Rotary ultrasonic machining of woven CFRP composite in a cryogenic environment

Accepted Manuscript Rotary ultrasonic machining of woven CFRP composite in a cryogenic environment S. Thirumalai Kumaran, Tae Jo Ko, Changping Li, Zhen Yu, M. Uthayakumar PII:

S0925-8388(16)34204-9

DOI:

10.1016/j.jallcom.2016.12.275

Reference:

JALCOM 40197

To appear in:

Journal of Alloys and Compounds

Received Date: 30 November 2016 Revised Date:

18 December 2016

Accepted Date: 21 December 2016

Please cite this article as: S. Thirumalai Kumaran, T.J. Ko, C. Li, Z. Yu, M. Uthayakumar, Rotary ultrasonic machining of woven CFRP composite in a cryogenic environment, Journal of Alloys and Compounds (2017), doi: 10.1016/j.jallcom.2016.12.275. 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.

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Burr area measurement

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Camscope (ITPlus 4.06)

Valley

Surface roughness plot

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Mitutoyo SJ-301 roughness tester

Peak

Kistler Dynamometer (type 9256C2)

Thrust force plot

ACCEPTED MANUSCRIPT Rotary ultrasonic machining of woven CFRP composite in a cryogenic environment S. Thirumalai Kumarana, Tae Jo Koa*, Li Changpinga, Yu Zhena, M. Uthayakumarb [email protected], [email protected]*, [email protected], [email protected], [email protected] a

School of Mechanical Engineering, Yeungnam University, 214-1 Dae-dong, Gyeongsan-si,

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Gyeongsangbuk-do 712-749, South Korea. b

Faculty of Mechanical Engineering, Kalasalingam University, Krishnankoil-626 126, Tamilnadu, India.

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*Corresponding Author: Mobile: +82-10-3537-2576, Fax: +82-53-810-4627

ABSTRACT

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In the present study, rotary ultrasonic machining (RUM) was adopted to perform drilling of carbon fiber reinforced plastics (CFRP) in a cryogenic environment. An L27 orthogonal array was selected to conduct experiments by varying the spindle speed (denoted as N), feed rate (denoted as f), and ultrasonic power (denoted as P). The thrust force (denoted as Fz), exit burr area, and surface roughness (denoted as Ra) were measured to evaluate the machining performance. The influence of process parameters and the regression model were

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derived for each output quality response. Additionally, multi-objective optimization was performed using desirability analysis, and the predicted levels were used for confirmation. The results indicated that the feed rate (f) contributed more to the thrust force (Fz) by 45.85 % and a maximum thrust force was recorded at 0.1 mm/rev. A decrease in spindle speed (N)

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was associated with an increase in feed rate (f) and ultrasonic power (P), and it resulted in minimum exit burr area. The influence of ultrasonic power (P) was highly significant in

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reducing burrs with a contribution of 52.45 %. Conversely, the surface roughness (Ra) of the drill holes decreased at 3000 rpm, and this was attributed to the brittle fracture of the fibers at a lower temperature. Both N (30.88 %) and f (30.83 %) had an equal influence on producing a better surface finish in the drill holes. Furthermore, the predicted optimal settings were used to validate the results and were found to be within 95 % confidence and prediction interval. Finally, the microscopic images of tool wear, burr formation, and drill hole surface morphology were analyzed and examined.

Keywords: Rotary ultrasonic machining; carbon fiber reinforced plastics; cryogenic; regression analysis; optimization

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1. INTRODUCTION Carbon fiber reinforced plastics (CFRP) are widely used in various structural applications. They possess high strength and good mechanical properties. The selection of fabrication method, orientation of fibers and its length are determined based on the purpose

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of CFRPs. Generally, a compression molding process is adopted to impregnate carbon fibers with a thermosetting resin. The prepared composite is then machined to a near net shape product with high dimensional accuracy [1]. Although there are several available machining methods, rotary ultrasonic machining (RUM) is preferred due to its lower burr formation, tool

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wear, and surface roughness (Ra). Tool rotation in conjunction with the ultrasonic spindle system performs the machining. Additionally, drilling under a cryogenic environment can

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reduce delamination and produce a burr free entrance and exit [2]. Thus, a novel methodology was adopted in this study to perform the RUM of a CFRP composite in a cryogenic environment.

Several studies focused on RUM by varying parameters such as spindle speed (N), feed rate (f), amplitude, ultrasonic power (P), and frequency. Ning et al. [3] compared output performance during grinding and RUM of a CFRP composite and concluded that the drilling

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by RUM produces lower thrust force (Fz), torque and a better surface finish. Furthermore, RUM was also found to improve the consistency of hole size. Debnath et al. [4] analyzed material removal, tool wear, surface roughness, and hole quality of glass fiber reinforced epoxy laminates during RUM. They reported that material removal increased linearly with an

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increase in power. Moreover, RUM drilling exhibited a better performance when compared with that of conventional drilling. Wang et al. [5] performed a study that examined exit

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chipping of quartz glass and achieved a lower chipping size when drilling with RUM. Additionally, the size of the lateral crack was found to be minimum when compared to that in conventional drilling. Zhang et al. [6] calculated exit chipping size, Fz, and Ra of K9 glass during RUM and reported that chipping size could be controlled at higher N, lower f, and nominal P. The Fz and Ra were also found to be lower than those in conventional drilling, and this was attributed to the ultrasonic spindle system. The selection of Taguchi based orthogonal array ensures that all the factors and levels are weighted equally. The total number of experiments are decided based on the degrees of freedom (number of levels – 1). Generally, full factorial design explores all the possible high/low combinations of all the factors. It also minimizes the possible error and inadequacy

ACCEPTED MANUSCRIPT of the model [7]. Regression analysis is a suitable method to predict a model for output responses based on input parameters. Desirability analysis is also a statistical method that is used to perform multi-objective optimization and to determine an optimal solution. Although several researchers applied these method for various machining processes, only a few studies examined RUM, and no studies, to the best of the authors’ knowledge,

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focused on cryogenic machining. Liu et al. [8] performed RUM on ceramic materials and developed a regression model for exit chipping and tool wear. The results of the desirability analysis indicated that an increased N, decreased f, and decreased P improved output performance. The obtained results were also validated through confirmation experiments.

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Krishnaraj et al. [9] derived a regression model for circularity, diameter, push-up delamination, and peel-up delamination during high speed drilling of CFRP laminates. Multi-

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variant optimization was also performed to predict suitable input parameters that minimized output responses simultaneously. They concluded that N at 12000 rpm and f at 0.137 mm/rev resulted in an optimum output response. Merino-Pérez et al. [10] assessed the influence of cutting speed on tool wear during drilling of CFRP composites using uncoated WC-Co tools. The predicted model was observed to correspond well with the design with reduced error. Gaitonde et al. [11] developed a second order regression model to predict the delamination

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factor during high speed drilling of CFRP composite. The correlation coefficient was predicted as 0.922, which indicates an excellent goodness-of-fit at 90% confidence level. The R2 value can further be increased by the proper selection of N, f and point angle of the drill bit.

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In the present study, a CFRP composite was subjected to RUM in a cryogenic environment to examine Fz, exit burr area, and Ra. The influence of each process parameter

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was analyzed, and the microscopic images of burr formation and the tool wear were obtained. Drill hole surface of the composite was examined using Scanning Electron Microscopy (SEM). The regression model was also developed, and multi-objective optimization of process parameters was performed using desirability analysis.

2. MATERIAL AND METHODS 2.1 Experimental procedure In the present study, a multidirectional woven fabric CFRP composite with a fiber volume fraction of 0.6 was used. The orientation of each layer of the carbon fiber corresponded to 0° and 90° as shown in Figure 1. The Korea Institute of Carbon Convergence

ACCEPTED MANUSCRIPT Technology supplied the CFRP composite and the tensile (ASTM D638 – 14) and compression (ASTM D695 – 15) strengths are shown in Table 1. The fabrication involved compression molding followed by curing at high temperatures. The prepared composites

Table 1 Material properties of CFRP

840 MPa 570 MPa 61.5 GPa 3.7 GPa 0.3 155 kg/m3 70 – 75 HRB

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Longitudinal (σ1t) and traverse tensile strength (σ2t) Longitudinal (σ1c) and traverse compression strength (σ2c) Young’s modulus Shear modulus Poisson’s ratio Density Rockwell hardness

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were then cut to required dimensions that corresponded to 90 mm x 90 mm x 6 mm.

Figure 1 The woven CFRP composite

A CNC machine (DMC model SS-600) with a G-NTS ultrasonic spindle system that possessed frequency and power ranges corresponding to 20–40 kHz and 0–100 %, respectively, was used to conduct the tests. A 6 mm diameter tungsten carbide drill bit with a helix angle of 30° and a point angle of 118° was selected to drill the CFRP composite. The cryogenic environment was achieved using liquid nitrogen (LN2) that was sprayed on the surface of the composite as shown in Figure 2. An L27 array was selected by varying N (800, 1500, and 3000 rpm), f (0.01, 0.05, and 0.1 mm/rev), and P (20, 40, and 60%) to measure and analyze Fz, exit burr area, and Ra.

ACCEPTED MANUSCRIPT During the experiment, the cutting force was measured using a Kistler dynamometer (type 9256C2). Figure 3 shows the typical plot of Fz during machining. The burr area was measured using an optical microscope, and a profilometer (Mitutoyo model SJ-301) was used to measure the Ra value. The probe was moved 5 mm in the traverse direction on the cut

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surface of the drill hole in a range of 350 µm
and at a speed of 0.25 mm/s.

Amplifier

Date recorder

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Figure 2 Experimental setup

Figure 3 A typical thrust force plot

2.2 Regression analysis and Desirability function Regression model and desirability analyses were performed for individual responses and multi-objective optimization, respectively. Multi-linear regression analysis was

ACCEPTED MANUSCRIPT performed to obtain results corresponding to Fz, exit burr area, and Ra using MINITAB® 17 software. The regression model for the dependent variable can be expressed as follows:

Output response = β0 + ∑

β X + ∑∑

β X X

(1)

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βX +

where k denotes the total number of factors, β0 denotes the intercept coefficient, and βi, βii, and βij denote the linear, squared, and interaction effects, respectively [12]. The observed results of the output response could be expressed in terms of the input parameters N, f, and P.

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Thus, the relationship between the input parameters and the output quality response can be written as follows:

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Output response = b0 + b1N + b2f + b3P + b11N2 + b22f2 + b33P2 + b12N*f + b13N*P + b23f*P (2)

The desirability function (di (yi)) is an optimization technique that assigns a number between 0 and 1 for each response (yi (x)). If the value corresponds to 0, then the response is

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completely undesirable, and if the value corresponds to 1, then the response is desirable or ideal [13]. The overall desirability (D) combines the mean of all the responses, which can be expressed as follows:

(3)

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D = (d1 (y1) * d2 (y2) * ……… dk (yk)) 1/k

Based on the response, the di (yi) involved a certain objective, such as maximization or

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minimization. In this study, minimization was set as the target for all the three output responses.

3. RESULTS AND DISCUSSION 3.1 Thrust force In RUM, the generation of Fz can be explained in four different stages. In the initial stage, the Fz increases gradually as the drill tool touches the first layer of the laminate and starts the drilling process. In stage II, the cutting edges of the drill tool completely penetrate into the CFRP composite, and the drilling process continues. A steady Fz value is also obtained at this stage, and the maximum Fz is recorded. In stage III, the drill tool reaches the

ACCEPTED MANUSCRIPT exit region of the composite, and thus Fz decreases with respect to time or cutting distance. Finally, the tool is retracted in stage IV, and the smoothening/finishing process occurs. Figure 4 shows the contour plots for Fz relative to varying input parameters. Evidently, the increase in N and P significantly reduced Fz. The reduced frictional contact in the work interface and the chip removal mechanism controlled the Fz value. Furthermore, the energy

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was minimized by the minimum cutting strain that developed during the drilling with the 118° point angle tool. The vibration caused due to the ultrasonic power reduced axial stress and minimized force generation during drilling. Similar results were observed by Feng et al. [14] by performing the RUM on CFRP composites. When P and N were set to maximum, the

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force generated was in control. Conversely, the increase in feed rate resulted with a maximum Fz value. However at 0.01 mm/rev, the burr formation was increased with increased spalling

with minimum entrance and exit burrs.

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and fuzzing effect. Thus, the proper selection of f is necessary to achieve a lower Fz value

Although the results were satisfactory, the Fz values that developed in the cryogenic environment were considerably higher than those in a conventional RUM. It was due to the increase in thermo-mechanical properties of the CFRP composite at lower temperatures. However, the tool wear was controlled in this process when compared to that in the dry RUM.

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Figure 5 shows the wear morphology of the tool at various feed rates. An outer corner wear was observed during drilling at 0.01 mm/rev. A further increase in the f resulted in the formation of some amount of severe crater wear along with the flank and margin wear. Thus, the results proved that a lower f value achieved minimum Fz and tool wear. However, Cong

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et al. [15] determined the feasible regions of RUM on CFRP composite with cold air as coolant. They concluded that the dry machining is not possible at higher P combined with

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lower f condition. Thus the role of LN2 is essential in this study.

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P (%)

f (mm/rev)

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N (rpm)

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P (%)

N (rpm)

f (mm/rev)

Figure 4 Contour plots of the thrust force

0.05 mm/rev

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0.01 mm/rev

Margin wear

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Flank wear

0.1 mm/rev

Outer corner wear

Crater wear Crater wear

Figure 5 Tool wear

The regression model for Fz was predicted, and R2 and Adj R2 values corresponded to 97.31% and 95.89%, respectively. This indicated that the predicted model exhibited a good fit at the 95% confidence level. Equation 4 shows the model derived for Fz as a function of N, f, and P as follows:

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Fz (N) =

79.21 – 0.01200N + 165.8f – 0.482P + 0.000002N2 + 179f2 + 0.00167P2 – 0.01282N*f + 0.000073N*P – 0.861f*P

(4)

3.2 Exit burr area

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It is necessary to study the burr area at the entrance and exit regions of the drill hole to evaluate the quality. Throughout the experiments, a burr free entrance hole was observed and was attributed to the cryogenic environment. The surface hardening effect on the CFRP composite led to brittle fracture. Conversely, at 0.01 mm/rev, minimum edge delamination

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was observed due to the loss of mechanical toughness. However, the ultrasonic spindle system assisted in reducing the delamination factor and enhanced the quality of the entrance

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region by producing burr free holes.

Figure 6 shows the contour plot of the exit burr as a function of input parameters. A lower speed with increased f and P resulted in a minimum exit burr area. The increased f produced better hole quality and burr free surface due to increased shear modules and transverse strength of the CFRP at a lower temperature. The P also played a crucial role in deciding the exit burr. At 20 % power, peel up delamination was observed at the exit surface

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and was gradually controlled as f reached 0.1 mm/rev. Increased vibration along with the feed force helped in eliminating spalling and fuzzing on the drill hole surface. Figure 7 shows the exit burr formation at 800 rpm with varying f and P. Although the burr area was reduced at 800 rpm, it had a less significant effect on the quality. The obtained results indicated an

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improvement of less than 10 % when comparing with those of the experiments conducted at 3000 rpm. Thus, a reduced exit burr area as low as 0.02 mm2 was achieved with 800 rpm, 0.1

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mm/rev, and 60 % power. Similar study was performed by Cong et al. [16] on CFRP composites to evaluate the drill hole surface quality. The difference in hole quality produced by dry machining and with coolant (cutting fluid and cold air) were assessed. They suggested that the dry machining is not recommended to produce burr free surface. The uncut resin was predominantly observed at the exit hole surface. The carbon fibers were removed substantially during RUM in the cryogenic environment, and this led to the minimum burr area. The fraying and chipping of fibers were also not visible during the experiments. Thus, the proposed machining study reduced the damage induced on the CFRP composite.

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P (%)

f (mm/rev)

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N (rpm)

f (mm/rev)

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P (%)

N (rpm)

Figure 6 Contour plots of the exit burr area

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0.05 mm/rev

60%

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0.01 mm/rev

40%

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20%

0.1 mm/rev

Figure 7 Microscopy of exit burr formation at 800 rpm

ACCEPTED MANUSCRIPT The regression model for the exit burr area was predicted, and the R2 and Adj R2 values corresponded to 96.75% and 95.03%, respectively. Thus, the predicted model had an alpha value less than 0.05, which confirmed the level of confidence. Equation 5 shows the model derived for the exit burr area as a function of N, f, and P as follows: 2.537 + 0.000505N – 15.68f – 0.0734P – 0.000001N2 – 34.8f2

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Burr area (mm2) =

+ 0.000461P2 – 0.001303N*f – 0.000004N*P + 0.3574f*P

3.3 Surface roughness

(5)

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The study of the drill hole Ra of the CFRP composite was essential as it determined the dimensional quality of the machined composite part. It also played a vital role when there

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was a need for aesthetic and precise requirements. However, the measurement of Ra in the CFRP composite was less reliable than that in metals [17]. The protruding fibers in the drill hole often became intertwined with the stylus. This could cause some additional error during the measurement and increased the roughness.

Figure 8 shows the influence of process parameters on Ra. An increase in N and P values resulted in a better hole finish. It should be noted that the high-speed ultrasonic spindle

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system removed the uncut fibers due to brittle fracture. Additionally, LN2 increased the fragility of the fibers and caused a better removal mechanism. This ultimately reduced the exposed fibers on the drill hole and improved the surface finish. Conversely at 0.1 mm/rev, the Ra deteriorated due to the surface rupture. The mechanism of fiber removal followed the

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combination of shearing and plastic deformation. Although the exit burr area was minimum at a higher f, the heavy impact force led to the removal of a greater chunk of material in the

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hole surface and produced a deeper crater. This aggravated and formed micro cavities in the CFRP composite and increased the Ra. A huge deviation was also observed between the peak and valley from the mean line during measurement using the profilometer. Hence, the induced profile height deviation was the main reason for the poor drill hole surface finish. Finally, it was concluded that the Ra could be minimized while drilling with N at 3000 rpm, f at 0.01 mm/rev, and P at 60 %.

N (rpm)

f (mm/rev)

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P (%)

N (rpm)

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P (%)

f (mm/rev)

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Figure 8 Contour plots of surface roughness

The wall surface of the drill hole was examined by SEM images as shown in Figure 9

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(a–c). Evidently, the formation of broken fibers and the surface rupture were predominantly observed during drilling at a higher f condition. Traces of fine groves and flaws were also observed. Additionally, a severe plastic deformation resulted with a poor surface finish on the drill hole. However at 0.01 mm/rev, the strong interfacial bond between the fibers and resin

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resisted surface damages and produced minimum roughness.

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Strong interfacial bond

Smooth surface Carbon fibers

(a) 0.01 mm/rev

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Plastic deformation

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(b) 0.05 mm/rev

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Broken carbon fiber

Broken carbon fibers

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Surface rupture

(c) 0.1 mm/rev

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Figure 9 SEM images of the drill hole surface

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The regression model for Ra was predicted, and the R2 and Adj R2 values corresponded to 94.49% and 91.57%, respectively. The model almost fitted the design, and it can be improved by ignoring inappropriate or insignificant sources. This can help in reducing the error deviation between the experimental and predicted values. Therefore, the predicted model could satisfy the 95% confidence level with suitable modifications. Equation 6 shows the model derived for Ra as a function of N, f, and P as follows:

Ra (µm) =

2.933 – 0.000231N + 6.44f – 0.00892P + 0.000001N2 – 2.9f2 + 0.000082P2 – 0.001386N*f – 0.000002N*P – 0.0278f*P

(6)

ACCEPTED MANUSCRIPT 3.4 Analysis of Variance (ANOVA) test The adequacy of an ANOVA model is checked for each output response. Typically, the probability term should be less than 0.05 to confirm significance. The experimental F values should also be greater than the calculated values. Table 2 shows the ANOVA results for the Fz and the outcome. The F-values of N, f, and P were considerably high, and this confirmed

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that the data were satisfactory. The p-value of the linear effects also indicated a similar influence on Fz. However, the results indicated that squared effects, such as f2, P2, and interaction effects, such as N*f and f*P exceeded 0.05. Thus, these sources were found to be insignificant with respect to Fz. The results also revealed that the f contributed more with

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respect to the effect on Fz by 45.85 %. Table 3 shows the ANOVA model for the exit burr area. The F-value of P was substantially high and was considered to exhibit a greater

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influence on the exit burr area. The contribution corresponded to 52.45 % with respect to minimizing the output and producing better quality holes. The significance of linear effects were observed given their respective p-values, whereas squared and interaction effects, such as N2, f2, and N*f were not significant. Table 4 shows the ANOVA model for the Ra. As shown in the table, the N and P significantly contributed towards the Ra by 30.88 % and 30.83 %, respectively. Hence, properly selecting these factors helps in producing a better

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surface finish. Sources such as f2, P2, and f*P were found to be insignificant based on their pvalues. However, all other linear, squared, and interaction effects contributed significantly with respect to Ra.

Degree of freedom 9 1 1 1 1 1 1 1 1 1 17 26

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Source

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Table 2 ANOVA for thrust force

Regression N f P N2 f2 P2 N*f N*P f*P Error Total

Sum of Mean squares square 1286.45 142.939 51.2 51.2 33.77 33.77 30.56 30.56 24.76 24.76 0.77 0.77 2.67 2.67 5.07 5.07 31.93 31.93 7.23 7.23 35.55 2.091

F-value

p-value

68.35 24.48 16.15 14.61 11.84 0.37 1.28 2.42 15.27 3.46

0.000a 0.000a 0.001a 0.001a 0.003a 0.553b 0.274b 0.138b 0.001a 0.080b

Contribution (%) 97.31 7.25 45.85 38.73 1.87 0.06 0.20 0.38 2.41 0.55 2.69 100.00

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Significant; bNot significant Table 3 ANOVA for exit burr area p-value

56.23 5.41 18.02 42.22 0.86 1.73 12.17 3.12 7.09 74.37

0.000a 0.033a 0.001a 0.000a 0.368b 0.206b 0.003a 0.095b 0.016a 0.000a

Contribution (%) 96.75 1.36 23.95 52.45 0.16 0.33 2.33 0.60 1.36 14.22 3.25 100.00

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F-value

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Mean square 0.94291 0.09074 0.30221 0.70797 0.01437 0.02897 0.20412 0.05237 0.11886 1.24701 0.01677

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Degree of Sum of freedom squares Regression 9 8.48623 N 1 0.09074 f 1 0.30221 P 1 0.70797 2 N 1 0.01437 2 f 1 0.02897 2 P 1 0.20412 N*f 1 0.05237 N*P 1 0.11886 f*P 1 1.24701 Error 17 0.28506 Total 26 a b Significant; Not significant Source

Table 4 ANOVA for surface roughness Degree of Sum of freedom squares Regression 9 1.0269 N 1 0.01888 f 1 0.05093 P 1 0.01045 2 N 1 0.02596 f2 1 0.00019 P2 1 0.00645 N*f 1 0.05925 N*P 1 0.01720 f*P 1 0.00755 Error 17 0.05992 Total 26 a b Significant; Not significant

Mean square 0.1141 0.01888 0.05093 0.01045 0.02596 0.00019 0.00645 0.05925 0.01720 0.00755 0.00352

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Source

F-value

p-value

32.37 5.36 14.45 4.97 7.37 0.06 1.83 16.81 4.88 2.14

0.000a 0.033a 0.001a 0.043a 0.015a 0.817b 0.194b 0.001a 0.041a 0.162b

Contribution (%) 94.49 30.88 22.04 30.83 2.39 0.02 0.59 5.45 1.58 0.69 5.51 100.00

3.5 Desirability analysis The minimization of an objective could deteriorate other output responses. Hence, the proper selection of input parameters is essential in simultaneously obtaining a better quality outcome. Multi-objective optimization was performed to determine the optimum input

ACCEPTED MANUSCRIPT parameters to achieve a lower Fz, exit burr area, and Ra. The desirability analysis shown in Figure 10 reveals the idealness of the design with an overall desirability value that corresponds to 0.9405. The results also indicated that the desirability of each output response exceeded 0.9. An optimal input parameter predicted in this approach produced better responses concurrently (N = 2398.5961 rpm, f = 0.0138 mm/rev and P = 58.6121 %). When

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the predicted conditions were used for the experiments, they were expected to achieve a 50.654 N thrust force, 0.1572 mm2 exit burr area, and 2.2907 µm surface roughness. Thus, lower-the-better performance characteristics of all the variables were achieved through this design. The confirmation experiment was also conducted to validate the results (Table 5).

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Optimal settings were used for the experiment, and the observed results were found to be within a 95 % confidence and prediction interval. Hence, the targets of minimization for all

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the three output responses were achieved.

Figure 10 Desirability analysis

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Table 5 Confirmation experiment Predicted value

Fz Exit Burr Ra

50.654 0.1572 2.2907

Confirmatory experimental results 52.4 0.25 2.324

4. CONCLUSIONS

95 % Confidence interval Low High 48.209 52.086 0.0500 0.2899 2.2008 2.3600

95 % Prediction interval Low High 46.532 53.762 0.2073 0.4400 2.1320 2.4288

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Response

Rotary ultrasonic machining was performed on a woven CFRP composite in a

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cryogenic environment to investigate thrust force, exit burr area, and surface roughness. A regression model was developed for each output response, and the optimum levels of input

from the observed experimental results: •

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parameters were predicted using desirability analysis. The following conclusions were drawn

The RUM in a cryogenic environment was superior as it produced a lower exit burr area and Ra. Conversely, a very high Fz was recorded, and this was attributed due to the increase in thermo-mechanical properties of the CFRP composite.

•

The increase in N and P generated a minimum Fz because of the reduced axial stress. Fz

mm/rev. •

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was highly influenced by f (45.85 %), and a minimum tool wear was observed at 0.01

The contribution of P was significantly high (52.45 %) in minimizing the exit burr area.

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Increased vibration along with the feed force helped in producing better hole quality. Further, enhanced shear modules and transverse strength of the CFRP at a lower temperature reduced peel-up delamination. Brittle fracture during ultrasonic drilling of the CFRP at 3000 rpm resulted in a lower Ra.

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•

The influence of both N (30.88 %) and f (30.83 %) were significant in producing a better surface finish in the drill holes. Additionally, the failure of the CFRP composite was verified from the SEM images. •

The confirmation experiment was performed with optimal input parameters (N = 2398.5961 rpm, f = 0.0138 mm/rev and P = 58.6121 %), and the results indicated that the observed results were within the 95 % confidence and prediction interval.

ACCEPTED MANUSCRIPT 5. ACKNOWLEDGEMENTS This work was supported by the Human Resource Training Program for Regional Innovation and Creativity through the Ministry of Education and the National Research Foundation of Korea (NRF–2014H1C1A1066502).

1.

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Jianjian Wang, Huiting Zha, Pingfa Feng, Jianfu Zhang. On the mechanism of edge

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5.

chipping reduction in rotary ultrasonic drilling: A novel experimental method. Precision Engineering 2016, 44, 231-235. 6.

Chenglong Zhang, Weilong Cong, Pingfa Feng and Zhijian Pei. Rotary ultrasonic

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machining of optical K9 glass using compressed air as coolant: A feasibility study. Journal of Engineering Manufacture 2014, 228 (4), 504-514. S Thirumalai Kumaran, M Uthayakumar, Adam Slota and Jerzy Zajac. Application of

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7.

grey relational analysis in high speed machining of AA (6351)-SiC-B4C hybrid composite 2015, 51 (1), 17-31. 8.

Jun Wei Liu, Dae Kyun Baek and Tae Jo Ko. Chipping minimization in drilling ceramic materials with rotary ultrasonic machining. International Journal of Advanced Manufacturing Technology 2014, 72 (9), 1527-1535.

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Vijayan Krishnaraj, A. Prabukarthi, Arun Ramanathan, N. Elanghovan, M. Senthil Kumar, Redouane Zitoune and J.P. Davim. Optimization of machining parameters at high speed drilling of carbon fiber reinforced plastic (CFRP) laminates. Composites: Part B 2012, 43, 1791-1799.

ACCEPTED MANUSCRIPT 10. Julián Luis Merino-Pérez, Eleanor Merson, Sabino Ayvar-Soberanis and Alma Hodzic. The applicability of Taylor’s model to the drilling of CFRP using uncoated WC-Co tools: the influence of cutting speed on tool wear. Machining and Machinability of Materials 2014, 16 (2), 95-112. 11. V. N. Gaitonde, S. R. Karnik, J. Campos Rubio, A. Esteves Correia, A. M. Abrão and J.

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Paulo Davim. Analysis of parametric influence on delamination in high-speed drilling of carbon fiber reinforced plastic composites. Journal of Materials Processing Technology 2008, 203 (1-3), 431-438.

12. Ashvin J. Makadia and J. I. Nanavati. Optimisation of machining parameters for turning

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operations based on response surface methodology. Measurement 2013, 46 (4), 15211529.

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13. Murat Sarıkaya and Abdulkadir Güllü. Taguchi design and response surface methodology based analysis of machining parameters in CNC turning under MQL. Journal of Cleaner Production 2014, 65, 604-616.

14. Q. Feng, W. L. Cong, Z. J. Pei and C. Z. Ren. Rotary ultrasonic machining of carbon fiber-reinforced polymer: feasibility study. Machining Science and Technology 2012, 16 (3), 380-398.

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15. W.L. Cong, Z.J. Pei, T.W. Deines and C. Treadwell. Rotary ultrasonic machining of CFRP using cold air as coolant: feasible regions. Journal of Reinforced Plastics and Composites 2011, 30 (10), 899-906.

16. W.L. Cong, Q. Feng, Z.J. Pei, T.W. Deines and C. Treadwell. Rotary ultrasonic

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machining of carbon fiber-reinforced plastic composites: using cutting fluid vs. cold air as coolant. Journal of Composite Materials 2012, 46 (14), 1745-1753.

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17. Kishore Debnath, Inderdeep Singh and Akshay Dvivedi. Rotary mode ultrasonic drilling of glass fiber-reinforced epoxy laminates. Journal of Composite Materials 2015, 29 (8), 949-963.

ACCEPTED MANUSCRIPT Highlights

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Prediction of regression model for RUM of CFRP in a cryogenic environment. Output responses such as thrust force, burr area and roughness are investigated. The adequacy of an ANOVA model is checked for each output response. Optimization is performed by desirability analysis and the results are validated. Tool wear, burr formation, and drill hole surface morphology are analyzed.

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