Machinability study of JFRP composite using design of experiment

Recently, the machining of composite materials has increased to a large extent to get the required shape and design during the assembly stage of Jute fiber reinforcement polymer (JFRP). The output performance of milled JFRP composite depends on the input machining parameter such as spindle speed, feed rate, and depth of cut. The output responses like tool wear, surface roughness (Ra), and delamination factor (Fd) affect the dimensional stability, structural integrity, and accuracy of the final product. The objective of this study to find out the most significant factor of the output performances on JFRP. In this machining study, the JFRP composite panels were fabricated according to the hand’s lay-up technique and the milling was done by using an uncoated carbide cutting tool. The DOE (Design of Experiment) tool was used to design the experimental table based on Response Surface Methodology (RSM). A Central Composite Design was used to analyze the data and the most significant factor that effect the output parameters. According to Analysis of variance (ANOVA), it was found that the feed rate has a significant influence on tool life, surface roughness, and delamination factor. The spindle speed has also an effect on output responses comparing to the depth of cut. Another objective of this research is to obtain an optimum setting of the input parameters and mathematical modeling equation to reduce the tool wear, surface roughness, and delamination factor. The optimum parameter of the input machining was found that the input parameter spindle speed 4293.88 rev/min, feed rate 150 mm/min, and depth of cut 1 mm in where the lowest surface roughness, delamination, and longer tool life would be achieved.


Introduction
Nowadays, there has been great interest in the use of Natural Fiber Reinforcement Polymer (NFRP) composite to replace synthetic fiber in composite applications [1]. Among different kinds of natural fibers, jute fiber is the most promising and satisfactory reinforcement for use in

Milling of Jute Fiber Composite
JFRP is generally fabricated in their net shape, however, to get the required shape, design, accuracy, dimensional stability, secondary machining operations must be done. These machining operations are such as drilling, milling, trimming, grinding, slotting. Machining of JFRP is difficult and quite different from metalworking because of the inhomogeneity, anisotropic structure, and abrasive nature. There also have different thermal properties of the fiber and matrix materials [10].
Even though the fibers can endure higher temperatures, the temperature generates during FRP machining should not over the curing temperature in order to avoid material deterioration. In the time of machining FRP composite, the cutting tool faces high abrasive wear. Abrasive wear happens when a hard-rough surface slides across a softer surface. The friction between the cutting tool and workpiece produces cutting forces in the machining of FRP and it can damage the material permanently [11]. Machining is a word that is used to describe a variety of metal material removal processes. There are various types of machining processes to get the required shape and design such as milling, drilling, slotting, turning, etc. The milling process is defined as the most acceptable process to remove materials and create a high-quality surface [12]. During machining, the principal drawbacks are severe tool wear, surface delamination, and poor surface roughness. The surface roughness drawing attention for many years because it can affect product performance, dimensional precision, and production cost [13]. In conventional machining methods, has been proved that FRP composite material faces difficulties in achieving acceptable surface quality [14]. Fibre delamination occurs generally in drilling and milling and affects product quality. During machining, the heterogeneous FRP composite causes delamination and this reduces the bearing strength, structural integrity, durability, and tool wear. Therefore, researchers and manufacturers face greater pressure as they need to establish a better understanding of FRP cutting processes, concerning accuracy and efficiency [15].
The challenges of machining can be eliminated by improving the machining cycle, in this way giving the occasion to higher efficiency and more noteworthy completing quality at a lower machining cost. The machining of FRPs requires an alternate age of instruments with changes in their calculation and the abrasion resistance of hardware material. Carbide cutting tool has better hardness and commonly used during FRP composite machining. According to Lie et al. [16], carbide cutting tools are costeffective and gives a better surface finish. Its wear resistivity is very high and machinability also good.

Tool wear Surface Roughness and Delamination Factor
The fundamental of wear mechanisms can vary under different conditions. In FRP machining, the significant effects on the composite are abrasion, surface damage, and adhesion. This wear mechanism is initially related to the mechanical and physical properties of the fiber and matrix materials. It is very important to achieve a high metal removal rate, low tool wear, and good surface finish [17]. According to Krishnaraj et al. [18], abrasive wear is visible in CFRP machining because carbon fiber is extremely abrasive. A similar opinion comes from Tsao & Chiu [19] which said in GFRP machining, tool wear is very clear due to the abrasive nature of glass fiber. The machining input parameters such as feed rate, cutting speed, depth of cut are the most significant factors affecting tool wear. The cutting speed influences tool wear because of the amount of thermal energy that is generated at the cutting edge. The heat distribution between the tool and the composite depends on the thermal conductivity of the composite material. Tool wear improves at a higher cutting speed which is reported by several researchers [20][21]. Teti [22] concluded that machining FRP at higher cutting speeds results in better tool life. Some of the researchers also stated that during machining of JFRP composite, tool wear is affected by the increasing and decreasing cutting speed. During machining of JFRP composite, tool wear become very fast with a higher depth of cut and feed rate [23].
A higher machining rate and better surface finish are desirable and many aspects have been studied to improve the machinability of FRP composites. In order to achieve a good surface finish end product, machining on composite should be continued based on reducing surface roughness and protecting the material characteristics. Rashid et al. [23] also stated that on milling JFRP composite material, many factors affect the surface quality such as feed rate, depth of cut, cutting speed and these are the most important parameter which influences the machine tool and workpiece set up. Aouici et al. [24] mentioned that cutting parameters have a greater influence on international dimensional precision and the surface in addition to machining force and specific cutting pressure. Bhushan et al. [25] agreed with this report that the machinability of FRP composites, the feed rate was found to be the most dominant parameter, which has the highest statistical and physical influence on surface roughness during machining. The feed rate is an important factor for the improvement of surface roughness when machining glass fiber reinforced polymer, as an increment in the feed rate reduced the surface quality [26]. Khairusshima et al. [27] explained that during the milling of CFRP composite, higher feed rate values produced greater surface roughness. Azmi et al. [28] stated that, during machining of natural fiber reinforced polymer (NFRP) composite, the surface quality of the machined composite materials is reduced due to an increase of feed rate, which led to a greater thrust force responsible for fracturing the composite material. Therefore, the scope of higher feed rate must be determined, to achieve acceptable surface roughness and it can decrease cutting time.
It has been found that fiber reinforced polymer milling shows delamination which is one of the surface quality related problem. Palanikumar [29] mentioned that delamination depends on fiber orientation and performance of cutting tools during milling GFRP. Delamination occurs in the form of fiber overhang and breakage of fiber at the cutting edge. Actually, delamination affects surface quality strongly and reduces the structural integrity and long-term performance of a part. Delamination factors decrease the structural integrity by lowering the bearing strength, leading to the poor assembly of tolerance, and potentially affect the long-term performance of parts [30]. The higher cutting speed reduces the delamination. It was explained by several researchers, Kilickap [31] recommended that low feed rate and high cutting speed reduces the delamination because higher speed results in the thermal condition of tool material, which burn the pull-out fiber and decrease the delamination.
The design of the experiment is the process of designing, planning, and analyzing the experiment. The objective, conclusion, and the valid result can be drawn efficiently and effectively through this design of experiment software. have been conducted to study the FRP machinability and analyzing the influencing factors. Response surface methodology (RSM) is an important technique for creating and IOP Publishing doi:10.1088/1757-899X/1092/1/012014 4 optimizing a statistical model. The performance of the advanced model is demonstrated by using scrutiny tests given by Analysis of Variance (ANOVA). Until now, no research has been conducted to find out the optimum input parameter of JFRP composite machining to get lower surface roughness and delamination factor with higher tool life. It is expected from this study, it would be possible to get the most significant input factor with optimum machining parameters.

Materials
The jute fabric (Tossa grade-1) was collected from Janata jute mill corporation, Bangladesh, and stored at room temperature. The tenacity of Tossa grade-1 jute fabric is 3.5-4.5 g/den. Its dimensional stability and thermal resistance are very good and moisture regains 13.5%. The staple length of Tossa grade-1 is 0.5-30 inches and a diameter of 18 microns respectively. Figure 1(a) shows the Tossa jute fabric grade-1. Epoxy resins are available in various quality and different coded forms like E205, E105, E101, BRT Epoxy resin, etc. The best quality coded (E101) epoxy resin was collected from Prantika Dsara Trading Company, Selangor. Similarly, there are various coded and commercially named hardener is available also like ALBAFIF-ECO, SUNFIX, MB-1, H10, H151, etc.

Fabrication of Jute Composite
Jute fabric was fabricated by following hands lay-up techniques in a different composition. The first composition was 60% jute fabric (reinforcement) with 40% matrix material (epoxy resin & hardener) and the second composition was 70% jute fabric with 30% matrix material. The fabric was cut according to the unidirectional way. The dimension of the composite was 200 mm × 200 mm × 5 mm ( Fig.1 (b)).
The resin was mixed with the hardener and the ratio was 2:1. The stirrer was used to mix these two materials uniformly. After making the solution, jute fabric was dipped with the solution one by one and placed it on mylar plastic. The plastic ruler was used to place the layer closely one after one and to distribute the resin hardener to all the corners of the fabric by moving the plastic ruler to and fro. After completion of five layers, another plastic was put on the top layer, and weight was applied according to the hands lay-up technique. All the panels were fabricated individually and prepared for the mechanical test according to ASTM standards and machining respectively. Figure 1(c) shows the machined JFRP panel.

Measurement of Tool wear, Surface Roughness, and Delamination
The Nikon Measuring Microscope model: MM-400/L used to measure tool wear of the uncoated carbide cutting tool and delamination factor. Figure 2 shows the delamination measurement area of the machined JFRP panel. The microscope is connected to the CPU and the data is analyzed using NIS-Element F3.0 software. Figure 3. shows the Nikon Measuring Microscope. The surface roughness of the milled JFRP is used to measure by using Veeco Wyco Optical Profiling System Measuring: model NT 1100. The microscope collects the surface data by scanning the machined surface. FOV and objectives lens options were selected to display the magnification and field view. The user controls the length, infra-red back scan, and the percentage modulation of the threshold.

Results and Discussion
Tool wear, surface roughness, and delamination factors are the greatest significant defects for the refutation of the industrially made constituents, which appeal serious consideration to the engineers for machining JFRP. It is very essential to measure the tool wear, surface roughness, and delamination factor for the acceptance of the produced goods. In this study, the surface roughness was measured by using the Veeco Wyco (1100) Optical Profiling System microscope and the tool wear and delamination factor of the JFRP panel was measured by using Nikon Measuring Microscope. The delamination factor was determined by measuring the maximum width of damage suffered by the material after machining.
According to the small CCD design, fifteen experiments were run and ( Table 2) shows that the result of the delamination factor for all cutting parameters.  Table 3 shows the ANOVA model for the tool life (Response 1). The Model F-value of 185.64 suggests that the model is significant with the Values of "Prob > F" under 0.05. There is essentially a 0.01% possibility that a "Model F-value" this large could happen because of noise. In this situation, the significant model terms are the fundamental effect of spindle speed (A), the primary impact of feed rate (B), the main effect of depth of cut (C), two-level interaction of feed rate and depth of cut (BC), the second-order impact of spindle speed (A 2 ) and feed rate (B 2 ). Table 3 likewise shows that the factor with the main impact on the tool life was the feed rate with an F-value that was equivalent to 827.83. This was expected and reported by a large portion of scientists that the feed rate is the essential factor that impacts the tool life of the cutting tool [25]. The model is acceptable on the grounds that the Lack of Fit is not significant with 21.42% comparative with the pure error. The R 2 is 0.993 which is high and close to 1, the R 2 predicted of 0.912, and the R 2 adjacent of 0.987.  Where, A = Spindle speed (rev/min), B = Feed rate (mm/min), and C = Depth of cut (mm) Table 4 shows the ANOVA model for surface roughness (Response 2). The Model F-estimation of 28.14 suggests that the model is significant with the Values of "Prob > F" under 0.05. There is only a 0.01% possibility that a "Model F-value" this large could happen because of noise. For this situation, the significant model terms are the principle impact of spindle speed (A) and feed rate (B) and the two-level interaction of spindle speed and depth of cut (AC), a two-level association of feed rate with a depth of cut (BC). unpleasantness with an F-value that was equivalent to 43.92. This is valid, as it has been reported by Palanikumar [32] that during machining composite GFRP, the feed rate has been recognized as the main factor that impacts the surface roughness of GFRP. The model is acceptable as the Lack of Fit is not significant with 38.85% comparative with the pure error. The R 2 is 0.939 which is high and close to 1. The R 2 predicted of 0.803 is in reasonable concurrence with the R 2 adjacent to 0.906. A proportion greater than 4 is desirable. In this model, the ratio is 19.936 which shows a satisfactory signal.  Where, A = Spindle speed (rev/min), B = Feed rate (mm/min), and C = Depth of cut (mm)

ANOVA analysis for Fd
The delamination factor (Fd) assumes a significant role that impacts the quality of the end product. In this investigation, a developed model has been predicted to observe the significant factor which influences the delamination factor. Table 5 shows that the ANOVA model shows the delamination factor (Response 1). The model gives the F-value 16.28 which recommends that the model is significant with Values of "Prob > F" under 0.05. For this situation, the significant model terms are the key impact of spindle speed (A), the fundamental effect of feed rate (B), the principal effect of depth of cut (C), two-level interaction of spindle speed and depth of cut (AC) and second-order impact of feed rate (B 2 ). The model shows that the effect of feed rate has the main effect on the delamination factor with an F value of 62.89. This outcome chooses with the report of [33], which determined that feed rate, gives the highest contribution to the delamination factor. The model has a Lack of Fit that is not significant with 75.71% comparative with the pure error. The R 2 is 0.9482 which is high and close to 1. The R 2 predicted of 0.7303 is in reasonable concurrence with the R 2 adjacent of 0.9094. Then, the value of satisfactory accuracy 19.98 which is desirable as the proportion is more noteworthy than 4. Where, A = Spindle speed (rev/min), B = Feed rate (mm/min), and C = Depth of cut (mm)

Optimization of all input parameter
In this study, the relationship of three input parameters which are spindle speed, feed rate, depth of cut, and three responses which are tool life, surface roughness, and delamination factor is observed. It is necessary to adopt the process of optimization to achieve the optimum values of the responses simultaneously. The optimization is obtained using software of Design Expert 10.0.3 which corresponded to the responses criteria of maximized tool life, minimized delamination factor, and surface roughness. The range of the responses is selected based on the data acquired during machining. a) Tool life: 11.31 < Tl < 41.6 minutes b) Surface roughness: 1.56 < Ra < 2.69 µm c) Delamination factor: 1.09 < Fd < 1.703 The optimum solutions are tabulated in Table 6 as the best desirability index obtained which is 96.8%. It has been indicated that the optimum values of the machining parameters can be obtained at a spindle speed 4293.56 rev/min, feed rate 150 mm/min, and depth of cut 1.0 mm. These conditions yield optimum value of surface roughness, tool life, and delamination factor of 28.525 min, 0.760 mm, and 1.188 µm respectively.  The graphical optimization or overlay contour plot was developed by overlapping the contours for each of the responses. Figure 4 shows the overlay plot for JFRP machining. The shaded portion on the overlay plot defines the permissible value of the dependent variable

. Conclusion
In this study, the experimental table was designed following the central composite design, and the analysis was done by using ANOVA. The cutting parameters were feed rate, spindle speed, depth of cut and responses was surface roughness. From the result, it can be decided as follows:  It was found that the machining feed rate is the most significant factor that affects the out responses of the tool wear, surface roughness, and delamination factor.  The best outcomes of the optimization solution were found that the cutting speed, feed rate, depth of cut are 4293.56 revs/min, 150 mm/min, and 1.0 mm. optimum value of the surface roughness was 1.18 µm. This optimum parameter can be used for the machining of NFRP (Natural fiber reinforced polymer) composite to get better machining performance.