Multiple Kerf Quality Optimization in Laser Cutting of BFRP Composite using Grey Relational based Genetic Algorithm

FME Transactions (2020) 48, 636-650 636 Received: March 2020, Accepted: May 2020 Correspondence to: Dr Dhananjay R. Mishra, Mechanical Engineering Department, Jaypee University of Engineering and Technology, Guna-473226, India E-mail: dm30680@gmail.com doi:10.5937/fme2003636G Girish Dutt Gautam Research Scholar Department of Mechanical Engineering Jaypee University of Engineering and Technology, Guna-473226, Madhya Pradesh India


INTRODUCTION
In recent decades, the interest of researchers focused on basalt fibers due to their higher mechanical performance and eco-friendly nature. These fibers are obtained from melted basalt rocks by an energy efficient extrusion process [1]. Silicon dioxide (SiO 2 ) and aluminium oxide (Al 2 O 3 ) are the main constituents of basalt fibers. Superior thermal, electrical, abrasion, corrosion, and chemical resistant properties with higher shear and compression strength make basalt fibers and its composites suitable for a wide range of applications in automobile, aircraft, and manufacturing industries. Basalt fibers have a wide range of working temperature from -269 ºC to 650 ºC. Their composites are widely used for the production of car headliners, disc brake pads and clutch facing components, engine insulator due to their higher frictional, thermal and shock resistance properties in the automotive industries. Nowadays basalt fibers are increasingly replacing E-glass fibers and carbon fibers as a reinforcing agent of polymer matrix com-posites due to its greater tensile and compressive properties and low cost. It has a similar chemical structure to the glass with slightly higher density and higher stability in an acidic environment. Basalt composite pipes are stronger as compare to glass fiber pipes for corrosive liquids and gases transportation [2].
In recent years, the applications of BFRP composites are increased in various engineering sectors. Machining of these composites is required for their structural applications. In their conventional machining, various frictional forces are developed and reduce their cut quality. Matrix cracking, thermal damages, whiskers formation, fiber losing and fiber delamination around cutting edges are some of the major drawbacks of conventional machining of BFRP composites. Advanced machining processes such as laser beam machining (LBM), water jet machining, plasma arc machining etc. compared to the conventional machining techniques provide superior cut quality during FRP composite machining. These processes also improve the production rate. [3].
Laser beam cutting (LBC) proves its wide acceptability for machining of FRP composites to obtain precise and complex profile cut. It provides a better cut quality and operation preciseness with low cost and improved machinability. In LBC, a high energy focused laser beam is utilized for removal of material from the work surface through melting and evaporation caused by the thermal energy of beam [4]. As no cutting force is present in LBC, it offers minimal delamination and matrix cracking as compared to other machining techniques. This process is able to provide complex shapes with accurate geometries of cut edges with higher material removal rate for a wide range of materials such as metals, non-metals, ceramics and composites [5]. The geometry of the laser cut is defined in the terms of its kerf quality characteristics such as kerf width (KW), kerf deviation (KD) and kerf taper (KT). These parameters decide the quality, geometrical accuracy and precisions of the cut. Moreover, in laser cutting, a taper in cut edge geometry always exists due to the converging-diverging nature of laser beam and known as kerf taper [6][7].
Numerous researchers have analysed the effect of different laser cutting parameters on the different geometrical quality characteristics of the laser cut such as top and bottom kerf width, top and bottom kerf deviation and kerf taper for FRP composites. Mathew et al. [8] have been investigated the effect of cutting speed, pulse energy, pulse duration, pulse repetition rate and gas pressure on the top and bottom kerf widths, kerf taper and heat affected zone in pulsed Nd:YAG laser cutting of carbon fiber reinforced plastic (CFRP) composites. They observed that pulse repetition rate and pulse energy were the most influencing factors for the kerf widths. They also found that at high cutting speed a no cut-situation is observed. Negarestani et al. [9] employed a nano-second pulsed DPSS Nd:YAG laser for cutting of CFRP composites to investigate the kerf taper and material removal rate with using mixed reactive and inert gases. They observed that higher cut quality can be achieved through the use of low oxygen content assistant gas. Leone and Genna [10] used a 150W Nd:YAG pulsed laser for cutting of CFRP composite. They observed that an accurate selection of the laser cutting parameters can reduce heat affected zone (HAZ) and KT. Cenna and Mathew [11] developed a model based on energy balance equations to predict kerf width and kerf taper angle during laser cutting of glass fiber reinforced polymer (GFRP) and aramid fiber reinforced polymer (AFRP) composite samples of varying thickness. They have revealed that for both materials average kerf angle decreases with increasing cutting speed.
Gautam and Pandey [12] evaluated the effects of different laser cutting parameters such as lamp current, pulse width, pulse frequency, compressed air pressure and cutting speed on top and bottom kerf deviation in Nd:YAG laser cutting of AFRP composite. They found that the lamp current is the highest affecting factor for both the top kerf deviation and bottom kerf deviation followed by pulse frequency.
In the detailed literature survey, limited research work is found for laser cutting of BFRP composites as individual or ingredient of hybrid laminates. Gautam and Mishra [13] performed the laser cutting of 1.60 mm thick Basalt fiber based composite sheet. They also employed firefly based multiobjective optimization approach to optimize kerf width, kerf deviation and kerf taper. They observed that lamp current influenced the kerf width and kerf taper remarkably. They also found that pulse frequency has negligible effects on all kerf quality characteristics. In another study, Gautam and Mishra [14] performed the laser cutting of 1.35 mm thick Kevlar-29 and Basalt fiber based hybrid composite sheet. They observed that the geometrical accuracy of the cut not only affected by the laser cutting parameters but also by the specific properties of Kevlar-29 and basalt fibers with epoxy resin. In another study [15], they observed that lower lamp current, pulse frequency and compressed air pressure whereas higher cutting speed is required for dimensionally accurate laser cutting of Kevlar-29 and Basalt fiber based hybrid composite sheet.
In LBC, it has been observed that achieving a better cut quality is a tough task due to the nonlinear relationship between the input and output parameters. To overcome this problem, various researchers employed different optimization techniques to obtain optimum levels of laser cutting parameters for achieving higher cut quality. El-taweel et al. [16] used Taguchi methodology (TM) to find optimum laser cutting parameters such as laser power, cutting speed, assistance gas pressure and laser mode setting to minimize kerf width, dross height, and slope of the cut for KFRP composite. Choudhury and Chuan [17] found significant improvement in kerf width and surface roughness using optimal settings of cutting parameters such as nozzle diameter, material thickness and cutting speed in CO 2 laser cutting of GRRP by using resonse surface methodology (RSM). They observed that better surface finish and kerf width achieved at small nozzle diameter.
In multi-objective optimization problems, weight factor determination for each quality characteristic is the key issue. Grey relational analysis provides an efficient solution for the simultaneous optimization of multiple quality characteristics containing discrete data. GRA proves its suitability in various field of engineering such as manufacturing, economic and management systems [18].
Adalarasan et al. [19] employed a hybrid approach of grey based response surface methodology (GRSM) for predicting the optimal combination of laser cutting parameters such as laser power, pulsing frequency, cutting speed and assist gas pressure for improved kerf width, surface finish and cut edge slope in CO 2 laser cutting of metal matrix composites. They observed a substantial improvement in the cut quality characteristics by employed hybrid technique. Rao and Yadava [20] employed a hybrid approach of TM and GRA to minimize the kerf width, kerf taper, and kerf deviation together during pulsed Nd:YAG laser cutting of a nickel -based super alloy. They considered oxygen pressure, pulse width, pulse frequency, and cutting speed as process parameters. They observed that the employed approach improved all kerf quality characteristics remarkably.
Tamrin et al. [21] used GRA to obtain a single optimal set of laser cutting parameters such as laser power, cutting speed and compressed air pressure for minimal HAZ and cut diameter in three different thermoplastics such as poly-methyl-methacrylate, polycarbonate and polypropylene. Mishra et al. [22] employed GRA technique for single index optimization of top and bottom kerf deviations during pulsed Nd:YAG laser cutting of a novel 2.34 mm thick Kevlar-29, Basalt and Glass fiber based hybrid FRP composite laminate. In recent years, GRA is successfully coupled with genetic algorithm by some researchers. They observed that hybrid GRA is able to improve optimum results significantly compared with alone GRA [23].
In a detailed literature survey, it is observed that the potential of laser beam machining for BFRP composites is yet to be explored. An optimum set of laser cutting parameters are also essential for the economic and competent cutting. Keeping this fact in mind, a detailed parametric study has been conducted to investigate the effects of five different laser cutting parameters like lamp current (I), pulse width (PW), pulse frequency (f), compressed air pressure (p) and cutting speed (S) on multiple kerf quality characteristics viz. top kerf width (TKW), bottom kerf width (BKW), top kerf deviation (TKD), bottom kerf deviation (BKD) and kerf taper (KT) in pulsed Nd:YAG laser beam cutting of BFRP composite laminate. A grey relational analysis based genetic algorithm (GRGA) optimization technique has been applied to optimize multiple kerf quality characteristics as a single performance index. Finally, a confirmation test has been carried out to validate the optimum results obtained by the employed approach. The paper also discusses the effect of significant control factors on the multiple kerf quality characteristics.

Material & Experimental Set-up
In the present research, BFRP composite laminate has been used as workpiece material. In this composite, basalt fiber has been used as the reinforcing agent in the epoxy-based matrix phase. The woven mat of Basalt fibers was supplied by Aerotech Technical Textile, Mumbai, India having thickness 200 gsm. Moreover, epoxy resin-520 and hardner-509 have been used as a polymeric binding agent, manufactured by Electro coating & Insulation Technical Pvt. Ltd., Pune, India. Table 1 and 2 contain the properties of employed woven basalt fabric, epoxy resin-520 and hardener-509 respectively. The 1.60 mm thick BFRP composite laminate has been fabricated by using the hand-layup technique in the ideal laboratory environment. In the fabrication process of BFRP composite laminates, a mild steel mold having dimensions 300 mm×300 mm×20 mm is used. In the literature survey, it has been observed that the physical properties of the laminate depend on the matrix impregnation and the orientation of the fibers. Therefore, the orientations of basalt fiber mats in fabricated laminates have been kept [B-0º/B-90º/B-0º/B-90º/B-0º/B-90º/B-0º] for the seven layers. The orientation angle of (0°/90°), has been taken for the better flow of the matrix because epoxy needs a larger space to flow. The dimensions of the fabricated laminate were 150 mm×250 mm×1.60 mm. The volume and weight fraction for fiber 87.50 % and 12.50 % and for matrix as 78.75 % and 21.25 %, found in fabricated laminate. Moreover, theoretical density of the BFRP laminate was observed 0.60 g/cm³. These physical properties ensure the higher mechanical properties of the laminate because of holding higher fiber volume. The process for BFRP composite fabrication is shown in Fig. 1.
The cutting experiments for BFRP composite laminate are performed by a pulsed Nd:YAG laser beam machine developed at Raja Rammana Center of Advanced Technology (RRCAT), Indore, India, having 250W average output power and a three axes CNC-controlled table using compressed air as the assist gas. The impact angle between the laser beam and composite surface kept 90° throughout the experimentation process. Stand-off distance also fixed at 1 mm during experimentation.

Design of experiments
In the literature survey, it is has been observed that the kerf quality characteristics of the cut surface depend on the leading laser machining parameters such as lamp current (I), pulse width (PW), pulse frequency (f), compressed air pressure (p) and cutting speed (S). A range of pilot experiments has been performed to minimize the suitable range of laser cutting parameters. Pilot experiments also help to define the lower and higher tolerable ranges of parameters for acceptable cut quality. In this research, the experiments have been designed according to the box-behnken design based on the response surface methodology. The box-behnken design is selected due to fewer design points as compared to full factorial design and central composite design with avoiding an extreme combination of factors. Five variable laser cutting parameters (I, PW, f, p and S) with three levels of each have been used to conduct forty-two experiments. The levels of the laser cutting parameters are shown in Table 3.

Kerf quality characteristics
For each combination of cutting parameters, a 30 mm long straight cut has been performed to ascertain kerf quality characteristics. The kerf width indicates the loss of material in cut and kerf deviation represents the waviness of kerf, while kerf taper shows the difference in the top kerf width and bottom kerf width of the cut. The measurement of the kerf width has been performed by a stereo optical microscope with a maximum magnification capacity of 160X. Six KW's (viz. K 1 , K 2 , K 3 , K 4 , K 5 , and K 6 ) have been measured on both top and bottom side of the cut. The average values of kerf are acquired in each cut for analysis. Equation 1, 2, 3, 4 and 5 have been used to calculate values of TKW, BKW, TKD, BKD, and KT, respectively.
where, t is the thickness of the BFRP composite laminate. Figure 2 shows the complete process of experimentation and measurement. The variation of measured values of TKW and BKW and calculated values of TKD and BKD, and KT are shown in Fig. 3, 4 and 5, respectively.

GREY RELATIONAL BASED GENETIC ALGO-RITHM (GRGA) OPTIMIZATION TECHNIQUE
The Grey relational based genetic algorithm (GRGA) optimization technique contains two established optimization approaches i.e. grey relational analysis (GRA) and genetic algorithm (GA). In this approach, GRA is used to identify relationships between process parameters and output responses [14,[22][23]. Calculated grey relational grades considered as a single performance quality index for all responses. A secondorder regression mathematical model is developed by using calculated grey relational grade. This model is used as an objective function for GA based optimization process. The technique of GRGA is disclosed in two phases as shown in Fig. 6. Grey relational analysis was introduced by Prof. Deng in 1982. He found that GRA is able to provide a decision about the system containing incomplete or complete information. GRA offers competent solution to the uncertain and discrete data system. It provides interrelationship between the process parameters and performance characteristics based on grey system theory. In GRA, the system information is determined by black and white color. No information situation of a system is represented by the black color. While white color represents a system having some information. The information level between black and white denotes by grey color. In other words, in a grey system, part information about the system is certain and part information is uncertain or unknown. So, grey system provides some certain and some uncertain relationships among the factors in a system. GRA is a measurement process of the absolute value of the data variance between sequences, and it ensures the approximate correlation between sequences. In GRA, grey relational generating is the first step to pre-processing of the entire range of data. Grey relational generating is necessary to develop a comparable sequence of original scatter data sequence. Thus, in grey relational generating, scatter data is transformed into normalized, scaled and polarized form in the range between 0 and 1. Three equations are used for normalization process shown in Eq. 6, 7 and 8 i.e. larger-the better, nominal is best and smaller-the better.
where, Z ij is the normalized value for i th experiment for j th response, Y i is thei th normalized value and Y ij is the i th normalized value for j th response. Equation 8 is used for the normalization process in this research because all five kerf quality characteristics (viz. TKW, BKW, TKD, BKD, and KT) are the smallerthe better quality characteristics. Then, grey relational coefficients (GRC's) are calculated by using Eq. 9.
where, GC ij is the grey relational coefficient for the i th experiment and j th response. Δ is the absolute difference between Y oj and Y ij ; here Y oj is the ideal normalized value of j th response. Δ min and Δ max are the minimum and maximum values of Δ, respectively. λ is the distinguishing coefficient having range 0 ≤ λ≤1. In this study, the value of λ is taken as 0.5. Δ min and Δ max are calculated by Eq. 10 and 11.
Weighting ratio 1:1:1:1:1 has been set for all five kerf quality characteristics for incorporating the GRC's into the grey relational grade for each experiment. Grey relational grades (G i ) were computed as per Eq. 12.
where, m is the number of responses.
Then, the mathematical model of the calculated Grey relation grades is used as an objective function for Genetic Algorithm (GA). It is one of the most popular evolutionary approaches for the optimization of the linear and the nonlinear complex problems. GA is able to identify the global optimum point without the limitation of the gradient methods. GA is based on Darwin's principle of natural selection (i.e. survival of the fittest).
The working of GA starts with a population of initial solutions generated at random. Then, the fitness /goodness value of the objective function is calculated in the case of a maximization problem. If the objective function has a minimization problem then it is converted into a corresponding maximization problem. Thereafter, the population of solutions is modified by using different operators namely reproduction, crossover, mutation and others. It is considered that all the solutions in a population may not be equally good in terms of their fitness values. Therefore, an operator named reproduction is utilized to select good solutions using their fitness values. It forms a mating pool consisting of good solutions probabilistically. The mating pool can contain multiple copies of the particular good solution.
The size of the mating pool is kept equal to the population of solutions considered before reproduction. Thus, the average fitness of the mating pool is expected to be higher than the pre-reproduction population of solutions. The proportionate selection (Roulette-Wheel selection), tournament selection, ranking selection are various types of reproduction schemes. The mating pairs or the parents are selected randomly from the mating pool.
The mating pair participates in the crossover which depends upon the value of crossover probability. The properties between the parents and new children are exchanged in the crossover stage and mutation is occurred. It is considered that if the parents are good, the children are expected to be good. Mutation represents the sudden change of a parameter or improvement in the gene of the child. In a GA search, the mutation is required to achieve a local change around the current solution and shift it to the global solution. After the reproduction, crossover and mutation are applied to the whole population of solutions. This whole process represents the one generation of GA [27]. This process is repeated until to achieve the best fitness values of function.

GRGA based multiobjective optimization
GRA has been applied to transform scatter data in the normalized form to obtain relationships between laser cutting parameters and kerf quality characteristics. All kerf quality characteristics are considered as smaller-the better characteristics. Equation 8 has been used to perform linear normalization of all five kerf quality characteristics. Table 4 shows the normalized values and deviational sequence for TKW, BKW, TKD, BKD, and KT. Calculated GRC' s and GRG's for all responses with their ranks are shown in Table 5. The values of Grey relational grade show a single representation for all kerf quality characteristics for a combination of cutting parameters. The highest value of GRG has been observed at the twenty-one experimental run as 0.8783. The response means of calculated grey relational grades are shown in Table 6. By response means, it has been found that the optimal combination of laser cutting parameters is at lower levels of compressed air pressure and cutting speed, and a moderate level of lamp current and higher levels of pulse width and pulse frequency. At these levels, the values of cutting parameters are lamp current at 180 Amp, pulse width at 2.6 ms, pulse frequency at 30 Hz, compressed air pressure at 8 kg/cm 2 and cutting speed at 50 mm/min. It has been observed in the analysis that grey relational grades are highly influenced by lamp current followed by compressed air pressure, pulse frequency, pulse width and cutting speed.
After calculating grey relational grades for all the experimental trials, a second-order regression model has been developed and shown in Eq. 13.
In the present work, the accuracy and adequacy of the developed mathematical model of grey relational grades have been decided by using the surface and contour plots of the standard error of design as shown in Fig. 7.
The circular shape of these plots demonstrates that the developed model has a better degree of fitness. This is due to the uniform trend of the standard error of design with respect to control parameters. The degree of fitness shows that the sample data of the developed model follows the normal distribution.
Basically, it determines whether the sets of observed data match the expected outcomes through the applicable model. The analysis of variance (ANOVA) has been performed to determine the fitness and adequacy of the developed quadratic model. The Svalue and coefficient of determination (R 2 and adjusted-R 2 ) values of the developed model have been found as 0.0477513, 90.76 % and 81.96 %, respectively. These values show that the developed model is adequate and significant for data prediction. From the ANOVA table, it has been found that F-value and P-value of developed model are in the acceptable range and confirm the adequacy of the model. The developed mathematical model as shown in Eq. 13 has been used as an objective function to minimize TKW, BKW, TKD, BKD and KT for GA based optimization. Before the execution of GA, its control parameters have been defined such as population size, crossover probability, and mutation probability etc. Then an initial random population has been generated by employing MATLAB M-files coding. In the present research work, initial population size has been considered as 50. Two points based crossover function having a crossover probability of 0.8 with uniform mutation function and mutation probability of 0.01 are chosen for GA operator's values. Initially, the generation limit has been set to 300. Then, the optimum values of process parameters have been selected based on the best fitness value. During the execution of GA, a lower bound [160,2,20,8,50] and an upper bound [200, 2.6, 30, 10, 200] have been used for five laser cutting parameters as lamp current, pulse width, pulse frequency, compressed air pressure and cutting speed, respectively. The best fitness value for the desired objective function is achieved after 151 generations, shown in Fig. 8. The values of the best fitness and mean fitness have been found at 0.852255 and 0.852257, respectively. The optimal values of different laser cutting parameters have been found by using GRGA approach as lamp current at 184.508 Amp, pulse width at 2 ms, pulse frequency at 30 Hz, compressed air pressure at 8 kg/cm 2 and cutting speed at 50 mm/min respectively.

Experimental validation
Experimental validation of optimal solutions has been performed by using optimal settings obtained by both GRA and hybrid GRGA approach. As mentioned in the previous section, the optimal solutions achieved by using GRA and GRGA technique are as I= 180 Amp; PW= 2.6 ms, f= 30 Hz, p= 8 kg/cm 2 and S= 50 mm/min and I=184.5 Amp; PW=2 ms; f= 30 Hz; p= 8 kg/cm 2 ; and S= 50 mm/min respectively. The aim of these optimal solutions is to minimize TKW, BKW, TKD, BKD, and KT. The results of the confirmation test for TKW, BKW, TKD, BKD, and KT are tabulated in Table 7. It has been found that GRGA approach significantly improved the kerf quality characteristics as compared to optimal settings of parameters obtained by GRA. An improvement of 13.33 %, 13.29 %, 23.52 %, 23.07 %, and 10.83 % has been observed in TKW, BKW, TKD, BKD, and KT, respectively with the GRGA setting against GRA optimal parameter settings. It has been observed that GRGA provides an overall improvement of 16.80 % for all kerf characteristics as compared to GRA. The maximum improvement is observed in TKD followed by the BKD, TKW, BKW, and KT.

Parametric effects analysis
The effect of different pulsed Nd:YAG laser cutting parameters on the multiple kerf quality characteristics in a single performance index represented by GRG during machining of BFRP composite laminates have been analysed by surface and contour plots. Figures 9-12 visually depicts the combined effects of I-PW, I-f, I-p and I-S on the values of the grey relational grades. From Fig. 9-12, it has been revealed that an increase in the value of lamp from 160 to 180 Amp, steps up the values of grey relational grades. However, the values of grey relational grades are decreased in the further increase in lamp current from 180 to 200 Amp. This may be due to that a higher lamp current increase the energy absorption tendency of BFRP composite surface through the incident laser beam. Whereas, basalt fiber has higher heat resistant properties so higher energy is required to smooth and higher cut quality. Moreover, higher lamp current (200 Amp) also increase the rate of vaporization of epoxy resin and affect the geometrical quality of cut.
Optical microscopic images of top and bottom kerf widths with parametric settings as lamp current 180 Amp, pulse width at 2.3 ms, pulse frequency at 20 Hz, compressed air pressure at 8 kg/cm 2 and cutting speed at 100 mm/min are shown in Fig. 13 (a-b). By these graphs, it can be inferred that the higher values of pulse width (2.6 ms) are able to provide the higher values of grey relational grades for the satisfactory quality of multiple kerf characteristics. This is due to the fact that interaction time between the incident laser beam and the composite surface is increased at higher pulse width (2.6 ms) and affect kerf quality characteristics remarkably. The combined effects of f-p and f-S on the values of grey relational grades are shown in Figure 17-18. These figures show that higher value of grey relational grades found at the higher setting of pulse frequency (30 Hz) with lower settings of compressed air pressure (8 kg/cm 2 ) and cutting speed (50 mm/min). This may be due to that higher pulse frequency provides sufficient time to burn fibers and epoxy resin of BFRP composite laminates. Figure 19 (a-c) shows the optical microscopic images of kerf width at lower, moderate, and higher levels of pulse frequency. Moreover, a lower value of pulse frequency also increases the tendency of the fiber's disorderliness of burning. The combined effects of p-S on the value of grey relational grades are shown in Figure 20. It has been observed that with the increase in the values of compressed air pressure and cutting speed, the values of grey relational grades decrease. It is a fact that higher compressed air pressure (10 kg/cm 2 ) and cutting speed (200 mm/min) increase the quality of kerf characteristics because of their combined effects. These effects provide the continuous and fast removal of dross and burnt fibers from the kerf edges. It decreases the kerf deviation and improve the geometrical accuracy of the cut. Whereas in the present research, due to the higher burning point of basalt fiber (approx. 1500 ο C), BFRP composite requires low cutting speed to the proper burning of fibers. Moreover, Basalt fiber also has a unique property to stop burn with the removal of the heat source. Besides, at the higher compressed air pressure (10 kg/cm 2 ), possibilities for the occurrence of high-temperature oxidation reaction at the composite surface are also minimized. During Nd:YAG laser cutting of BFRP composite, irregular shapes have been also observed at the bottom side of the cut. These shapes are formed due to the difference in thermal properties between basalt fiber and epoxy matrix. This is due the heat transfer by the fiber filaments to the polymer matrix. Epoxy has vicious nature, so when it melted, ejection is difficult and heat accumulation takes place at the bottom side of the cut and results in droplets deposition as shown in Fig. 21 (ac). Figure 22 (a-b) shows the peeling off structure of basalt fibers at the top side of laser cut. This is due to the fact of the heat accumulated by the basalt fibers are sufficiently high to decompose polymer matrix without burning of fibers. It is also shown in the SEM images of the cut edge surface in Fig. 23 (a-b). Moreover, it has been observed that heat conduction properties of basalt fiber and epoxy resin also responsible for improper laser cutting of BFRP composite.

CONCLUSION
In the present study, an attempt has been made to cut Basalt fiber reinforced polymer composite laminate by using a pulsed Nd-YAG laser system. To ascertain the better geometrical accuracy of the cut, major kerf quality characteristics such as top and bottom kerf widths, top and bottom kerf deviations and kerf taper have been simultaneously optimized by using a hybrid grey relational based genetic algorithm optimization approach. The aim of this research is to pave the way for geometrically accurate laser cutting of Basalt fiber reinforced polymer composites. The following conclusions have been drawn by the present research: • In the present research, efficient cutting of 1.60 mm thick Basalt fiber reinforced polymer composite laminate by using pulsed Nd:YAG laser system have been attempted. • The geometrical quality of the cut is quantified in the terms of top kerf width (TKW), bottom kerf width (BKW), top kerf deviation (TKD), bottom kerf deviation (BKD) and kerf taper (KT). • A grey relation based genetic algorithm hybrid approach is employed to single index optimization of multiple kerf quality characteristics. • The optimum settings of laser cutting parameters obtained by using GRA based multi-objective optimization are lamp current 180 Amp, pulse width 2.6 ms, pulse frequency 30 Hz, compressed air pressure 8 kg/cm 2 and cutting speed 50 mm/min. • The optimal settings of cutting parameters obtained by GRGA are lamp current 184.5 Amp; pulse width 2 ms; pulse frequency 30 Hz, compressed air pressure 8 kg/cm 2 and cutting speed 50 mm/min. • GRGA provides an overall improvement of 16.80 % as compared GRA in kerf quality characteristics at optimal parametric settings. • Hybrid GRGA approach is better than GRA for predicting the optimal laser cutting parameters. • From the analysis of results, lamp current has been found the most significant factor for all kerf quality characteristics followed by pulse width, compressed air pressure, pulse frequency and cutting speed in pulsed Nd:YAG laser cutting of BFRP composite laminates. • The authors have confidence that the outcomes of this study will lead the researchers and modern industries to cut the FRP composite materials with higher accuracy and geometrical precision.