Machinability evaluation and desirability function optimization of turning parameters for Cr2O3 doped zirconia toughened alumina (Cr-ZTA) cutting insert in high speed machining of steel

Machinability evaluation and desirability function optimization of turning parameters for Cr2O3 doped zirconia toughened alumina (Cr-ZTA) cutting insert in high speed machining of steel

Author’s Accepted Manuscript Machinability Evaluation and Desirability Function Optimization of Turning Parameters for Cr 2O3 doped Zirconia Toughened...

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Author’s Accepted Manuscript Machinability Evaluation and Desirability Function Optimization of Turning Parameters for Cr 2O3 doped Zirconia Toughened Alumina (Cr-ZTA) Cutting Insert in High Speed Machining of Steel B K Singh, B Mondal, Nilrudra Mandal www.elsevier.com/locate/ceri

PII: DOI: Reference:

S0272-8842(15)02034-9 http://dx.doi.org/10.1016/j.ceramint.2015.10.128 CERI11575

To appear in: Ceramics International Received date: 7 August 2015 Revised date: 29 September 2015 Accepted date: 16 October 2015 Cite this article as: B K Singh, B Mondal and Nilrudra Mandal, Machinability Evaluation and Desirability Function Optimization of Turning Parameters for Cr2O3 doped Zirconia Toughened Alumina (Cr-ZTA) Cutting Insert in High Speed Machining of Steel, Ceramics International, http://dx.doi.org/10.1016/j.ceramint.2015.10.128 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 galley proof before it is published in its final citable 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.

Machinability Evaluation and Desirability Function Optimization of Turning Parameters for Cr2O3 doped Zirconia Toughened Alumina (CrZTA) Cutting Insert in High Speed Machining of Steel

B K Singh, B Mondal, Nilrudra Mandal* Centre for Advanced Materials Processing CSIR-Central Mechanical Engineering Research Institute Durgapur-713209, India

*

Corresponding Author Dr. Nilrudra Mandal Scientist Centre for Advanced Materials Processing CSIR-Central Mechanical Engineering Research Institute Durgapur-713209 India Tel.: +91-343-6510218 Fax: +91-343-2546745 E-mail address: [email protected], [email protected]

Abstract In present study, mechanical properties, microstructure and machining parameter optimization of Cr2O3 doped zirconia toughened alumina (ZTA) ceramic insert have been investigated for application in high speed turning of AISI 4340 steel with achieving maximum tool life. The yttria stabilized zirconia (YSZ) in α-Al2O3 matrix with varying percentage of co-doped chromia (Cr2O3) is prepared to study the phase transformation behaviour. The samples are uniaxially pressed in the form of cutting inserts and subsequently sintered at 1600°C to evaluate the mechanical properties. Hardness and fracture toughness reaches the highest value i.e. 17.40 GPa and 7.20 MPa.m1/2 respectively at 0.6 % Cr2O3 doped ZTA due to more

metastable tetragonal ZrO2 phase present in the alumina matrix. After 50 minutes of machining, the flank wear and surface roughness are found well below the tool rejection criteria. The cutting force also does not affect detrimentally on the job-tool interface. Turning experiments have been adopted as per central composite design (CCD) of response surface methodology (RSM) with varying 3 levels of cutting speed (140 m/min , 280 m/min, 420 m/min), feed rate (0.12 mm/rev, 0.18 mm/rev, 0.24 mm/rev) and depth of cut (0.50 mm, 1.00 mm, 1.50 mm). The effect of each input parameter on output responses are investigated using analysis of variance (ANOVA) and modelled using regression analysis. The influence of cutting speed, feed rate and depth of cut is observed maximum for determination of flank wear, cutting force and surface roughness respectively. Cutting speed of 420 m/min with feed rate of 0.12 mm/rev and depth of cut of 0.5 mm has been shown as optimized condition with 83.32% desirability for minimum tool failure and maximum tool life. Keywords: chromia; zirconia toughened alumina; machinability; central composite design; response surface methodology

1. Introduction In metal working industry, as day to day new materials occupies and replaces the old and traditional ones, so, it is very difficult to select an efficient cutting insert for any particular machining application. The performance of cutting tool is dependent on the material to be machined and the type of operation. The supplementary factors that affect the selections of tool are machine tool horsepower, availability of inserts, speed range and rigidity of the machine, tooling budget limitations, productivity demands, machine tool burden rate etc. In order to achieve efficient tool to maintain all the mentioned criteria’s, ceramic inserts have a greater potential due to its high hot hardness, abrasion resistance and chemical stability [1]. From twentieth century, ceramic (alumina) cutting inserts have been used for

machining operation. It was known that only 5% of total tool or inserts used in industries are made up of ceramic (alumina) [2]. To enhance the use of ceramics tool, it is very much imperative to eliminate the hurdles that limit its use. The major problem associated with ceramics inserts has its low toughness and catastrophic failure [3]. Xing Li et al [3] have found a premature or catastrophic failure in cutting inserts by using monolithic Al2O3 due to high stress at high elevated temperature as well as high shock experienced by the cutting edge and face. Hence, to enhance the toughness of the materials, some additives such as yttria stabilised zirconia (YSZ) [4], titanium carbide [5], titanium nitride [6], carbon [7] and ceria [8] have been added to alumina matrix. It is also illustrated by many researchers that the anti wear property of inserts are highly effected by hardness of tool or inserts which can be increased by doping MgO and chromia (Cr2O3) etc to the matrix. As zirconia and alumina is easily available material so ample research has been carried out in the field of zirconia toughened alumina (ZTA) ceramics. ZrO 2 also exists in polymorphism so phase stabilization is essentially required before application of the material. Szutowska et al [9] have revealed that the toughening mechanisms of Al2O3-ZrO2 composite are highly associated with the stress induced phase transformation toughening and microcrack toughening. It is found that the tetragonal phase or second phase of ZrO2 efficiently improve its toughness value. The improvement is also associated with the transformation strengthening method done by phase transformation through mixing with yttria stabilized zirconia (YSZ) [4]. The composite produced by the mixing with YSZ with alumina is known as zirconia toughened alumina (ZTA) and its wear resistance is high due to the transformation toughening mechanism in which the YSZ is surrounded by alumina matrix. It has been also proved that the ZTA has a peculiar phenomena based on polymorphic transformation of ZrO2 (t) tetragonal phase into ZrO2 (m) monoclinic phase during the cooling spam of sintering temperature to room temperature and results in increased value of strength and fracture toughness of ceramics. This improvement may be due to volumetric the t expansion during → m transformation of ZrO2 diffuse in the matrix. The yttria stabilised zirconia (YSZ) in α-Al2O3 increases the fracture toughness of the matrix. There are several other additive materials viz. MgO, NiO, Cr2O3 and TiO2 in α-Al2O3 show increase in fracture toughness of the matrix. Among the additives, chromia (Cr2O3) has a potential to modify the physical properties of alumina. Azhar et al [10] found that chromia doped in alumina forms isovalent solid

solution because both are sesquioxides and have similar corundum crystal structure (approximately hexagonal close-packed oxide ions with the Al3+ and Cr3+ ions capturing two thirds of the available octahedral interstitials sites). While doping of chromia in alumina at high temperature shows complete range of substitution solid solution. It also significantly increases refractoriness and chemical stability [11]. Hardness, tensile strength and thermal shock resistance in chromia doped alumina ceramics is predominantly significant [12]. The increment of grain size and bimodal in size distribution appear when chromia (≈ 2 mol %) is added. It is also found that there is an increase in fracture toughness and flaw tolerance of alumina but decrease in fracture strength. Before machining application, the study of machinability is very much required to be conducted in given work-tool combination. To enhance the productivity and quality of the machined product, it is important to study the different phenomena like surface integrity, tool wear, chip formation and cutting force. In addition to that, development of predictive model for all influencing parameters is also essential to visualise them. Therefore, to manufacture components economically, engineers are trying to find ways for the improvement of machining performance. To achieve high cutting performance, proper selection of optimum parameter is necessary. Generally, the operator’s knowledge or the design data book determines this optimum parameter selection. However, proper experimental data is very limited for machining with the advanced cutting tool. Procedures for statistical design of experiment are quiet extensively used in machinability investigations. Statistical design of experiments refers to the process of planning the experiment, so that the appropriate data can be analyzed by statistical methods, resulting in valid conclusions. Design and methods such as factorial design, response surface methodology (RSM) and taguchi methods are now widely used in place of one factor at a time experimental approach. Benga and Abrao [13] has investigated the surface roughness by using response surface methodology and developed a model by varying cutting speed and feed rate for three different cutting tool i.e. mixed ceramics, whishker – reinforced ceramics and poly crystalline cubic boron nitride (PCBN). It has been found in all three cutting tools, the surface roughness has been affected by feed rate. The similar phenomenon has been observed by Kacal and Yildirim [14] for turning of AISI D6 by ceramics and CBN inserts. Aslan et al [15] has applied analysis of variance (ANOVA) for surface roughness and found that the surface roughness varies with

cutting speed-feed rate and feed rate-depth of cut interactions, for turning of AISI 4140 steel with mixed ceramics inserts. A predictive model has been suggested [16] for utilising neural network and multiple linear regression models to evaluate surface roughness and flank wear in finish turning of AISI D2 steel with wiper ceramic inserts. Meddour et al [17] has investigated and developed a model for cutting force and surface roughness by utilising ANOVA and response surface methodology. In their investigations, inserts made up of mixed ceramics have been used for cutting AISI 52100 steel. The investigation using ANOVA has been performed and it has been concluded that the cutting force is mainly affected by depth of cut followed by feed rate with light contribution. Even though, many research has been carried out for development and machinability investigation of ZTA cutting inserts but little work has been done in respect of chromia addition in ZTA insert. Apart from study the phase purity, density, grain size in terms of doping, machinability investigation has been carried out to visualize the flank wear of the insert, cutting force developed in the time of machining and surface finish of the job. The CCD design of RSM has been employed to model the turning parameters in terms of flank wear, cutting force and surface roughness. ANOVA has been employed to see the effect of each parameter on the responses. Desirability function optimization is utilized to define the optimal machining parameters in high speed machining of AISI 4340 steel using the developed insert.

2. Experimental Details 2.1 Powder Synthesis & Characterization A monolithic Al2O3 (average particle size 60 μm, supplier Merck) is used for preparation Cr2O3 doped ZTA composite material. Yttria Stabilized Zirconia (YSZ) particles (average particle size 1.0 μm, supplier Zirox) is added to Al2O3 matrix with a ratio of 90 wt.% Al2O3 / 10 wt. % YSZ. Samples are synthesized with 0-1 wt % Cr2O3 (average particle size 1 μm, supplier Sigma Aldrich). The powders are wet mixed for 60 min using ultrasonic machine and 30 min using automatic stirrer subsequently. The mixture solution is dried for 24 hr in an oven at 200°C. The powders of Al2O3, YSZ and Cr2O3 are then ball milled for 12 hr using 0.8 wt % of polyethylene glycol

1000 as a plasticizing agent. The morphology of the powders is characterized through particle size analyzer. The powder is calcined at 600°C and sintered at 1600°C for 2 hours. The X-ray diffraction (XRD) of sintered powder at 1600°C is studied for determining the degree of stabilization of phases [18]. In this work, the stabilization of phases is specifically carried out to distinguish between monoclinic and cubic/tetragonal phases at an angle 2θ between 10° and 700.The fraction of tetragonal zirconia is calculated by comparing the peak intensities of Tetragonal phase [101] and Monoclinic phase [111] and [ 111 ] obtained from X-ray diffraction of calcined as well as sintered samples using the following equation 1 & 2 [19]

Vm =

Where, X m =

1.311 X m (1 + 0.311 X m )

(1)

I m (111) + I m (111) X100 I m (111) + I t (101) + I m (111)

(2)

Where, Vm is the volume fraction of monoclinic ZrO2, I = integrated intensity of the respective diffracting plane, Xm is the intensity of m-ZrO2 with respect to total ZrO2, subscript m and t stands for monoclinic and tetragonal ZrO2. The crystallite size of the powder is measured from X ray line broadening analysis using Scherrer’s formula [20]

D=

0.9 l B cos q

(3)

Where, D is the crystallite size, λ is the wavelength of the radiation, θ is the Bragg's angle and B is the full width at half maximum. 2 2 B 2 = Bmeas - Binst

(4)

Where, Bmeas = Observe full width at half maximum from peak values and Binst = Instrumental broadening. 2.2 Fabrication and Sintering of Cutting Insert The tool inserts are prepared after uniaxially compaction of milled powder with a pressure of 5 ton cm-2 in a hydraulic press (Make: Carver, USA). It has been compacted into a designed square shaped (16 mm x 16mm x 6mm) pellets with a die. The drawing of the same is portrayed in Fig 1.

The compacts are sintered at 1600-1625°C with soaking time of 3 hrs in an air atmosphere. The diamond wheel is used to reduce the specimen size in tailor made designed Jig-Fixture and polished slowly to make the inserts very close to the international standard SNUN 120408 (ISO). Finally, the inserts are polished with fine diamond paste (0.5-1.0 µm) in polishing machine. A flat land of angle 20 deg and width of 0.2 mm has been given on each cutting edge to impart edge strength to the inserts. The light honing is also tried on the sharp edges to make rounding off. The final shape of Cr-ZTA insert is depicted in Fig 2. Archimedes Principle is used to calculate apparent porosity and bulk density of the sintered specimens. Sintered samples are weighed in dry state. After that, samples are immersed in kerosene and kept under vacuum of 4 mm of mercury for two hours for filling the pores completely with kerosene. Then, soaked (in kerosene) and suspended samples are weighed. From the measured weight, the apparent porosity and bulk density is calculated as follows:

Dry weight of the samples =Wd Soaked weight of the samples =Ws Suspended weight of the samples =Wa % ApparentPorosity = Bulk Density =

Ws - Wd X100 Ws - Wa

Wd Ws - Wa

(5) (6)

The grain size is determined using a rectangular intercept procedure, following the ASTM E112-88 standard. The average grain size G is calculated by using the following mathematical expression:

G=

4A 3.14 (ni + n0 2)

(7)

where, A is the area of rectangular section, ni and n0 are the grain numbers within the rectangular section and on the boundary respectively. FESEM image of sintered surface of Cr2O3-ZTA insert is taken in Field Emission Scanning Electron Microscope (FESEM) (CARL-ZEISS-SMT-LTD, Germany, Model: SUPRA 40). The hardness of the materials is calculated from the size of the impression produced under load by a pyramid-shaped diamond indenter. The indenter employed

in the Vickers test is a square-based pyramid whose opposite sides met at the apex at an angle of 136°. The diamond is pressed into the surface of the material at loads ranging up to approximately 2 Kgf. The size of the impression (usually no more than 0.5 mm) is measured with the aid of Vickers hardness testing machine Matsuzwa, MXT-70. The Vickers number (HV) is calculated using the following formula [21]

HV =1.854 ( F / D 2 )

(8)

Where, F is the applied load (measured in Kgf) and D 2 is the area of the indentation (measured in mm2). Fracture toughness is also determined by the Vickers indentation technique. KIC is measured by the indentation method, where the length of cracks emerging from the Vickers indentation corners. KIC is calculated using the expression proposed by Evans and Charles in 1976 [22] The fracture toughness KIC is estimated using the equation

K IC = 0.16 (c / a) -1.5 ( Ha 0.5 )

(9)

KIC

= Fracture toughness (MPa•m1/2)

H

= Vickers hardness (MPa)

P

= Test load in Vickers hardener (Newton)

c

= Average length of the cracks obtained in the tips of the Vickers marks

(microns) a

= Half average length of the diagonal (microns)

2.3 Machinability Evaluation The NH-26 lathe (Make: HMT Ltd, India) powered by an 11 KW motor and speed range of 47-1600 RPM is used for turning experiments (Fig 3). The initial diameter of the AISI 4340 steel bar (Hardness 48 HRC) used for machining is 150 mm and the length is 470 mm. The tool holder used is CSBNR2525N43 (Make: NTK) with tool angles -6°, -6°, 6°, 6°, 15°, 15° and 0.8. A piezoelectric dynamometer (Make: Kistler, 9272) fitted in a developed fixture is used for the measurement of cutting forces (Fz). It has been calibrated in the range of 0 to 5000 Newton. A charge amplifier (Make: Kistler, 5015 A) is used to display the

amplified value of force from charge rating using Dynoware software. Cutting force is also measured three times in same speed and average of the same has been taken for machinability investigation. The surface roughness of the AISI 4340 steel has been measured by the portable surface roughness tester SURTRONIC 25. The direction of the roughness measurement is perpendicular to the cutting velocity vector. A total of five measurements of surface roughness are taken at random on each machined surface and the average value is used in the analysis. Flank wear is one kind of abrasive wear caused by abrasive action of the hard work piece material with the cutting inserts. The flank wear is characterized by the abrasive groove and ridges on the flank face of the tool. The flank wear land is measured from the position of the original major cutting edge using a Tool Makers Microscope (Make: Leica, Germany) with X 30 to X 150 magnification and 1 micron resolution. 2.4 Statistical Modelling using Response Surface Methodology Response surface methodology is a modelling technique in which the relationship among different parameters with several responses is determined. It is also helpful for searching out the significance of each parameter and the extent of each on the individual responses. In the present investigation, as the cutting inserts are newly developed and non-isotropic in nature so machinability investigation is very much important before application in high speed turning. In this investigation, cutting speed, feed rate and depth of cut are identified as process parameters which affect the responses such as cutting force produced at the time of turning, surface roughness of job and flank wear of the inserts which are the main criteria for investigation of machinability of material. The effects of the parameters on the responses are tested through a set of planned experiments based on 3 levels 3factor central composite design for mapping it in the quadratic response surfaces. The parameters and their levels are depicted in Table 1. The response function representing the performance can be expressed as

Y = y (V, F, D)

(10)

Where, Y is the desired response and Ψ is the response function. In the present study the CCD based models for each response has been developed with cutting speed, feed rate and depth of cut. The second order regression equation was used to represent the response surface for M factors is given by

m

Y = a0 + å ai X i + i =1

m

m

å aij X i X j + å aii X i2

i , j =1

(11)

i =1

Where, a 0 is the free term of the equation, the coefficients a 1, a2…………… am are linear terms; a11, a22 ………… amm are quadratic terms; and a12, a13……………am-1,m are the interaction terms. For three factors, the selected polynomial could be expressed as Y=a0 + a1V + a2F + a3D + a12VF + a13FD + a23VD + a11V2 + a22F2 + a33D2

(12)

The values of the coefficients of the polynomial of equation (12) are calculated by the regression method. 3. Result & Discussion 3.1 Material Characterization A typical XRD of 0.6 wt % Cr2O3 in ZTA has been portrayed in Fig 4. The stabilization of the phases has been studied for different wt % of Cr 2O3 in ZTA at low angle of 2θ between 27° to 35° especially to distinguish between monoclinic (mZrO2) and cubic/tetragonal phases (c-ZrO2/t-ZrO2) as depicted in Fig.5 and to determine the crystallite size of the samples. The phase transition, density, crystallite size, and grain size of different wt% of Cr2O3 doped ZTA have been listed in Table 2.
From the table, it is clearly shown that the formation of stabilized zirconia, especially tetragonal zirconia (t-ZrO2) is present in all the samples and with the increase wt% of Cr2O3 the t-ZrO2 phase increases. The trend of t-ZrO2 retention is also similar to that observed for density variation. The mechanical characterization i.e. determination of hardness and fracture toughness has been carried out to correlate the phases with mechanical strength. The values are shown in Table 3. The metastable tetragonal phase in α-Al2O3 matrices plays a vital role for enhancing the fracture toughness and hardness of the material. In this table, it is clearly seen that significant improvement in hardness and fracture toughness for increasing wt % of Cr2O3. It has been observed when Cr2O3 content reaches to 0.6 wt% then both hardness and fracture toughness reaches the highest value i.e. hardness of 17.40

GPa and fracture toughness of 7.20 MPa.m1/2. The hardness and fracture toughness of alumina–zirconia composites depends on the morphology and distribution of zirconia particles, their size, shape, location in alumina matrix, and size distribution, which are critically influenced by the processing methodology and additive content as stabilizer. From the study of Azhar et al. [10], it can be concluded that the increase of hardness from 0 to 0.6 wt % occurs due to formation of isovalent solid solution between Al3+ and Cr3+ for their same corundum structure. The hardness of ZTA-Cr2O3 is also higher than yttria stabiles ZTA insert [23-24] earlier prepared by the author and same trend is also reported by Riu et al. [12]. When the wt % of Cr2O3 increases more than 0.6 % then due to the separation of the matrix, pore formation occurs in the samples [10]. Though the tetragonality factor is more in 1 wt % Cr2O3ZTA than 0.6 wt % Cr2O3-ZTA, but the higher fracture toughness can be seen in 0.6 wt

%

Cr2O3-ZTA

due

to

more

metastable

tetragonal

ZrO2

than

stable

tetragonal/cubic phase which in turn expands the volume and restrict the crack propagation. This transformation toughening phenomena increases the fracture toughness of the materials [18]. The same phenomenon has been reported by Azhar et al. [10] where it has been stated that after 0.6 wt % Cr2O3 the specimens behaves like an undoped samples due to vaporization and condensation of Cr 2O3 in pressure less sintering [25-27]. The FESEM image of 0.6 wt % Cr2O3 doped ZTA is shown in Fig 6. It has been clearly seen that YSZ and Al2O3 grain are well distributed among each other with few agglomeration of particle [4, 28]. Cr2O3 particle is not visible for their low wt % in the matrix but EDAX analysis only confirms the existence of same. The image of crack propagation is also seen in inset of FESEM image for determination of fracture toughness and hardness with an indentation in the sample. 0.6 wt. % Cr2O3-ZTA inserts have been selected for machining AISI 4340 steel due to their better mechanical properties. 3.2 Machinability Evaluation Flank wear is measured perpendicular to the major cutting edge and from the position of the original major cutting edge after 5 minutes and 10 minutes of operation and then after 10 minutes interval up to 50 minutes of machining using same operating condition for each inserts. The flank wear values at different speed

have been shown in Fig 7. It is predominant that after 40 minutes of machining the increment of flank wear is not very significant. It is also to be noted that at high speed i.e. 420 m/min, the Cr-ZTA provides better flank wear values than pure ZTA inserts. The tool rejection criteria for machining operation are considered from ISO Standard 3685 for tool life testing [29] .i.e. Average Flank Wear > 0.4 mm Maximum Flank Wear > 0.7 mm During the machining operation, the observed average and the maximum flank wear values are below the respective stipulated tool rejection criterion at all cutting conditions. The photograph of flank wear observed during machining is depicted in Fig 8. Any catastrophic failure of cutting tools is not observed during the machining process. Kumar et al.[30] compared the flank wear of ZTA insert with Ti [C, N] mixed alumina insert and it has been observed that the flank wear value of 0.34 mm for ZTA insert and 0.32 mm for Ti [C, N] mixed alumina insert with cutting speed 270 m/min. In the present study, the flank wear value of the developed CrZTA insert is less than the said value at the cutting speed of 420 m/min which proves that this insert is very much suitable for high speed machining. It is very difficult to calculate tool life for the developed inserts because huge material consumption in high speed turning. But from the flank wear criteria, it can be suggested that tool life of the developed insert is much better than pure ZTA inserts. The surface roughness is measured with increasing cutting speed under different depth of cut with a constant feed rate i.e. 0.18 mm/rev and the graph of the same is portrayed in Fig 9. From the figure, it can be concluded that for low, medium and high depth of cut i.e. 0.50 mm, 1.00 mm and 1.50 mm, the surface roughness value first increases up to a certain level with increasing cutting speed and after reaching a peak value, the surface roughness value decreases with increase in speed. This phenomenon is observed with a cutting speed more than 280-300 m/min that suggest that this insert can be used for medium to high speed machining. The dimensional accuracy is governed by the flank wear of the turning tool. The quality of the machined surface largely depends upon the stability of the cutting nose. In this work, it is also seen that

the surface roughness is exhibited a rising trend up to certain speed beyond which there has been an improvement of surface finish. The improvement can be explained from nose associated transformation toughening (t-m transformation) phenomena of the respective tool material which is significant in the case of developed Cr-ZTA insert. The same trend of surface roughness property has been also attributed by Kumar et al. [30] while turning with commercial ZTA tool. The surface roughness criteria [29] for rejection of a tool as per ISO Standard 3685 for tool life testing is > 6 micron and the developed insert shows the

surface roughness well below the

criteria at any cutting condition. So, it can be concluded that the developed insert is suitable for machining without the detrimental effect on surface roughness. Cutting force is measured with increasing cutting speed for different feed rate with constant depth of cut of 1 mm and is depicted in Fig 10. It is clearly seen that the cutting force is decreased with increasing cutting speed up to 280-300 m/min in all different feed rate. Beyond this cutting speed, the cutting force is almost constant for feed rate of 0.18 mm/rev but the cutting force is increased slightly with feed rate of 0.24 mm/rev and slightly reduced in case of 0.12 mm/rev feed rate. Almost same nature of cutting force has been portrayed in other constant depth of cut i.e. 0.50 mm and 1.50 mm which are not shown in the figure. Kumanduri et al. [31] stated the reason for variation of cutting force with cutting speed. It is anticipated that cutting speed affects the cutting force by two opposing mechanisms. Firstly, with increase in cutting speed the cutting force decreases for the softening of the work material at the shear zones and chip-tool interaction faces favourable changes. On the contrary, as the higher cutting speed increases the tool wear, this in turn increases the cutting force. So, as the cutting speed increases, the cutting force changes depending on the dominant mechanism plays in the job-tool interface. Usually, cutting force reduces with increase in cutting speed until a minimum is reached called characteristics speed of a given tool-work combination. Beyond that characteristics speed, the cutting force may tend to increases slowly. In present study, the cutting speed in the range of 340-350 m/min has been achieved as characteristics speed. The similar nature of cutting force has been observed by Dutta et al. [32] where 300 m/min characteristics cutting speed has been achieved while machining C-45 steel with commercial ceramic insert. 3.3 Statistical Modelling

The experimental result of flank wear, cutting force and surface roughness as per central composite design layout is portrayed in Table 4. The coefficients of polynomial equation (Eqn. 12) for each response are calculated by Design Expert software (Version 8.0.1). These equations clearly describe the relationship between the input parameters and responses. The ANOVA is performed to check the adequacy of the model and establish the statistical significance of the each contributing parameters in the model. It also helps to estimate the lack of fit for validation of model which must be insignificant because here the intention of the authors is to model that fits. The significance test of each parameters has been carried out with 95% confidence level i.e. by comparing “Prob>F” to 0.05. By calculating regression parameters, linear equation has been selected for modelling the flank wear and quadratic equation has been selected for modelling the cutting force and surface roughness. The backward elimination procedure has been applied to remove the insignificant model terms and the resulting ANOVA for flank wear, cutting force and surface roughness are presented in Table 5, Table 6 and Table 7 respectively.
From Table 5, it is seen that the Model F-value is in the order of 115.72 implies that it is significant. There is only a 0.01% chance that a “Model F-Value” becomes large because of noise factor. It can be concluded that the contribution of cutting speed is 71% which is more significant than the contribution of the depth of cut about 22% with respect to flank wear study. The feed rate has a very little effect (7%) on the same. This may be a result of more shear stress and thermal stress at higher cutting temperature observed in elevated cutting speed and higher depth of cut enabling the induction of tensile stress and exceeding the tool resistance which increases flank wear of the tool [23]. The R2 value is high close to 1, which is desirable. The “Pred. R-Squared” of 0.948 is in reasonable agreement with the “Adj R-Squared” of 0.958. “Adequate Precision” which measures the signal to noise ratio has been calculated as 37.19 - which indicates that this model can be exactly fitted to navigate the design space. From Table 6, Model F-value has been calculated as 175.12 which imply that it is significant. It is also found that the feed rate and cutting

speed has profound effect for the determination of cutting force i.e 56% and 31% respectively. The depth of cut and cutting speed2 has a very little effect i.e. 7% and 5% respectively on the cutting force. Since the increase of the feed rate value the chip cross-section is also increased, the cutting force shall be required more for chip formation. Increase in cutting speed also improves the chip formation and removal of chips at the cutting region [33-35]. The R2 value comes around 0.988 and “Pred. RSquared” of 0.970 is very close to the “Adj R-Squared” of 0.983. As the Adequate Precision” has been calculated as 48.04, it can be concluded that this developed model is navigating the design space very well. From Table 7, it is seen that the main effect of cutting speed (A), depth of cut (C) & cutting speed (A)2 is the noteworthy model term for determination of surface roughness. It is also seen that the Model F-value is in the order of 110.45 implies that the model is significant. In this work, as the cutting speed as well as depth of cut increases the surface finish of the job becomes smooth, so, both these two parameters have profound effect on the job quality [24]. As the R2 value comes around 0.96 and “Pred. R-Squared” of 0.95 closely matches with “Adj R-Squared” of 0.93, so, it can be concluded that this developed model is navigating the design space very well. Adequate Precision” has been calculated 31.44 indicates that this model has a good prediction capability. After backward elimination, the equations for flank wear, cutting force and surface roughness are written below: Flank Wear in Coded Factors = 0.21625 + 0.047*A + 0.015*B + 0.026*C

(13)

Flank Wear in Actual Factors = 0.02525 + 0.00033 * Cutting Speed + 0.25 * Feed Rate + 0.052 * Depth of Cut

(14)

Cutting Force in Coded Factors = 414.66 – 34.2*A + 45.7*B + 15.8*C – 5.5*B*C + 21.53 *A2

(15)

Cutting Force in Actual Factors = 367.5 – 0.8595*Cutting Speed + 945* Feed Rate + 64.6* Depth of Cut – 183.33* Feed Rate* Depth of Cut + 0.0010* Cutting Speed 2 (16) Surface Roughness in Coded Factors = 4.28 – 0.23*A + 0.442*C - 0.831*A2 (17) Surface Roughness in Actual Factors = 0.531 + 0.0221*Cutting Speed + 0.884 * Depth of Cut – 4.243E-05 * Cutting Speed2 3.4 Direct and Interaction effect of variables

(18)

The direct and interaction effect of parameters are portrayed in Fig 11, Fig 12, Fig 13 and Fig 14. The direct effect of cutting speed for the determination of flank wear, cutting force and surface roughness with constant depth of cut and feed rate is portrayed in Fig 11. From Fig 11, it is clearly seen that cutting force is decreasing and flank wear is increasing with increase in cutting speed where as surface roughness increasing up to certain level and then decreases at higher cutting speed. The reason behind the same is already explained in section 2.2. In case of increasing depth of cut due to higher material removal, all the responses increases but well below the critical limit of machining as depicted in Fig.12. It has been found that feed rate has also profound effect on flank wear of the insert and surface roughness of the job as shown in Fig.13. The interaction effect of depth of cut and feed rate has also significant effect on cutting force (Fig 14). When feed rate is increasing the cutting force is also increasing significantly but cutting force increases marginally with increase of depth of cut at constant cutting speed. 3.5 Confirmation Run In order to verify the adequacy of the developed model, five confirmation run experiments have been performed as shown in Table 8. The run conditions for first three confirmation experiments are selected from previous experimental runs and other two are performed outside the range of operating conditions previously used in the experiments. Using Design Expert software, the result is predicted within 95% confidence level. The predicted value of all the responses have been calculated from the Eqn 14, Eqn 16, Eqn 18. The maximum percentage error for cutting force, surface roughness and flank wear has been estimated 1.38%, 5.29% and 5.62% respectively. It can be concluded that the predicting capability of the models are very well for this application.
3.6 Optimization of Parameters

Desirability function optimization of the RSM has been employed for all the responses in this machining study. During the optimization process, it is required to find the optimal values of cutting parameters in order to minimize the values of flank wear, cutting force surface roughness during the hard turning process using the developed Cr-ZTA insert. As the material removal rate mainly depends upon cutting speed, the condition for cutting speed has been set as maximum with feed rate and depths of cut are kept in experimental range. The optimal solutions for each response are reported in Table 9 with decreasing desirability level.
From the Table 9, it can be concluded that cutting speed 420 m/min, feed rate 0.12 mm/rev and depth of cut 0.5 mm is the optimum condition with 83.32% desirability level for minimum flank wear and surface roughness. This proves that this insert can be used for high speed machining with low feed rate and low depth of cut. 4. Conclusion The effect of different mole % of Cr2O3 addition in 90 wt. % α-Al2O3 / 10 wt. % YSZ has been studied for visualize tetragonality factor of ZrO 2 crystal. The mechanical characterization i.e. determination of hardness and fracture toughness has been carried out to correlate the phases with mechanical strength and it has been found that both hardness and fracture toughness reaches the highest value i.e. hardness of 17.40 GPa and fracture toughness of 7.20 MPa.m1/2 at 0.6 % Cr2O3 doped ZTA due to more metastable tetragonal ZrO2 than stable tetragonal/cubic phase presents in the samples. The cutting inserts have been developed with the same composition and machinability investigation has been carried out by machining AISI 4340 steel in NH 26 lathe. During the machining operation, it has been observed that the average and the maximum flank wear values are below the respective stipulated tool rejection criterion at all cutting conditions. Surface finish of the job is also improved in medium to high range of speed. Characteristic speed for minimum cutting force is also achieved in the range of 340-350 m/min for these newly developed insert. As the developed insert is non-isotropic in nature so the CCD design of response surface methodology has been applied to optimize the cutting condition for minimum tool failure and maximum tool life. Optimum condition has been found at

cutting speed of 420 m/min, feed rate of 0.12 mm/rev and depth of cut of 0.5 mm with 83.32% desirability. From this study, it can be concluded that this insert can behave very well at medium to high speed machining and have a great potential to replace the carbide or coated carbide tool in near future. Acknowledgement The authors would like to express their gratitude to Director, CSIR-Central Mechanical Engineering Research Institute, Durgapur for his kind permission to publish the paper in Ceramic International journal. The authors are also gratefully acknowledged the staff members and research fellows of Centre for Advanced Materials Processing (CAMP) for their continuous effort in the experimentation part of the paper. The authors are also thankful to Central Research Facility, Indian Institute of Technology, Kharagpur and CSIR-CMERI, Durgapur for helping us to carry out the characterization study like XRD, FESEM etc. Lastly, the financial support (SB/S3/MMER/0035/2014 dated 22-05-2014) received from Science and Engineering Research Board (SERB) of Department of Science and Technology (DST), Govt of India, New Delhi is highly acknowledged.

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4. Smuk B, Szutkowska M, Walter J. Alumina ceramics with partially stabilized zirconia for cutting tools. J mater process technol 2003;133:195-198. 5. Casto SL, Valvo EL, Lucchinib E, Maschiod S, Piacentinia M, Ruisia VF. Ceramic materials wear mechanisms when cutting nickel-base alloys. Wear 1999;225229:227-233. 6. Kumara AS, Duraia AR, Sornakumar T. Development of yttria and ceria toughnened alumina composite for cutting tool application. Int J Refract Met Hard Mater 2007;25: 214–219. 7. Xu C, Ai X, Huang C. Fabrication and performance of an advanced ceramic tool material. Wear 2001;249:503-508. 8. D’Errico G E, Bugliosi S, Calzavarini R, Cuppini D. Wear of advance ceramics for tool materials. Wear 1999;225-229:267-272. 9. Szutkowska M. Fracture resistance behaviour of alumina–zirconia composites. J mater process technol 2004;153-154:868-874. 10. Azhar AZA, Mohamed H, Choong CL, Ratnam MM, Ahmad AZ, Effects of Cr 2O3 addition on the mechanical properties, microstructure and wear performance of zirconia-toughened –alumina (ZTA) cutting inserts. J Alloys Compd 2012;513:91-96. 11. Bondioli F, Ferrari AM, Leonelli C, Manfredini T, Linati L, Mustarelli P. Reaction mechanism in alumina/chromia (Al2O3–Cr2O3) solid solutions obtained by coprecipitation. J Am Ceram Soc. 2000;83:2036-2040. 12. Riu DH; Kong YM; Kim HE. Effect of Cr2O3 addition on microstructural evolution and mechanical properties of Al2O3. J Eur Ceram Soc 2000;20:1475-1481. 13. Benga GC, Abrao AM. Turning of hardened 100Cr6 bearing steel with ceramics and PCBN cutting tools. J Mater Process Technol 2003;143-144:237-241. 14. Kacal A, Yildirim F. Application of grey relation analysis in high-speed machining of hardened AISI D6 steel. J Mech Eng Sci 2012;227(7):1566-1576. 15. Aslan E, Camuscu N, Birgoren B. Design optimisation of cutting parameter when turning hardened AISI 4140steel (63HRC) with Al2O3 + TiO2 mixed ceramics tool. Mater Des 2007; 28:1618-1622. 16. Ozel T, Karpat Y, Figueira L, Daavim JP. Modeling of surface finish and tool flank wear in turning of AISI D2 steel with ceramic wiper inserts. J Mater Process Technol 2007;189:192-198. 17. Meddour I, Yallese MA, Khattabi R, Elbah M, Boulanouar L. Investigation and modelling of cutting force and surface roughness when hard turning of AISI 52100 steel with mixed ceramic tool: cutting condition optimization. Int Adv Manuf Technol 2015;77:1387-1399.

18. Mondal B, Mandal N, Doloi B. Development of Ce-PSZ-/Y-PSZ- toughened alumina inserts for high-speed machining steel. Int J Appl Ceram Technol 2014; 11:228–239 19. Mokhtar M, Basahel SN, Ali TT. Effect of synthesis methods for mesoporous zirconia on its structural and textural properties. J Mater Sci 2013;48:2705–2713 20. Cullity BD. Elements of X-ray diffraction. 2nd Ed Addison-Wesley 1978. 21. Lawn BR, Swain MV. Microfracture beneath point indentations in brittle solids. J Mat Sci 1975;10:113-122. 22. Evans AG, Charles EA. Fracture toughness determination by indentation. J Am Ceram Soc 1976;59:371-372. 23. Mandal N, Doloi B, Mondal B. Development of flank wear prediction model of zirconia toughened alumina (ZTA) cutting tool using response surface methodology. Int J Refract Met Hard Mater 2011;29:273–280. 24. Mandal N, Doloi B, Mondal B. Predictive modelling of surface roughness in high speed machining of AISI 4340 steel using yttria stabilized zirconia toughened alumina turning insert. Int J Refract Met Hard Mater 2013;38:40–46. 25. Magnani G, Brillante A. Effect of the composition and sintering process on mechanical properties and residual stresses in zirconia–alumina composites. J Eur Ceram Soc 2005;25:3383-3392. 26. Hernandez MT, Gonzalez M, Pablos AD. C-diffusion during hot press in the Al2O3-Cr2O3 system, Acta Mater 2003;51:217-228. 27. Hirata T, Akiyama K, Yamamoto H. Sintering behaviour of Cr2O3-Al2O3 ceramics. J Eur Ceram Soc 2000;20:195-199. 28. Hao JKC, Azhar AZA, Ratnam MM, Ahmad ZA. Wear performance and mechanical properties of 80 wt-%Al2O3/20wt-%YSZ cutting inserts at different sintering rates and soaking times. Mater Sci Technol 2010;26:95-103. 29. Kumara AS, Duraia AR, Sornakumar T. The effect of tool wear on tool life of aluminium–based ceramic cutting tools while machining hardened martensitic stainless steel. J mater Process Tech 2006;173:151-156. 30. Kumara AS, Duraia AR, Sornakumar T. Machinability of the hardened steel using alumina based ceramic cutting tools. Int J of Refract Met and Hard Mater 2003;21:109-117. 31. Komanduri R, Flom DG, Lee M. Highlights of the DARPA advanced machining research program, Trans ASME J Manuf Sci Eng 1985;107:325-335. 32. Dutta AK, Chattopadhyaya AB, Ray KK. Progressive flank wear and machining performance of silver toughened alumina cutting tool inserts. Wear 2004;261:885895.

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Figure Caption: Fig 1 Design of Die and Punch Fig 2 Final shape of Cr-ZTA Insert Fig 3 Set up of lathe and job Fig 4 XRD spectra of 0.6 wt % Cr2O3 in ZTA Fig 5 XRD spectra of different wt % Cr2O3 in ZTA Fig 6 FESEM Image of Cr-ZTA Insert (Inset: View of Crack Propagation) Fig 7 Values of Flank wear at different cutting speed Fig 8 Image of Flank wear Fig 9 Surface Roughness with cutting speed at different depth of cut Fig 10 Cutting force with cutting speed at different feed rate Fig 11 Direct effect of cutting speed for Machinability Investigation Fig 12 Direct effect of depth of cut for Machinability Investigation Fig 13 Direct effect of feed rate for Machinability Investigation Fig 14 Interaction effect of depth of cut and feed rate for Cutting Force

Table Caption: Table 1 Process Parameters and their levels Table 2 Phase Composition, Density, Crystallite Size and Grain Size of different wt % Cr2O3 in ZTA Table 3 Hardness and Fracture Toughness of different wt % Cr2O3 in ZTA Table 4 Experimental result as per design layout Table 5 Final ANOVA table for Flank Wear Table 6 Final ANOVA table for Cutting Force Table 7 Final ANOVA table for Surface Roughness Table 8 Confirmation Run Table 9 Optimization Result

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Table

Table-1: Process Parameters and their levels

Sl no 01

Lower Level (-1)

Cutting Speed (m/min) 140

Feed Rate (mm/rev) 0.12

Depth of Cut (mm) 0.50

02

Middle Level (0)

280

0.18

1.00

03

Higher Level (-1)

420

0.24

1.50

Table

Table 2. Phase Composition, Density, Crystallite Size, and Grain Size of different wt % Cr2O3 in ZTA

Composition

Density (% Theoretical)

Bulk Density

Crystallite size (nm)

ZTA + 0 wt% Cr2O3 ZTA + 0.2wt%Cr2O3 ZTA + 0.4wt%Cr2O3 ZTA + 0.6wt%Cr2O3 ZTA + 0.8wt%Cr2O3 ZTA + 1.0wt%Cr2O3

97.50 98.25 98.44 98.62 98.75 98.90

4.49 4.40 4.38 4.32 4.28 4.22

36.26 39.52 40.20 42.02 44.52 45.02

Phase Composition m-ZrO2 t-ZrO2 52 48 47 53 40 60 24 76 16 84 4 96

Average grain size (micron) 1.65 1.58 1.52 1.42 1.35 1.26

Table

Table 3. Hardness and Fracture Toughness of different wt % Cr2O3 in ZTA Composition

Sintering Temperature

Hardness (GPa)

ZTA + 0 wt% Cr2O3 ZTA + 0.2wt%Cr2O3 ZTA + 0.4wt%Cr2O3 ZTA + 0.6wt%Cr2O3 ZTA + 0.8wt%Cr2O3 ZTA + 1.0wt%Cr2O3

1600 1600 1600 1600 1600 1600

16.00 16.20 16.80 17.40 17.05 16.90

Fracture Toughness (MPa.m1/2) 5.81 6.24 6.63 7.20 6.81 6.73

Table

Table.4 Experimental result as per design layout

Run 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Machining Parameters Cutting speed Feed Rate Depth of Cut A (m/min) B (mm/rev) C (mm) 140 420 140 420 140 420 280 420 280 280 280 140 420 280 140 280

0.18 0.18 0.12 0.12 0.12 0.12 0.18 0.24 0.18 0.18 0.24 0.24 0.24 0.18 0.24 0.12

1.0 1.0 1.5 1.5 0.5 0.5 1.0 1.5 1.5 1.0 1.0 0.5 0.5 0.5 1.5 1.0

Flank Wear Vb (mm) 0.16 0.25 0.18 0.28 0.13 0.22 0.23 0.30 0.25 0.21 0.25 0.16 0.25 0.19 0.20 0.20

Response Factors Cutting Force Surface (Newton) Roughness (µm) 464 3.60 396 3.50 448 4.15 376 3.62 402 3.14 335 2.70 417 4.27 467 3.48 430 4.75 420 4.29 448 4.16 513 3.25 436 2.80 402 3.95 525 4.26 371 4.27

Table

Table.5 Final ANOVA of Flank Wear

Source Model A-Cutting Speed B-Feed Rate C-Depth of Cut Residual Lack of Fit Pure Error Cor Total Std. Dev. Mean C.V. % PRESS

Sum of Squares df 0.0311 3 0.02209 1 0.00225 1 0.00676 1 0.001075 12 0.000875 11 0.0002 1 0.032175 15 0.009464847 0.21625 4.376807974 0.001645469

Mean Square 0.010366667 0.02209 0.00225 0.00676 8.95833E-05 7.95455E-05 0.0002

F Value 115.72093 246.58605 25.116279 75.460465

p-value Prob > F < 0.0001 < 0.0001 0.0003 < 0.0001

0.3977273

0.8589

R-Squared Adj R-Squared Pred R-Squared Adeq Precision

0.966589 0.9582362 0.9488588 37.190246

Cont.% 71.02894 7.234727 21.73633

Remarks significant significant significant significant not significant

Table

Table.6 Final ANOVA of Cutting Force

Source Model A-Cutting Speed B-Feed Rate C-Depth of Cut BC A^2 Residual Lack of Fit Pure Error Cor Total Std. Dev. Mean C.V. % PRESS

Sum of Squares 37058.51667 11696.4 20884.9 2496.4 242 1738.816667 423.2333333 418.7333333 4.5 37481.75 6.50563858 428.125 1.519565216 1123.681682

df 5 1 1 1 1 1 10 9 1 15

Mean Square 7411.703333 11696.4 20884.9 2496.4 242 1738.816667 42.32333333 46.52592593 4.5

F Value 175.12097 276.35819 493.46066 58.984012 5.7178861 41.084114

p-value Prob > F < 0.0001 < 0.0001 < 0.0001 < 0.0001 0.0379 < 0.0001

10.339095

0.2371

R-Squared Adj R-Squared Pred R-Squared Adeq Precision

0.9887083 0.9830624 0.9700206 48.043691

Cont.% 31.56 56.36 6.74 0.65 4.69

Remarks significant significant significant significant significant significant not significant

Table

Table 7. Final ANOVA of Surface Roughness

Source Model A-Cutting Speed C-Depth of Cut A^2 Residual Lack of Fit Pure Error Cor Total Std. Dev. Mean C.V. % PRESS

Sum of df Squares 5.076400417 3 0.529 1 1.95364 1 2.593760417 1 0.183843333 12 0.183643333 11 0.0002 1 5.26024375 15 0.12377511 3.761875 3.290250465 0.323197298

Mean Square 1.692133472 0.529 1.95364 2.593760417 0.015320278 0.016694848 0.0002

F Value 110.45057 34.5294 127.51988 169.30244

p-value Prob > F < 0.0001 < 0.0001 < 0.0001 < 0.0001

83.474242

0.0852

R-Squared Adj R-Squared Pred R-Squared Adeq Precision

0.9650504 0.956313 0.9385585 31.438739

Cont.% 10.42077 38.48475 51.09448

Remarks significant significant significant significant not significant

Table

140

210

280

300

420

2

3

4

5

Cutting Speed

1

Sl. No.

0.24

0.12

0.24

0.24

0.18

Feed Rate

Parameters

Table 8. Confirmation Run

1.0

0.5

1.5

448

342

469

492

464

1.0 1.5

Cutting Force

Depth of Cut

3.4

3.92

4.56

4.45

3.6

Surface Roughness

0.27

0.18

0.25

0.23

0.16

Flank Wear

Experimental Values

447.70

343.22

470.67

493.15

470.40

Cutting Force

3.22

3.79

4.72

4.63

3.68

Surface Roughness

Predictive Values

0.2780

0.1820

0.2570

0.2334

0.1690

Flank Wear

0.067

-0.357

-0.356

-0.234

-1.380

Cutting Force

5.294

3.316

-3.508

-4.045

-2.222

Surface Roughness

% Error

-2.963

-1.111

-2.800

-1.478

-5.625

Flank Wear

Table

Table 9. Optimization Result

Number 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Cutting Speed 420.00 420.00 420.00 420.00 420.00 419.99 420.00 417.86 420.00 420.00 416.63 420.00 414.70 413.92 410.38 420.00 420.00 416.14 420.00 420.00

Feed Rate 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.13 0.12 0.12 0.12 0.12 0.12 0.12 0.16 0.12 0.12 0.17 0.17

Depth of Cut 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.53 0.50 0.55 0.50 0.50 0.50 0.50 0.63 0.60 0.50 0.50

Flank Wear 0.22225 0.222518 0.222468 0.222704 0.223005 0.223182 0.223151 0.221532 0.224355 0.223883 0.221119 0.224945 0.220471 0.22045 0.21902 0.231735 0.228911 0.226009 0.234023 0.234476

Surface Roughness 2.77800 2.77801 2.78171 2.77800 2.77801 2.77809 2.78182 2.80675 2.77800 2.80576 2.82306 2.82337 2.84858 2.85864 2.90419 2.77800 2.89119 2.91556 2.77801 2.77800

Desirability 0.833214005 0.832574237 0.832345537 0.832130024 0.831407567 0.830963761 0.830700518 0.828658469 0.828147621 0.826683945 0.826036286 0.822442249 0.821877950 0.819672056 0.812580619 0.809468807 0.806135743 0.804717878 0.803356980 0.802130499

Selected