APPLICATION OF DOE, ANOVA AND REGRESSION ANALYSIS TO STUDY THE EFFECT OF MACHINING FACTORS ON CHISEL EDGE WEAR IN DRILLING GFRP COMPOSITES

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1 APPLICATION OF DOE, ANOVA AND REGRESSION ANALYSIS TO STUDY THE EFFECT OF MACHINING FACTORS ON CHISEL EDGE WEAR IN DRILLING GFRP COMPOSITES Sathish Rao U., Akshay Mimani, Manjot Singh Dhillon, Sanjay S. Department of Mechanical and Manufacturing Engineering, Manipal Institute of Technology, Manipal University, Manipal, India Dr. Lewlyn L.R. Rodrigues, Head, Department of Humanities and Management, Manipal Institute of Technology, Manipal University, Manipal, India Abstract: Since three decades, almost all the traditional engineering materials have been replaced by composite materials. The composites offer many advantages like high strength to weight ratio, less weight, flexibility in design, structural and dimensional stability, corrosion and wear resistance along with low tooling cost compare to homogenous materials. But, because of the anisotropy nature, machining composite materials is a complex process especially operations like drilling and milling, as these machining operations lead to tool wear because of abrasive nature of reinforcing fibers. It was also observed that the tool wear is influenced and controlled by the respective machining factors. Inspired by this, in this research work, the various drill process factors i.e., drill diameter (D), spindle speed (N), feed rate (F), and tool point angl levels, to minimise chisel edge tool wear in the drilling of Glass Fiber Reinforced Polyester (GFRP) composites. Taguchi s Orthogonal Array (OA) experimental design is applied to carry out the experiments. The optimum values of the process factors for minimizing the drill chisel edge wear was found using Signal to Noise (S/N) ratio. ANOVA was used to find the contribution of each parameter towards the chisel edge wear. A regression equation for calculating the chisel edge wear was generated using experimental data. The reliability of the regression equation was checked through experimental validation. The micrograph image shows that there is quantifiable amount of chisel edge wear on the drill due to abrading and adhering action between the GFRP composite and the HSS drill. Keywords - GFRP composites, ANOVA, chisel edge tool wear, S/N ratio, orthogonal array I. INTRODUCTION Composite Materials are made by combining two or more different materials with significantly different properties. In general, the two major constituents are Matrix material (which forms the bulk of the Composite Material) and the Reinforcement material (which provides the strength and stiffness). The two materials combine to give the composite unique properties which are better than those of the individual constituents, when used alone [1]. In contrast to metallic alloys, each material retains its separate physical, chemical and mechanical properties. Composites are nowadays commonly used in industrial and domestic purposes as they are light in weight but stronger compared to metals. The Matrix material performs several critical functions like taking up the initial applied load and gradually transferring it to the fibers, maintaining the fibres in the proper 32

2 orientation and protecting them from abrasive environment. By choosing an appropriate combination of the constituent materials (matrix+fiber), a new composite material can be made that can exactly meet the requirements of a particular application [2] Drilling is the most frequently employed operation in any of the conventional / composite materials, owing to the need for structure joining and assembly. The rapid tool wear of the drill bit has been recognized as one of the major problems during drilling operations. The consequences of tool wear while machining may change the dimension, tolerance, shape and surface finish of a drilled hole. Care must be taken in early stage before the tool breakage has damage on the product or process flow in order to reduce cost and time [3]. So, the process of drilling of composites is economically important since the extremely abrasive nature of the fibers limits the drill life [4]. The experimental results and theoretical analysis show that the degree of tool damage depends on drilling factors and on the composite material composition [5]. It was found that, with an optimized combination of the various factors of the materials, machine and the tool, the wear of the drill can be minimized [6]. A number of research works reveal that, in practical, the significant type of wear in drilling are flank and crater wear [7]. Many investigations say that the tool wear in drilling occurs due to abrasion of tool material at lower cutting speeds and through diffusion at higher speeds in machining on metals [8]. Thus composite materials are difficult to machine because of anisotropy nature, and of the abrasive nature of reinforcements. So, damage to the work piece is significant and tool will high wear at higher rate [9]. The alloyed tool steel material can withstand hardness at higher temperatures and are economical. Due to these findings, the present study is focused on HSS drilling on GFRP composites to minimize chisel edge wear by controlling the machining factors. The machining factors considered are Spindle speed, Feed, Tool diameter and Drill point angle. II. METHODOLOGY Composite laminate of constant thickness of 6mm was manufactured by hand lay-up method (Figure 1). Glass fibers of 15 micron diameter with random orientation was used as reinforcement material and Isophthalic polyester resin was used as matrix material for fabricating the composite laminate. Process factors and levels: Drill Spindle speed: The spindle speed levels chosen are 2000, 2500 and 3000 rpm. 33

3 Drill feed: The drill feed process factor was set to 0.2mm/rev, 0.3mm/rev and 0.4mm/rev. Drill diameters: HSS drills of diameters 5mm, 6mm and 7mm are opted for the experimental studies. A set of 9 drill bits were chosen for each run of the experimental design. Tool point angle: The point angle of the drill bit was taken into account as the fourth process factor with three levels of 90, 104 and 118. The point angles were ground on a set of 9 drill bits each. Each experimental run had a new drill bit and a new composite laminate. Sizing of the GFR laminates (using CATIA): Number of slabs required for each drill diameter: 9 Number of holes to be drilled in each laminate: 80 Maximum tool travel distance in x-y direction: 250 mm x 145mm Cutting allowances to be given: 4 to 5 mm. Different ways of drilling 80 holes (rows*columns): 1*80 2*40 4*20 8*10 5*16 The calculations for sizing of each type of laminate was done using the modelling software, CATIA. After trying different combination of drilling 80 holes in each laminate, the most optimum way was chosen which would give us the required number of slabs needed for the experiments by minimum material consumption. The optimum calculations for each type of slab are shown below: Optimum laminate dimensions for a 5 mm tool diameter (Figure 3): 4*20 holes. Minimum Requirement : mm*48.5 mm. Dimensions after allowance : 245 mm*53 mm. Optimum laminate dimensions for a 6 mm tool diameter (Figure 4): 8*10 Holes. Minimum requirement: mm*115.8 mm. Dimensions after allowance: 150 mm*120 mm 34

4 Optimum laminate dimensions for a 7 mm tool diameter (Figure 5): 8*10 Holes. Minimum requirement: mm*135.1 mm. Dimensions after giving allowance: 173 mm *140 mm. Experimental Design: For the experimental study, the tool factors have been used as the control factors whereas the material factors were kept constant. The various tool factors and the different levels of each parameter used in the experiment are shown in Table 1. Experimental Setup: CNC Vertical Machining Centre (Figure 6) was used for drilling operation on the composite laminates. A fixture was designed for each drill diameter, to hold the work piece in position (Figure 6) during drilling. There were a total of 27 laminates and in each laminate 80 holes were drilled (Figure 7). Measuring Chisel Edge wear The chisel edge of the drill bit is subjected to maximum wear during the drilling operation. Therefore, the change in the length of the chisel edge before and after the drilling operation For the present experimental study, four process factors and three levels of each factor has been taken into consideration and the optimum number of experiments per run are determined using Taguchi s L9 Orthogonal Array[9,10] and number of replications of each experiment was set to 3, thus leading to a total numbers of 27 experiments. The various experiments as per Taguchi s L9 experimental design are shown in Table 2. 35

5 was taken as a measure to show the amount of tool wear due to drilling of the GFR Composite. Tool room microscope was used for measuring the chisel edge length. The precision of the Tool room microscope was mm (Figure 8). The undeformed chisel edge length was measured accurately for each drill bit before and after the drilling operation corresponding to each experimental run. The difference in chisel edge length before and after the drilling operation was measured and considered for the chisel edge wear of the drill bit. Three such trials were carried out and the average of difference in chisel edge length was considered for accuracy and reliability of measured data (Table 3). 36

6 The Main effect plot for Mean (Figure 9) of chisel edge wear shows that feed rate has more influence on chisel edge wear followed by tool diameter, spindle speed and tool point angle. This is further supported by ranking of the process factors in Table 4. Figure 10 shows that the minimum chisel edge wear occurs at a spindle speed of 3000 rpm, feed rate of 0.4 mm/rev, 7 mm drill diameter and 104 tool point angle. The S/N ratio plot for chisel edge wear was based on smaller the better criterion. Based on this, the value of S/N Ratio for different levels of factor is shown in Table 5. From Table 4, the ranking of Process Factors in terms of significance on chisel edge wear is as follows: 1. Feed Rate (F) 2. Tool Diameter (Dt) 3. Spindle Speed (N) 4. Tool Point Angle (Ɵ) Analysis of Variance (ANOVA) of chisel edge wear From Table 6, the value of P-level for each process factor is limited to zero which is lesser than the level of confidence opted i.e. α=0.05. This again implies that each process factor has some significant effect on the chisel edge wear. To find the level of significance of each process factor on the chisel edge wear, the percentage contribution of each process factor towards the chisel edge wear is determined [10]. The contribution of each process factor is as shown below (Table 6) 1. Feed Rate (F) % 2. Tool Diameter (Dt) % 3. Spindle Speed (N) % 4. Tool Point Angle (Ɵ) % Micrograph analysis Figure 12 shows the micrograph image of the deformed / worn out chisel edge after the drilling operation. The image also shows the adhering/stucking of the work piece material on to the chisel edge thus displaying adhesive wear 37

7 mechanism. The abraded chisel edge says that there is significant amount of friction and abrading action between the hard glass fibers and chisel edge of the HSS drill tool confirming abrasion wear mechanism. The percentage error between the Experimental values of chisel edge wear and the values obtained from the Regression Equation is less than 10% (Table 8) for all validation experiments, which concludes that the obtained Regression Equation is reliable under the given experimental conditions. The chisel edge wear was found to be more at the ends than at the center since the cutting velocity is maximum at the periphery than at the center of the drill bit. Regression equation for chisel edge tool wear The following Regression Equation was generated for the Chisel Edge Wear : Chisel Edge Wear = *N *F *Dt *Ɵ IV. EXPERIMENTAL VALIDATION The experimental validation was carried out by considering the levels of some process factors which are not in the Taguchi s experimental design. They are Spindle speed: 1800, 2300 and 2800 rpm. Drill feed : 0.15, 0.25 and 0.35 mm/rev Drill diameter: 5, 6 and 7mm. V. CONCLUSIONS For the minimum chisel edge wear, the optimum levels of process factors are N3 (3000 rpm), F3 (0.4 mm/rev), D3 (7 mm) and Ɵ2 (104 ). From ANOVA, feed rate has been found with a percentage contribution of 53.42%, followed by tool diameter (23.44 %), spindle speed (15.59 %) and tool point angle (7.53 %) towards chisel edge wear. Micrograph analysis shows adhesion and abrasion wear mechanism responsible for chisel edge wear. The percentage error for chisel edge wear has been found out to be less than 10% from 38

8 validation experiments. Thus, the generated Regression Equations is reliable. VI. REFERENCES 1. J. Babu and Tom Sunny, Optimization of Process Factors in Drilling of GFRP Composites, International Journal of Recent Development in Engineering and Technology (2013), Volume-10, Issue-1, pp B. Ramesh, A. Elayaperumal, S. Satish Kumar, Experimental and Analytical Studies on the Determination of Hole Quality in drilling of GFRP Composites, International Journal of Applied Research in Mechanical Engineering (2013), Volume-3,Issue-1, pp S. Ranganathan, Senthilvelanb S., Gopalakannan C, Multiple Optimization in Drilling of GFRP Composites, IEEE Conference on Advances in Engineering, Science and Management (2012), pp G. Dilli Babu, K. Sivaji Babu, B. Uma Maheswar Gowd, Effects of Drilling Factors on Delamination of Fibre Reinforced Composites, International Journal of Mechanical Engineering Research and Development (2012), Volume-2, Issue-1, pp S. Jayabal and U Natarajan, Drilling Analysis of Fibre Reinforced Polyester Composites, Bull. Material Science, Indian Academy of Sciences (2011) Volume-34, Issue-7, pp K. Lipin and Dr. P. Govindan, Effect of various Process Factors on the Surface Roughness, AKGEC International Journal of Technology (2008), Volume-4, Number-2, pp C.C. Tsao, H. Hocheng, Taguchi analysis of delamination associated with various Drill Bits in drilling of Composite Material, International Journal of Machine Tools & Manufacture (2004), Volume-44, Issue-3, pp Vinod Kumar Vankanti and Venkateswarlu Ganta, Optimization of Process Factors in drilling of GFRP composite using Taguchi method, Journal of Material Research and Technology (2002), pp Erol Kilicap, Determination of Optimum Factors in drilling of GFRP Composites by Taguchi Methods, Indian Journal of Engineering & Material Sciences (2010), Volume-17, Number- 1, pp Dr. Ian Vallance & Dr. Ricky Tomanek, Introduction to Analysis of Variance (2007) 39