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Prediction of surface roughness in slotting of CFRP
Accepted Manuscript Prediction of surface roughness in slotting of CFRP Souhir Gara, Oleg Tsoumarev PII: DOI: Reference:
S0263-2241(16)30162-2 http://dx.doi.org/10.1016/j.measurement.2016.05.016 MEASUR 4032
To appear in:
Measurement
Received Date: Revised Date: Accepted Date:
8 December 2014 25 April 2016 3 May 2016
Please cite this article as: S. Gara, O. Tsoumarev, Prediction of surface roughness in slotting of CFRP, Measurement (2016), doi: http://dx.doi.org/10.1016/j.measurement.2016.05.016
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Prediction of surface roughness in slotting of CFRP Souhir Gara*1 and Oleg Tsoumarev* * Laboratoire de Recherche Mécanique Appliquée et Ingénierie (MAI), ENIT - BP 37, 1002 Tunis Le Belvédère, Tunisia 1 Corresponding author: [email protected]
Abstract Nowadays, more attention is drawn to the industrial products made of composite materials. Their anisotropy and inhomogeneity cause a difficulty in predicting their behaviour during machining. With the purpose of understanding and zooming the contact area tool/workpiece, this paper presents a study that evaluate the transverse and longitudinal roughness measurements for knurled tool in slotting of multidirectional carbon fiber-reinforced plastic (CFRP) laminate. By transverse (respectively longitudinal) roughness we mean roughness measured perpendicular to the advance direction (respectively in the advance direction). A theoretical model of transverse roughness is given: it highlights its dependance of only tool geometry. Experiments were carried out to validate the model, to study how longitudinal roughness measurements depends on cutting conditions (cutting speed and feed per tooth) and to predict the surface topography. Keywords: CFRP, slotting, transverse roughness, longitudinal roughness, knurled tool. 1. Introduction Composite materials are made from two or more components with different characteristics in order to take advantage of the superior properties of them. Comparing with metals; they are light, durable and resistant to corrosion. They have low thermal expansion coefficient, high strength and high stiffness. Machining operations such as slotting, edge trimming, routing or grinding are still used in order to remove excess material, give the workpiece its final geometric and dimensional constraints listed in the definition drawing and produce high quality surface [1, 2]. Because of carbon fiber reinforced plastics (CFRPs) inhomogeneity caused by difference in characteristics and properties of the matrix and the fiber components, the machined surface is less regular and generally rougher than machined metal surface using the same cutting conditions [3-5]. When studying the factors of influence of the working environment on the surface quality, Ramulu et al. [6] said that the roughness variations measured in the transverse direction do not seem to depend on fiber orientation with respect to the cutting direction. In its turn, Jamal Sheikh Ahmad et al. [7] found that transverse surface roughness does not have clear trends and is generally higher than the longitudinal surface roughness. Chandrasekaran et al. [8] announced that longitudinal arithmetic average roughness varies linearly with the feed rate and inversely with the spindle speed: it depends mainly on the feed rate followed by spindle speed and depth of cut. This finding was confirmed by Palanikumar et al. [9], Nurhaniza et al.[10], Azmi et al.[11] and contradicted by Reddy Sreenivasulu [12] who said that depth of cut is the key factor that influences the roughness followed by feed rate and cutting speed. In this context, Chongyang Gao et al.[13] told that fiber orientation angle, depth of cut, and cutting speed are the important factors which affect surface roughness and that the coupling
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effects of these machining parameters are relatively negligible in the machining of CFRP composites. Vaclav Schornik et al. [14] found that the appropriate feed rate can be determined as 200mm/min for a spindle rotation speed equal to 20 000rev/min whereas Takeshi Yashiro et al. [15] observed that the matrix resin was not influenced even if cutting speed was as high as 300m/min within a range of variation of feed rate [75; 1500] mm/min. To their turn, Seyedbehzad Ghafarizadeh et al. [16-17] said that cutting speed has significant influence on roughness measurements and that a good surface quality was produced with the cutting conditions (250 m/min cutting speed, 0.063 mm/rev feed rate, 0.5 mm depth of cut). Nurhaniza et al.[10], Azmi et al.[11] and Puw et al. [18] added that the best surface roughness value is obtained at higher cutting speed, lower feed rate and lower depth of cut. The works of a number of authors [18-21] have shown that cutting parameters radically influence the surface quality. Prashanth Janardhan [22] concluded that the roughness measurements are conditioned by tool geometry and cutting conditions. By studying three tools with different helix angles, Chegdani et al.[23] said that the surface roughness increases with the increase of the helix angle of the cutting tool. Neebu alex urban [20] added that up milling provides better roughness measurements than down milling. Previous studies have treated longitudinal roughness, works that have addressed the transverse roughness are few. Several tools and a variety of cutting parameters are chosen in order to find the better combination of cutting speed and feed which gives the surface quality recommended by the customer and defined in the definition drawing. But it is difficult to compare the results because material (fiber reference, matrix reference, technical properties, d geometry) and cutting parameters vary from study to study [24]. The effect of the tool geometry on surface quality has not been investigated in detail for knurled tool fine toothings. The present work aims to study the transverse and longitudinal roughness for a knurled tool fine toothings with non continuous cutting edge. The influence of cutting parameters on the roughness measurements and the predicted surface topography will be presented. 2. Theoretical transverse roughness model and surface topography 2.1. Theoretical transverse roughness model A K20 uncoated knurled tool fine toothings with dimensions and geometry listed in table 1 is used for tests (Fig.1). The tool geometry is special because cutting edges are not continuous: the bases of the teeth are resulting from an intersection between the left and the right helixes (Fig.2). Focusing on the active part of the tool, it seems clear that the teeth are distributed in a regular pattern (Fig.3): - on the circumference: they follow a circular helix, which will be called "third helix". It has the same axis and the same diameter of the cutting tool; - on the length of the cutter, they follow parallel curves which will be called "fourth curve". Naming X1 the distance between two consecutive tooth tops of the third helix (in height) measured in the reference plane Pr, (°) the principal lead angle and (°) the secondary lead angle (Fig.4), the total height of the roughness profile Rt ted as in the expression 1. (1)
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Because of: Rt = K x Ra (2) with K is belongs to the interval [3; 6] [25], the theoretical model of transverse arithmetic average roughness Rat obtained by slotting of CFRP with knurled tool fine toothings is given by the equation 3. (3), K [3; 6]
2.2. Surface topography The tool can be considered as a succession of a finite number of the third helix. When contacting the workpiece, it grooves the form indicated in Fig.5. Indeed, every tooth of the tool grooves his form as in Fig.6.a on the laminate plate and so the topography of the machined surface seems like in Fig.6.b with: (4) being pash3 the pitch of the third helix. 3. Experimental procedure 3.1. Materials and method In order to achieve the objective of this work, multidirectional CFRP monolithic laminate is used in tests. Material was produced by manual lay-up of prepregs (0.3mm thick) with fiber orientation presented as in table 2 consisting of 16 layers with 4.8mm in thikness (Fig.7). It is composed of continuous carbon fiber reinforced with 42% of epoxy matrix. The physical and mechanical properties of the CFRP laminate are given in table 3. The tests were performed on a 3-axis vertical machining center SV815 SEIKI CNC AKIRA. It has 30kW spindle power, maximum spindle speed of 14 000rpm, maximum fast feedrate of 48 000 / 48 000 / 36 000 mm/min and advance work of 12 000mm/min. The machine was equipped with a dust extraction system capable of removing fine particles. The fixation of the test specimen was made as observed in Fig.8 to make sure that vibration and displacements are eliminated. After machining, the test specimens (Fig.9) are cut along the groove axis and installed on a control mounting as shown in figures Fig.10.a and Fig.10.b. The surface roughness was evaluated with SJ-201 rugosimeter provided by the company Mitutoyo and calibrated before use. Transverse and longitudinal average roughness are measured in up and down milling. For each test, five measurments are made over slotted surfaces. 3.2. Design of experiments A full factorial design for two factors at three levels was used for the elaboration of experiments plan with the objective of understanding the behavior of longitudinal roughness surface with speed and feed per tooth. By levels we mean the values taken by the factors. Table 4 indicates the factors to be studied and the assignment allocation of the corresponding levels. The response to be studied is longitudinal arithmetic average roughness Ral
3
arithmetic average roughness measured in the advance direction (perpendicular to the tool axis). The plan of experiment was made of nine tests (array rows) as shown in table 5. 4. Results and discussion After machining test specimens, transverse Rat and longitudinal Ral roughness are measured in up and down milling and slotted surfaces are examined under an optical microscope. 4.1. Transverse roughness Table 5 shows the results of the transverse arithmetic average roughness Rat, measured perpendicular to the advanced direction as function of cutting parameters in up and down milling relating to the knurled tool fine toothings. Because of r1 55.53°, r2 74.60° and X1 0.07mm, total height of the roughness profile is then equal to: Considering that , whatever cutting conditions. The model described in eq.3 mentioned that the transverse roughness depends only on the tool geometry. Cutting conditions, fiber orientation and material properties haven't any influence on transverse roughness measurments: this result is validated with the experimental tests (Fig.11). 4.2. Longitudinal roughness Table 6 shows the results of longitudinal arithmetic average roughness Ral in up and down milling CFRP with knurled tool fine toothings. The plan of tests was developed with the aim of relating the influence of cutting speed and feed per tooth with longitudinal arithmetic average roughness. Statistical treatment of the data was made with Analysis of Variance (ANOVA) and effect of the factors. 4.2.1. ANOVA and effects of the factors
An analysis of variance of the data with the longitudinal arithmetic average roughness on the CFRP composite material was done with the objective of evaluating the influence of cutting speed and feed per tooth on the total variance of longitudinal roughness measurements. Tables 7 and 8 show the results of the ANOVA with the longitudinal arithmetic average roughness in up and down milling. This analysis was carried out for a level of significance of 5% (i.e. for a level of confidence of 95%). From the analysis of table 7 and 8, it can be noted that in up or down milling, feed per tooth and cutting speed factors presents statistical and physical significance on longitudinal arithmetic average roughness Ral because F > F =5% . The feed per tooth factor has more significance on the longitudinal roughness measurements than the cutting speed factor. 4.2.2. Models
Arithmetic average roughness is obtained by multiple linear regression. The resulting equations were as follow: In up milling: (5),
4
R=0.97
In down milling: (6)
R=0.98
Being Ral the arithmetic average roughness in m, Vc the cutting speed in m/min and fz the feed per tooth in mm/rev/tooth. From fig.12 it can be considered that Eqs.(5,6) correlate the evolution of Ral in up and down milling function of cutting speed and feed per tooth with reasonable degree of approximation. 4.3. Surface topography appearance By photographing machined surfaces under optical microscope at different cutting conditions, images of the figure 13 were obtained. They show residual resin scraped off by the teeth of the tool. Indeed, the tool (with pointed top of the teeth) tends to generate interfacial failure from his first contact with the composite material. Moving forward, it leaves the fibers exposed and carries with it the resin (which have low hardness characteristics than fibers) that matches the shape of the teeth. 5. Conclusion A theoretical and experimental approach to evaluate the transverse and longitudinal roughness in slotting of CFRP with knurled tool fine toothings was proposed in this study. The conclusions drawn are as follows: - for knurled tool fine toothings, it was possible to obtain transverse arithmetic average roughness (measured pe of cutting parameters used: manufacturers should optimize cutting parameters before working; - transverse roughness does not depend on cutting conditions, it depends only on tool geometry; - longitudinal roughness in up milling is lower than that in down milling; - feed per tooth is the cutting parameter that presents the highest statistical and physical influence on surface roughness; - the equations (6) and (7) can be effectively used to evaluate the slotting of induced surface roughness obtained. Acknowledgements The authors acknowledge to the Higher Institute of Technological Studies of Nabeul and the Higher Institute of Technological Studies of Beja for allowing us to use their equipments in the experimental work. References [1]: Aude CAILLAUD, Mathieu RITOU, Sébastien GARNIER, Benoît FURET, 2009, Choix de procédés de parachèvement pour les pièces en matériaux composites, JNC 16, France. [2]: El-Hofy M.H., S.L. Sooa, D.K. Aspinwalla, W.M. Simb, D. Pearsonc, P. Hardend, 2011, Factors affecting workpiece surface integrity in slotting of CFRP, Procedia Engineering 19, 94 99. [3]: Koplev A, Lystrup Aa, Vorm T, 1983, The cutting process, chips and cutting forces in Composites, Vol. 14 (4), pp. 371 - 376.
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[4]: König W, Wolf C, Graf P, Willersceid H, 1985, Machining of fibre reinforced plastics, Ann. CIRP 34, 537-547. [5]: Abrate S, Walton S.A, 1992, Machining of composite materials. Part I: Traditional methods, Composites Manufacturing Vol 3 No 2. [6]: Ramulu M, Wern C.W, Garbini J.L, 1993, Effect of the direction on surface roughness measurements of machined graphite/epoxy composite, Compos. Manuf. 4 (1) 39 51. [7]: Jamal Sheikh Ahmad, Nebu Urban, Hossein cheraghi, Machining damage in edge trimming of CFRP, Materials and Manufacturing Processes, 27: 802-808, 2012. [8]: M.Chandrasekaran, D.Devarasiddappa, Development of predictive model for surface roughness in end milling of Al-SiCp metal matrix Composites using fuzzy Logic, World Academy of Science, Engineering and Technology, Vol 6, 2012-07-25. [9]: K.Palanikumar, F.Mata, J.Pauli Davim, Analysis of surface roughness parameters in turning of FRP tubes by PCD tool, Journal of Materials Processing Technology, 204, 2008, 469-474. [10]: M. Nurhaniza, M. K. A. M. Ariffin, F. Mustapha, and B. T. H. T. Baharudin, 2016, Analyzing the Effect of Machining Parameters Setting to the Surface Roughness during End Milling of CFRP-Aluminium Composite Laminates, Hindawi Publishing Corporation International Journal of Manufacturing Engineering Volume 2016, Article ID 4680380, 9 pages. [11]: H. Azmi, C. H. C Haron, J. A. Ghani , M. Suhaily , A. B. Sanuddin and J. H. Song, Study on machinability effect of surface roughness in milling kenaf fiber reinforced plastic composite (unidirectional) using response surface methodology, ARPN Journal of Engineering and Applied Sciences, VOL. 11, NO. 7, APRIL 2016. [12]: Reddy Sreenivasulu, Optimization of surface roughness and delamination damage of GFRP omposite material in end milling using Taguchi design method and artificial neural network, Procedia Engineering, 64, 2013, pp:785-794. [13]: Chongyang Gao, Jianzhang Xiao, Jiuhua Xu and Yinglin Ke, 2015, Factor analysis of machining parameters of fiber-reinforced polymer composites based on finite element simulation with experimental investigation, Int J Adv Manuf Technol, DOI 10.1007/s00170015-7592-2. [14]: Vaclav Schornik, Milan Dana, Ivana Zetkova, The influence of the cutting conditions on the machined surface quality when the CFRP is machined, Procedia Engineering, 100 (2015), 1270-1276. [15]: Takeshi Yashiro, Takayuki Ogawa, Hiroyuki Sasahara, Temperature measurment of cutting tool and machined surface layer in milling of CFRP, International Journal of Machine Tool and Manufacture, 70 (2013), 63-69. [16]: Seyedbehzad Ghafarizadeh, Gilbert Lebrun and Jean-François Chatelain, 2015, Experimental investigation of the cutting temperature and surface quality during milling of unidirectional carbon fiber reinforced plastic, Journal of Composite Materials, 0(0) , pp: 1 13. [17]: Seyedbehzad Ghafarizadeh, Jean-François Chatelain and Gilbert Lebrun, 2016, Finite element analysis of surface milling of carbon fiber-reinforced composites, Int J Adv Manuf Technol, DOI 10.1007/s00170-016-8482-y. [18]: Puw, H.Y., Hocheng, H. , 1998, Chip Formation Model of Cutting Fibre-Reinforced Plastics Perpendicular to Fibre Axis. J. Manufacturing Science and Engineering, Vol. 120(1), 192-196. [19]: Puw, H.Y., Hocheng, H., 1999, Milling of polymer composites , a chapter in Machinig of Ceramics and composites, Ed. S. Jahanmir and M. Ramulu, Marcel Dekker Book, pp. 267294. [20]: Neebu alex urban, 2001, Analysis of machining quality in edge trimming of carbon fibre reinforced composite, thesis, India.
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[21]: Davim J.P, Pedro Reis, 2005, Damage and dimensional precision on milling carbon fibre-reinforced plastics using design experiments, Journal of Materials Processing Technology 160, 160 167. [22]: Prashanth Janardhan, 2005, tool wear of diamond interlocked tools in routing of CFRP composites, thesis, Faculty of the graduate school of Wichita state university, December. [23]: F. Chegdani, S. Mezghani, M. El Mansori, Étude de la signature tribologique multiéchelle de l'angle d'hélice sur l'usinabilité des agrocomposites à renfort tissé de fibres de lin, JIFT 2016, 27-Etienne, France. [24]: Else Eriksen, 1999, Influence from production parameters on the surface roughness of a machined short fibre reinforced thermoplastic, International Journal of Machine Tools and Manufacture, Volume 39, Issue 10, Pages 1611 1618. [25]: Stefanuta Enache, la qualité des surfaces usinées, translated by Michel Chambon DUNOD, Paris 1972.
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List of Figures Fig.1 : Active part of knurled tool fine toothings Fig.2 : Knurled tool composition Fig.3 : Knurled tool configuration Fig.4 : Configuration of the contact area tool/workpiece Fig.5 : Teeth traces on the workpiece Fig.6 : Tooth impression (a) and estimated topography of the machined surface (b) Fig.7 : CFRP laminate plate Fig.8: Fixation of the test specimen on the machine Fig.9: Machined test specimen Fig.10 : a: Mounting for measuring the transverse roughness, b: Mounting for measuring the longitudinal roughness Fig.11 : Transverse arithmetic roughness as a function of cutting parameters Fig.12: Comparison of experimental data and theoretical models in up and down milling Fig.13: Surface topography
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Figures
Fig.1 : Active part of knurled tool fine toothings
Active portion
Right helix
Shank
Left helix
Fig.2 : Knurled tool composition
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Base of the tooth
Fig.3 : Knurled tool configuration
Fig.4 : Configuration of the contact area tool/workpiece
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Fig.5 : Teeth traces on the workpiece
a b Fig.6 : Tooth impression (a) and estimated topography of the machined surface (b)
Fig.7 : CFRP laminate plate
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Knurled tool fine toothings Laminate plate
Mounting jig
Fig.8: Fixation of the test specimen on the machine
Fig.9: Machined test specimen
Slotted surface Control mounting a
b
Fig.10 : a: Mounting for measuring the transverse roughness, b: Mounting for measuring the longitudinal roughness
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Fig.11 : Transverse arithmetic roughness as a function of cutting parameters
Fig.12: Comparison of experimental data and theoretical models in up and down milling Tooth traces
Fig.13: Surface topography in up milling
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List of Tables Table 1 Tool dimension and geometry Table 2 Fibre orientation material Table 3 Physical and Mechanical CFRP properties Table 4 Assignment of the levels to the factors Table 5 Values of transverse arithmetic average roughness R at as a function of cutting parameters Table 6 Values of longitudinal arithmetic average roughness R al as a function of cutting parameters Table 7 ANOVA table for the longitudinal arithmetic average roughness R al in up milling Table 8 ANOVA table for the longitudinal arithmetic average roughness R al in down milling
Tables Table 1 Tool dimension and geometry Diameter (mm) 8 Overall length (mm) 100 Cutting length (mm) 45 Number of left helixes 14 Number of right helixes 12 Table 2 Fibre orientation material Ply number 1 2 3 4 5 6 7 8
Orientation 0°/90° 45°/135° 0°/90° 45°/135° 45°/135° 0°/90° 45°/135° 0°/90°
Ply number 9 10 11 12 13 14 15 16
Table 3 Physical and Mechanical CFRP properties CFRP properties Industrial reference reinforcement
Value G803
15
Orientation 0°/90° 45°/135° 0°/90° 45°/135° 45°/135° 0°/90° 45°/135° 0°/90°
Industrial reference matrix Minimum breaking strength Minimum shear stress Ply thikness
914 14 kN 60 MPa 0.3mm
Table 4 Assignment of the levels to the factors Level 1 2 3
Vc (m/min) 100 175 250
Factors fz (mm/rev/tooth) 0.008 0.034 0.060
Table 5 Values of transverse arithmetic average roughness Rat as a function of cutting parameters Up milling Vc Vf Test fz (mm/rev/tooth) z Test 1 Test 2 Test 3 Test 4 (m/min) (mm/min) 1 100 0.008 14 446 3.43 3.41 3.37 3.35 2 100 0.034 14 1894 3.40 3.41 3.42 3.42 3 100 0.060 14 3342 3.40 3.40 3.42 3.38 4 175 0.008 14 780 3.41 3.41 3.42 3.42 5 175 0.034 14 3314 3.42 3.41 3.40 3.42 6 175 0.060 14 5849 3.40 3.42 3.41 3.43 7 250 0.008 14 1114 3.38 3.41 3.42 3.43 8 250 0.034 14 4735 3.40 3.41 3.43 3.42 9 250 0.060 14 8356 3.41 3.42 3.39 3.42 Down milling Vf Vc Test 1 Test 2 Test 3 Test 4 f (mm/rev/tooth) z Test (mm/min) (m/min) z 1 100 0.008 14 446 3.39 3.40 3.42 3.38 2 100 0.034 14 1894 3.40 3.42 3.42 3.40 3 100 0.060 14 3342 3.41 3.42 3.41 3.44 4 175 0.008 14 780 3.42 3.40 3.40 3.41 5 175 0.034 14 3314 3.41 3.42 3.41 3.43 6 175 0.060 14 5849 3.40 3.41 3.40 3.42 7 250 0.008 14 1114 3.40 3.40 3.41 3.41 8 250 0.034 14 4735 3.41 3.38 3.40 3.39 9 250 0.060 14 8356 3.40 3.42 3.42 3.41
Test 5
Rat average
3.38 3.41 3.41 3.41 3.42 3.44 3.42 3.39 3.42
3.39 3.41 3.40 3.41 3.41 3.42 3.41 3.41 3.41
Test 5
Rat average
3.42 3.41 3.41 3.39 3.40 3.40 3.39 3.41 3.41
3.40 3.41 3.42 3.40 3.41 3.41 3.40 3.40 3.41
Table 6 Values of longitudinal arithmetic average roughness Ral as a function of cutting parameters Up milling Vc Vf fz Test z Test 1 Test 2 Test 3 Test 4 (m/min) (mm/rev/tooth) (mm/min) 1 100 0.008 14 446 2.37 2.31 2.41 2.30 2 100 0.034 14 1894 6.86 6.78 6.65 6.68 3 100 0.060 14 3342 9.91 9.92 9.80 9.92
16
Test 5
Ral average
2.32 6.65 9.88
2.34 6.72 9.89
4 175 5 175 6 175 7 250 8 250 9 250 Down milling Vc Test (m/min) 1 100 2 100 3 100 4 175 5 175 6 175 7 250 8 250 9 250
0.008 0.034 0.060 0.008 0.034 0.060 fz (mm/rev/tooth) 0.008 0.034 0.060 0.008 0.034 0.060 0.008 0.034 0.060
14 14 14 14 14 14 z 14 14 14 14 14 14 14 14 14
780 3314 5849 1114 4735 8356 Vf (mm/min) 446 1894 3342 780 3314 5849 1114 4735 8356
6.06 11.42 16.71 9.60 13.82 21.33
6.12 11.39 16.73 9.96 13.71 21.47
6.26 11.40 16.66 9.97 13.68 21.34
6.23 11.61 16.77 9.96 13.65 21.52
6.21 11.61 16.59 9.95 13.73 21.58
Test 1
Test 2
Test 3
Test 4
Test 5
1.54 8.57 16.58 5.06 19.32 28.54 15.48 28.41 39.36
1.56 8.36 16.60 5.09 19.32 28.62 15.56 28.41 39.38
1.54 8.56 16.73 5.18 19.35 28.60 15.72 28.48 39.28
1.51 8.53 16.80 5.15 19.36 28.40 15.86 28.51 39.25
1.50 8.57 16.79 5.14 19.38 28.59 15.65 28.33 39.32
6.18 11.49 16.69 9.89 13.72 21.45 Ral average
Table 7 ANOVA table for the longitudinal arithmetic average roughness R al in up milling Source of SDQ d.f Variance Test F P(%) F =5% variance Vc (m/min) 114.78 2 57.39 33.97 6.94 41.55 fz (mm/rev/tooth) 146.59 2 73.30 43.38 6.94 53.41 Error 6.76 4 1.69 5.04 Total 268.13 8 100 SDQ :Sum of squares, d.f : degress of freedom, P : percentage of contribution. Table 8 ANOVA table for the longitudinal arithmetic average roughness Ral in down milling Source of SDQ d.f Variance Test F P(%) F =5% variance Vc (m/min) 535.85 2 267.92 40.27 6.94 43.17 fz (mm/rev/tooth) 647.85 2 323.93 48.69 6.94 52.43 Error 26.61 4 6.65 4.40 Total 1210.31 8 100 SDQ :Sum of squares, d.f : degress of freedom, P : percentage of contribution.
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1.53 8.52 16.70 5.12 19.35 28.55 15.65 28.43 39.32
Highlights Transverse roughness depends only on tool geometry. Longitudinal roughness depends on cutting conditions. Feed per tooth is the key factor that influences the roughness values in slotting of CFRP with knurled tool fine toothings. Manufacturers must optimize cutting conditions based on the equations 5 and 6.
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S0263-2241(16)30162-2 http://dx.doi.org/10.1016/j.measurement.2016.05.016 MEASUR 4032
To appear in:
Measurement
Received Date: Revised Date: Accepted Date:
8 December 2014 25 April 2016 3 May 2016
Please cite this article as: S. Gara, O. Tsoumarev, Prediction of surface roughness in slotting of CFRP, Measurement (2016), doi: http://dx.doi.org/10.1016/j.measurement.2016.05.016
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Prediction of surface roughness in slotting of CFRP Souhir Gara*1 and Oleg Tsoumarev* * Laboratoire de Recherche Mécanique Appliquée et Ingénierie (MAI), ENIT - BP 37, 1002 Tunis Le Belvédère, Tunisia 1 Corresponding author: [email protected]
Abstract Nowadays, more attention is drawn to the industrial products made of composite materials. Their anisotropy and inhomogeneity cause a difficulty in predicting their behaviour during machining. With the purpose of understanding and zooming the contact area tool/workpiece, this paper presents a study that evaluate the transverse and longitudinal roughness measurements for knurled tool in slotting of multidirectional carbon fiber-reinforced plastic (CFRP) laminate. By transverse (respectively longitudinal) roughness we mean roughness measured perpendicular to the advance direction (respectively in the advance direction). A theoretical model of transverse roughness is given: it highlights its dependance of only tool geometry. Experiments were carried out to validate the model, to study how longitudinal roughness measurements depends on cutting conditions (cutting speed and feed per tooth) and to predict the surface topography. Keywords: CFRP, slotting, transverse roughness, longitudinal roughness, knurled tool. 1. Introduction Composite materials are made from two or more components with different characteristics in order to take advantage of the superior properties of them. Comparing with metals; they are light, durable and resistant to corrosion. They have low thermal expansion coefficient, high strength and high stiffness. Machining operations such as slotting, edge trimming, routing or grinding are still used in order to remove excess material, give the workpiece its final geometric and dimensional constraints listed in the definition drawing and produce high quality surface [1, 2]. Because of carbon fiber reinforced plastics (CFRPs) inhomogeneity caused by difference in characteristics and properties of the matrix and the fiber components, the machined surface is less regular and generally rougher than machined metal surface using the same cutting conditions [3-5]. When studying the factors of influence of the working environment on the surface quality, Ramulu et al. [6] said that the roughness variations measured in the transverse direction do not seem to depend on fiber orientation with respect to the cutting direction. In its turn, Jamal Sheikh Ahmad et al. [7] found that transverse surface roughness does not have clear trends and is generally higher than the longitudinal surface roughness. Chandrasekaran et al. [8] announced that longitudinal arithmetic average roughness varies linearly with the feed rate and inversely with the spindle speed: it depends mainly on the feed rate followed by spindle speed and depth of cut. This finding was confirmed by Palanikumar et al. [9], Nurhaniza et al.[10], Azmi et al.[11] and contradicted by Reddy Sreenivasulu [12] who said that depth of cut is the key factor that influences the roughness followed by feed rate and cutting speed. In this context, Chongyang Gao et al.[13] told that fiber orientation angle, depth of cut, and cutting speed are the important factors which affect surface roughness and that the coupling
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effects of these machining parameters are relatively negligible in the machining of CFRP composites. Vaclav Schornik et al. [14] found that the appropriate feed rate can be determined as 200mm/min for a spindle rotation speed equal to 20 000rev/min whereas Takeshi Yashiro et al. [15] observed that the matrix resin was not influenced even if cutting speed was as high as 300m/min within a range of variation of feed rate [75; 1500] mm/min. To their turn, Seyedbehzad Ghafarizadeh et al. [16-17] said that cutting speed has significant influence on roughness measurements and that a good surface quality was produced with the cutting conditions (250 m/min cutting speed, 0.063 mm/rev feed rate, 0.5 mm depth of cut). Nurhaniza et al.[10], Azmi et al.[11] and Puw et al. [18] added that the best surface roughness value is obtained at higher cutting speed, lower feed rate and lower depth of cut. The works of a number of authors [18-21] have shown that cutting parameters radically influence the surface quality. Prashanth Janardhan [22] concluded that the roughness measurements are conditioned by tool geometry and cutting conditions. By studying three tools with different helix angles, Chegdani et al.[23] said that the surface roughness increases with the increase of the helix angle of the cutting tool. Neebu alex urban [20] added that up milling provides better roughness measurements than down milling. Previous studies have treated longitudinal roughness, works that have addressed the transverse roughness are few. Several tools and a variety of cutting parameters are chosen in order to find the better combination of cutting speed and feed which gives the surface quality recommended by the customer and defined in the definition drawing. But it is difficult to compare the results because material (fiber reference, matrix reference, technical properties, d geometry) and cutting parameters vary from study to study [24]. The effect of the tool geometry on surface quality has not been investigated in detail for knurled tool fine toothings. The present work aims to study the transverse and longitudinal roughness for a knurled tool fine toothings with non continuous cutting edge. The influence of cutting parameters on the roughness measurements and the predicted surface topography will be presented. 2. Theoretical transverse roughness model and surface topography 2.1. Theoretical transverse roughness model A K20 uncoated knurled tool fine toothings with dimensions and geometry listed in table 1 is used for tests (Fig.1). The tool geometry is special because cutting edges are not continuous: the bases of the teeth are resulting from an intersection between the left and the right helixes (Fig.2). Focusing on the active part of the tool, it seems clear that the teeth are distributed in a regular pattern (Fig.3): - on the circumference: they follow a circular helix, which will be called "third helix". It has the same axis and the same diameter of the cutting tool; - on the length of the cutter, they follow parallel curves which will be called "fourth curve". Naming X1 the distance between two consecutive tooth tops of the third helix (in height) measured in the reference plane Pr, (°) the principal lead angle and (°) the secondary lead angle (Fig.4), the total height of the roughness profile Rt ted as in the expression 1. (1)
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Because of: Rt = K x Ra (2) with K is belongs to the interval [3; 6] [25], the theoretical model of transverse arithmetic average roughness Rat obtained by slotting of CFRP with knurled tool fine toothings is given by the equation 3. (3), K [3; 6]
2.2. Surface topography The tool can be considered as a succession of a finite number of the third helix. When contacting the workpiece, it grooves the form indicated in Fig.5. Indeed, every tooth of the tool grooves his form as in Fig.6.a on the laminate plate and so the topography of the machined surface seems like in Fig.6.b with: (4) being pash3 the pitch of the third helix. 3. Experimental procedure 3.1. Materials and method In order to achieve the objective of this work, multidirectional CFRP monolithic laminate is used in tests. Material was produced by manual lay-up of prepregs (0.3mm thick) with fiber orientation presented as in table 2 consisting of 16 layers with 4.8mm in thikness (Fig.7). It is composed of continuous carbon fiber reinforced with 42% of epoxy matrix. The physical and mechanical properties of the CFRP laminate are given in table 3. The tests were performed on a 3-axis vertical machining center SV815 SEIKI CNC AKIRA. It has 30kW spindle power, maximum spindle speed of 14 000rpm, maximum fast feedrate of 48 000 / 48 000 / 36 000 mm/min and advance work of 12 000mm/min. The machine was equipped with a dust extraction system capable of removing fine particles. The fixation of the test specimen was made as observed in Fig.8 to make sure that vibration and displacements are eliminated. After machining, the test specimens (Fig.9) are cut along the groove axis and installed on a control mounting as shown in figures Fig.10.a and Fig.10.b. The surface roughness was evaluated with SJ-201 rugosimeter provided by the company Mitutoyo and calibrated before use. Transverse and longitudinal average roughness are measured in up and down milling. For each test, five measurments are made over slotted surfaces. 3.2. Design of experiments A full factorial design for two factors at three levels was used for the elaboration of experiments plan with the objective of understanding the behavior of longitudinal roughness surface with speed and feed per tooth. By levels we mean the values taken by the factors. Table 4 indicates the factors to be studied and the assignment allocation of the corresponding levels. The response to be studied is longitudinal arithmetic average roughness Ral
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arithmetic average roughness measured in the advance direction (perpendicular to the tool axis). The plan of experiment was made of nine tests (array rows) as shown in table 5. 4. Results and discussion After machining test specimens, transverse Rat and longitudinal Ral roughness are measured in up and down milling and slotted surfaces are examined under an optical microscope. 4.1. Transverse roughness Table 5 shows the results of the transverse arithmetic average roughness Rat, measured perpendicular to the advanced direction as function of cutting parameters in up and down milling relating to the knurled tool fine toothings. Because of r1 55.53°, r2 74.60° and X1 0.07mm, total height of the roughness profile is then equal to: Considering that , whatever cutting conditions. The model described in eq.3 mentioned that the transverse roughness depends only on the tool geometry. Cutting conditions, fiber orientation and material properties haven't any influence on transverse roughness measurments: this result is validated with the experimental tests (Fig.11). 4.2. Longitudinal roughness Table 6 shows the results of longitudinal arithmetic average roughness Ral in up and down milling CFRP with knurled tool fine toothings. The plan of tests was developed with the aim of relating the influence of cutting speed and feed per tooth with longitudinal arithmetic average roughness. Statistical treatment of the data was made with Analysis of Variance (ANOVA) and effect of the factors. 4.2.1. ANOVA and effects of the factors
An analysis of variance of the data with the longitudinal arithmetic average roughness on the CFRP composite material was done with the objective of evaluating the influence of cutting speed and feed per tooth on the total variance of longitudinal roughness measurements. Tables 7 and 8 show the results of the ANOVA with the longitudinal arithmetic average roughness in up and down milling. This analysis was carried out for a level of significance of 5% (i.e. for a level of confidence of 95%). From the analysis of table 7 and 8, it can be noted that in up or down milling, feed per tooth and cutting speed factors presents statistical and physical significance on longitudinal arithmetic average roughness Ral because F > F =5% . The feed per tooth factor has more significance on the longitudinal roughness measurements than the cutting speed factor. 4.2.2. Models
Arithmetic average roughness is obtained by multiple linear regression. The resulting equations were as follow: In up milling: (5),
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R=0.97
In down milling: (6)
R=0.98
Being Ral the arithmetic average roughness in m, Vc the cutting speed in m/min and fz the feed per tooth in mm/rev/tooth. From fig.12 it can be considered that Eqs.(5,6) correlate the evolution of Ral in up and down milling function of cutting speed and feed per tooth with reasonable degree of approximation. 4.3. Surface topography appearance By photographing machined surfaces under optical microscope at different cutting conditions, images of the figure 13 were obtained. They show residual resin scraped off by the teeth of the tool. Indeed, the tool (with pointed top of the teeth) tends to generate interfacial failure from his first contact with the composite material. Moving forward, it leaves the fibers exposed and carries with it the resin (which have low hardness characteristics than fibers) that matches the shape of the teeth. 5. Conclusion A theoretical and experimental approach to evaluate the transverse and longitudinal roughness in slotting of CFRP with knurled tool fine toothings was proposed in this study. The conclusions drawn are as follows: - for knurled tool fine toothings, it was possible to obtain transverse arithmetic average roughness (measured pe of cutting parameters used: manufacturers should optimize cutting parameters before working; - transverse roughness does not depend on cutting conditions, it depends only on tool geometry; - longitudinal roughness in up milling is lower than that in down milling; - feed per tooth is the cutting parameter that presents the highest statistical and physical influence on surface roughness; - the equations (6) and (7) can be effectively used to evaluate the slotting of induced surface roughness obtained. Acknowledgements The authors acknowledge to the Higher Institute of Technological Studies of Nabeul and the Higher Institute of Technological Studies of Beja for allowing us to use their equipments in the experimental work. References [1]: Aude CAILLAUD, Mathieu RITOU, Sébastien GARNIER, Benoît FURET, 2009, Choix de procédés de parachèvement pour les pièces en matériaux composites, JNC 16, France. [2]: El-Hofy M.H., S.L. Sooa, D.K. Aspinwalla, W.M. Simb, D. Pearsonc, P. Hardend, 2011, Factors affecting workpiece surface integrity in slotting of CFRP, Procedia Engineering 19, 94 99. [3]: Koplev A, Lystrup Aa, Vorm T, 1983, The cutting process, chips and cutting forces in Composites, Vol. 14 (4), pp. 371 - 376.
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[4]: König W, Wolf C, Graf P, Willersceid H, 1985, Machining of fibre reinforced plastics, Ann. CIRP 34, 537-547. [5]: Abrate S, Walton S.A, 1992, Machining of composite materials. Part I: Traditional methods, Composites Manufacturing Vol 3 No 2. [6]: Ramulu M, Wern C.W, Garbini J.L, 1993, Effect of the direction on surface roughness measurements of machined graphite/epoxy composite, Compos. Manuf. 4 (1) 39 51. [7]: Jamal Sheikh Ahmad, Nebu Urban, Hossein cheraghi, Machining damage in edge trimming of CFRP, Materials and Manufacturing Processes, 27: 802-808, 2012. [8]: M.Chandrasekaran, D.Devarasiddappa, Development of predictive model for surface roughness in end milling of Al-SiCp metal matrix Composites using fuzzy Logic, World Academy of Science, Engineering and Technology, Vol 6, 2012-07-25. [9]: K.Palanikumar, F.Mata, J.Pauli Davim, Analysis of surface roughness parameters in turning of FRP tubes by PCD tool, Journal of Materials Processing Technology, 204, 2008, 469-474. [10]: M. Nurhaniza, M. K. A. M. Ariffin, F. Mustapha, and B. T. H. T. Baharudin, 2016, Analyzing the Effect of Machining Parameters Setting to the Surface Roughness during End Milling of CFRP-Aluminium Composite Laminates, Hindawi Publishing Corporation International Journal of Manufacturing Engineering Volume 2016, Article ID 4680380, 9 pages. [11]: H. Azmi, C. H. C Haron, J. A. Ghani , M. Suhaily , A. B. Sanuddin and J. H. Song, Study on machinability effect of surface roughness in milling kenaf fiber reinforced plastic composite (unidirectional) using response surface methodology, ARPN Journal of Engineering and Applied Sciences, VOL. 11, NO. 7, APRIL 2016. [12]: Reddy Sreenivasulu, Optimization of surface roughness and delamination damage of GFRP omposite material in end milling using Taguchi design method and artificial neural network, Procedia Engineering, 64, 2013, pp:785-794. [13]: Chongyang Gao, Jianzhang Xiao, Jiuhua Xu and Yinglin Ke, 2015, Factor analysis of machining parameters of fiber-reinforced polymer composites based on finite element simulation with experimental investigation, Int J Adv Manuf Technol, DOI 10.1007/s00170015-7592-2. [14]: Vaclav Schornik, Milan Dana, Ivana Zetkova, The influence of the cutting conditions on the machined surface quality when the CFRP is machined, Procedia Engineering, 100 (2015), 1270-1276. [15]: Takeshi Yashiro, Takayuki Ogawa, Hiroyuki Sasahara, Temperature measurment of cutting tool and machined surface layer in milling of CFRP, International Journal of Machine Tool and Manufacture, 70 (2013), 63-69. [16]: Seyedbehzad Ghafarizadeh, Gilbert Lebrun and Jean-François Chatelain, 2015, Experimental investigation of the cutting temperature and surface quality during milling of unidirectional carbon fiber reinforced plastic, Journal of Composite Materials, 0(0) , pp: 1 13. [17]: Seyedbehzad Ghafarizadeh, Jean-François Chatelain and Gilbert Lebrun, 2016, Finite element analysis of surface milling of carbon fiber-reinforced composites, Int J Adv Manuf Technol, DOI 10.1007/s00170-016-8482-y. [18]: Puw, H.Y., Hocheng, H. , 1998, Chip Formation Model of Cutting Fibre-Reinforced Plastics Perpendicular to Fibre Axis. J. Manufacturing Science and Engineering, Vol. 120(1), 192-196. [19]: Puw, H.Y., Hocheng, H., 1999, Milling of polymer composites , a chapter in Machinig of Ceramics and composites, Ed. S. Jahanmir and M. Ramulu, Marcel Dekker Book, pp. 267294. [20]: Neebu alex urban, 2001, Analysis of machining quality in edge trimming of carbon fibre reinforced composite, thesis, India.
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[21]: Davim J.P, Pedro Reis, 2005, Damage and dimensional precision on milling carbon fibre-reinforced plastics using design experiments, Journal of Materials Processing Technology 160, 160 167. [22]: Prashanth Janardhan, 2005, tool wear of diamond interlocked tools in routing of CFRP composites, thesis, Faculty of the graduate school of Wichita state university, December. [23]: F. Chegdani, S. Mezghani, M. El Mansori, Étude de la signature tribologique multiéchelle de l'angle d'hélice sur l'usinabilité des agrocomposites à renfort tissé de fibres de lin, JIFT 2016, 27-Etienne, France. [24]: Else Eriksen, 1999, Influence from production parameters on the surface roughness of a machined short fibre reinforced thermoplastic, International Journal of Machine Tools and Manufacture, Volume 39, Issue 10, Pages 1611 1618. [25]: Stefanuta Enache, la qualité des surfaces usinées, translated by Michel Chambon DUNOD, Paris 1972.
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List of Figures Fig.1 : Active part of knurled tool fine toothings Fig.2 : Knurled tool composition Fig.3 : Knurled tool configuration Fig.4 : Configuration of the contact area tool/workpiece Fig.5 : Teeth traces on the workpiece Fig.6 : Tooth impression (a) and estimated topography of the machined surface (b) Fig.7 : CFRP laminate plate Fig.8: Fixation of the test specimen on the machine Fig.9: Machined test specimen Fig.10 : a: Mounting for measuring the transverse roughness, b: Mounting for measuring the longitudinal roughness Fig.11 : Transverse arithmetic roughness as a function of cutting parameters Fig.12: Comparison of experimental data and theoretical models in up and down milling Fig.13: Surface topography
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Figures
Fig.1 : Active part of knurled tool fine toothings
Active portion
Right helix
Shank
Left helix
Fig.2 : Knurled tool composition
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Base of the tooth
Fig.3 : Knurled tool configuration
Fig.4 : Configuration of the contact area tool/workpiece
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Fig.5 : Teeth traces on the workpiece
a b Fig.6 : Tooth impression (a) and estimated topography of the machined surface (b)
Fig.7 : CFRP laminate plate
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Knurled tool fine toothings Laminate plate
Mounting jig
Fig.8: Fixation of the test specimen on the machine
Fig.9: Machined test specimen
Slotted surface Control mounting a
b
Fig.10 : a: Mounting for measuring the transverse roughness, b: Mounting for measuring the longitudinal roughness
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Fig.11 : Transverse arithmetic roughness as a function of cutting parameters
Fig.12: Comparison of experimental data and theoretical models in up and down milling Tooth traces
Fig.13: Surface topography in up milling
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List of Tables Table 1 Tool dimension and geometry Table 2 Fibre orientation material Table 3 Physical and Mechanical CFRP properties Table 4 Assignment of the levels to the factors Table 5 Values of transverse arithmetic average roughness R at as a function of cutting parameters Table 6 Values of longitudinal arithmetic average roughness R al as a function of cutting parameters Table 7 ANOVA table for the longitudinal arithmetic average roughness R al in up milling Table 8 ANOVA table for the longitudinal arithmetic average roughness R al in down milling
Tables Table 1 Tool dimension and geometry Diameter (mm) 8 Overall length (mm) 100 Cutting length (mm) 45 Number of left helixes 14 Number of right helixes 12 Table 2 Fibre orientation material Ply number 1 2 3 4 5 6 7 8
Orientation 0°/90° 45°/135° 0°/90° 45°/135° 45°/135° 0°/90° 45°/135° 0°/90°
Ply number 9 10 11 12 13 14 15 16
Table 3 Physical and Mechanical CFRP properties CFRP properties Industrial reference reinforcement
Value G803
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Orientation 0°/90° 45°/135° 0°/90° 45°/135° 45°/135° 0°/90° 45°/135° 0°/90°
Industrial reference matrix Minimum breaking strength Minimum shear stress Ply thikness
914 14 kN 60 MPa 0.3mm
Table 4 Assignment of the levels to the factors Level 1 2 3
Vc (m/min) 100 175 250
Factors fz (mm/rev/tooth) 0.008 0.034 0.060
Table 5 Values of transverse arithmetic average roughness Rat as a function of cutting parameters Up milling Vc Vf Test fz (mm/rev/tooth) z Test 1 Test 2 Test 3 Test 4 (m/min) (mm/min) 1 100 0.008 14 446 3.43 3.41 3.37 3.35 2 100 0.034 14 1894 3.40 3.41 3.42 3.42 3 100 0.060 14 3342 3.40 3.40 3.42 3.38 4 175 0.008 14 780 3.41 3.41 3.42 3.42 5 175 0.034 14 3314 3.42 3.41 3.40 3.42 6 175 0.060 14 5849 3.40 3.42 3.41 3.43 7 250 0.008 14 1114 3.38 3.41 3.42 3.43 8 250 0.034 14 4735 3.40 3.41 3.43 3.42 9 250 0.060 14 8356 3.41 3.42 3.39 3.42 Down milling Vf Vc Test 1 Test 2 Test 3 Test 4 f (mm/rev/tooth) z Test (mm/min) (m/min) z 1 100 0.008 14 446 3.39 3.40 3.42 3.38 2 100 0.034 14 1894 3.40 3.42 3.42 3.40 3 100 0.060 14 3342 3.41 3.42 3.41 3.44 4 175 0.008 14 780 3.42 3.40 3.40 3.41 5 175 0.034 14 3314 3.41 3.42 3.41 3.43 6 175 0.060 14 5849 3.40 3.41 3.40 3.42 7 250 0.008 14 1114 3.40 3.40 3.41 3.41 8 250 0.034 14 4735 3.41 3.38 3.40 3.39 9 250 0.060 14 8356 3.40 3.42 3.42 3.41
Test 5
Rat average
3.38 3.41 3.41 3.41 3.42 3.44 3.42 3.39 3.42
3.39 3.41 3.40 3.41 3.41 3.42 3.41 3.41 3.41
Test 5
Rat average
3.42 3.41 3.41 3.39 3.40 3.40 3.39 3.41 3.41
3.40 3.41 3.42 3.40 3.41 3.41 3.40 3.40 3.41
Table 6 Values of longitudinal arithmetic average roughness Ral as a function of cutting parameters Up milling Vc Vf fz Test z Test 1 Test 2 Test 3 Test 4 (m/min) (mm/rev/tooth) (mm/min) 1 100 0.008 14 446 2.37 2.31 2.41 2.30 2 100 0.034 14 1894 6.86 6.78 6.65 6.68 3 100 0.060 14 3342 9.91 9.92 9.80 9.92
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Test 5
Ral average
2.32 6.65 9.88
2.34 6.72 9.89
4 175 5 175 6 175 7 250 8 250 9 250 Down milling Vc Test (m/min) 1 100 2 100 3 100 4 175 5 175 6 175 7 250 8 250 9 250
0.008 0.034 0.060 0.008 0.034 0.060 fz (mm/rev/tooth) 0.008 0.034 0.060 0.008 0.034 0.060 0.008 0.034 0.060
14 14 14 14 14 14 z 14 14 14 14 14 14 14 14 14
780 3314 5849 1114 4735 8356 Vf (mm/min) 446 1894 3342 780 3314 5849 1114 4735 8356
6.06 11.42 16.71 9.60 13.82 21.33
6.12 11.39 16.73 9.96 13.71 21.47
6.26 11.40 16.66 9.97 13.68 21.34
6.23 11.61 16.77 9.96 13.65 21.52
6.21 11.61 16.59 9.95 13.73 21.58
Test 1
Test 2
Test 3
Test 4
Test 5
1.54 8.57 16.58 5.06 19.32 28.54 15.48 28.41 39.36
1.56 8.36 16.60 5.09 19.32 28.62 15.56 28.41 39.38
1.54 8.56 16.73 5.18 19.35 28.60 15.72 28.48 39.28
1.51 8.53 16.80 5.15 19.36 28.40 15.86 28.51 39.25
1.50 8.57 16.79 5.14 19.38 28.59 15.65 28.33 39.32
6.18 11.49 16.69 9.89 13.72 21.45 Ral average
Table 7 ANOVA table for the longitudinal arithmetic average roughness R al in up milling Source of SDQ d.f Variance Test F P(%) F =5% variance Vc (m/min) 114.78 2 57.39 33.97 6.94 41.55 fz (mm/rev/tooth) 146.59 2 73.30 43.38 6.94 53.41 Error 6.76 4 1.69 5.04 Total 268.13 8 100 SDQ :Sum of squares, d.f : degress of freedom, P : percentage of contribution. Table 8 ANOVA table for the longitudinal arithmetic average roughness Ral in down milling Source of SDQ d.f Variance Test F P(%) F =5% variance Vc (m/min) 535.85 2 267.92 40.27 6.94 43.17 fz (mm/rev/tooth) 647.85 2 323.93 48.69 6.94 52.43 Error 26.61 4 6.65 4.40 Total 1210.31 8 100 SDQ :Sum of squares, d.f : degress of freedom, P : percentage of contribution.
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1.53 8.52 16.70 5.12 19.35 28.55 15.65 28.43 39.32
Highlights Transverse roughness depends only on tool geometry. Longitudinal roughness depends on cutting conditions. Feed per tooth is the key factor that influences the roughness values in slotting of CFRP with knurled tool fine toothings. Manufacturers must optimize cutting conditions based on the equations 5 and 6.
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