainless steel using the double channel shielding gas method with cored wire
- Applying quadraphonic transmission ultrasonic defectoscopy on standard aluminum materials
- Kalender/Calendar
- Kalender