Abstract
Grinding is a choice for obtaining high surface quality and closer dimensional tolerance. For meeting this objective economically, the material removal rate (MRR) must be sacrificed to certain extent. The MRR could be increased by either increase in wheel speed, depth of cut, and feed rate. An increase in MRR increases the surface temperature leading to thermal defects on surfaces. Improving the MRR without compromising the surface quality is a challenging objective. Many investigations are progressing for machining various materials under different cooling environments to meet such challenges. This experimental novel aim is to investigate the performance of Al2O3 nanofluid in high-speed grinding of EN31 steel under flood cooling method for reduction of surface roughness and cutting zone temperature. Taguchi’s full factorial design was employed for experimental investigation. The factors such as feed, depth of cut and cutting fluid environment were considered for analysing the responses of cutting zone temperature and surface roughness. The thermal analysis on the work piece was carried out with experimental values by the finite element analysis method. The nanofluids outperform in terms of reduction of surface roughness and downsizing cutting zone temperature. The proposed nanofluid-based grinding significantly reduced the surface roughness and cutting zone temperature.
1. Introduction
Surface grinding on EN31 steel is vital operation for meeting the functional requirements of its application such as textile industrial tools, measuring gauges, and precision dies. Large heat generated while grinding due to multipoint cutting tool (abrasive wheel), high friction between work and wheel, rapid chip formation, and the grinding zone is completely adiabatic reported by Malkin and Guo [1]. High temperature at the cutting zone causes faster tool wear and thermal defects on surfaces (surface burning, surface crack, physical and chemical changes not only on the surface but also up to some depth stated by Paul and Chattopadhyay) [2]. But it is indispensable to control the cutting zone temperature to control surface quality. Cutting fluids are usually employed for this task. Because the cutting fluids are used for braking chips and prevent corrosion reported by Henriksen [3], they flush away the broken chips, reduce tool and work piece temperatures, and also act as lubricant to reduce the friction at the interface of wheel and work piece reported by Suresh et al. [4]. Chen et al. found that the increase of tool life improved surface finish and tolerance [5]. Based on the industrial practices, dry machining, flood/wet cooling, solid coolants, high-pressure cooling, and minimum quantity lubrication (MQL) environments were used for grinding in which wet cooling practices are obvious. Many disadvantages were listed such as (1) high cost for removing excess heat reported by Klocke and Eisenblatter [6] and also by Sreejith and Ngoi [7], (2) less heat dissipation due to difficulty in supplying cutting fluid at cutting zone when rapid chip formation, and (3) high friction analysed by Brinksmeier et al. [8]. Cutting fluid causes techno-environmental problems like health hazard to the operator and environment pollution in disposal [9], and such cutting environment is evident in the industries. For preventing such demerits, a new kind of cutting fluids is evolved. Some examples are as follows: Max Mist ST-2020 yielded lowest net manufacturing costs of any fluid and environmentally acceptable vegetable oil-based lubricant as reported by Jung Soo et al. [10] and eco-friendly cutting fluid TRIM E709 emulsifier as explained by Vasu and Manoj Kumar [11].
2. Research Gap
Most of the works are reported in nanofluid as cutting fluid in MQL environment. Some of them are as follows: Khan et al. [12] stated that nanofluids are stronger and possess temperature-dependent thermal conductivity at low concentration which enhances process performance in many applications. But the author’s investigation was MQL on turning in AISI 9310 steel with vegetable oil-based cutting fluid. Mao et al. [13] investigated nanofluid performance in grinding with MQL environment. The analysis was varying the nanofluid concentration with other parameters. The finding was higher concentration of nanofluid reduces the grinding force, tool wear, surface roughness. Vasu and Kumar [11] mixed 1% Al2O3 nanoparticles with TRIM E709 emulsifier to form nanofluid and used as cutting fluid in MQL environment for machining EN31 steel at low speed cutting for his investigation. Subhash et al. [14] considered two kinds of nanofluid as 1% and 4% Al2O3 nano particles separately blended with Max Mist ST-2020 vegetable oil and used them for turning in a lathe of Nicrofer C263 superalloy in MQL environment to study the nanofluid roll in turing that material. Since the cutting zone heat reduction and good surface finish are main objectives, alumina has good thermal conductivity and good tribological characteristics. The enhanced functional behaviour, wear resistance, and fatigue life of high chromium steel components are depending heavily on their higher surface quality [15]. The Taguchi-coupled grey relational analysis has been used to determine the best turning parameters for the multiperformance characteristics in the turning process. To do this, an interchangeable two-phase straight cemented tungsten carbide-cobalt mixed (WC-Co) insert grade (CSTC—K20) tool has been developed. While cutting speed, feed rate, and depth of cut were regarded as the controllable process parameters, flank wear and surface finish were considered as performance attributes. Three process parameters were considered at four levels in the Taguchi L16 orthogonal array used to arrange the experiments [16]. The process parameters were predicted for obtaining the best surface finish in surface grinding of EN24 steel. The prediction model was developed from ANOVA results of response surface methodology [17]. Based on the cross section sensitivity and matching restrictions of solid end mills, an iterative optimization approach was developed for the bearing and geometric parameters of grinding wheels [18]. This research interest is unique. As the flood cooling type environment is still obvious in much industry, this work tried to enrich flood cooling environment by suspending alumina nanoparticles for investigating nanofluid performance in high-speed surface grinding on EN31 steel at high wheel speed. Conventionally, the nanofluids were utilized in minimum quantity lubricant (MQL) type lubrication system to achieve cutting zone temperature reduction. But they cannot be reused. This investigation considered nanofluids in the flood cooling system and could be reused multiple times, so the coolant cost will be less than MQL.
3. Experimental Design
The EN31 steel is high-speed grounded by three different machining environments: dry (natural flow atmospheric air cooling), with the use of conventional coolant and with the use of nanofluid. Taguchi full factorial design was employed to conduct the experiments to observe the cutting zone temperature and surface roughness on grounded materials. The results were compared. The thermal analysis was done based on the experimented observations and presented. The DOE Taguchi full factorial design is employed for the experimental design. The work piece tested chemically to ensure its originality of EN31 steel. The tested values are presented in Table 1. The factors and responses considered for the experimental design are furnished in Tables 1–3. The constant parameters of the experimental setup are furnished in Table 4. Taguchi full factorial design for the case is furnished in Tables 5–7.
4. Machining Environment
4.1. Dry Machining
The dry machining practices exist for meeting product requirements economically because the cutting fluid consumes more cost. Dry machining means there is no cutting fluid used during the machining process. The temperature rise of the cutting tool is very high when dry machining induces reduction of tool wears and tool life. The chips generated at dry machining do not wash away, and they cause deterioration on the machined surface.
4.2. Wet Machining
Wet machining is the one in which the cutting fluid is used. Here, the eco-friendly cutting fluid TIRM SOL LC sf branded general-purpose emulsion and nonchlorinated, siloxane-free emulsifier is used. Since it is heavy duty cutting, the mixing ratio 1 : 10 was preferred. The emulsions are suspensions of oil droplets in water and have a milky appearance with an oil droplet size in the range 0.005 mm to 0.002 mm. They will provide good cooling with moderate lubricity and overcome demerits highlighted in the literature.
4.3. Nanofluid
Since nano Al2O3 particles have superior tribological and antitoxic properties reported by Jung et al. [19], it is preferred in this study. Based on the literature, the percentage of mixing is 1% which is customary practice for investigation. Here, the alumina nanopowder is mixed with TIRM SOL LC sf cutting fluid in the ratio of 1 : 100, that is, one gram of alumina nanopowder for 100 grams of TIRM SOL LC sf cutting fluid by weight. After mixing, the fluid was stirred continuously about 8 to 9 hours in a magnetic stirrer for reducing a particle size about 5 nm and homogeneous mixing of nanopowder with cutting fluid. Then, the fluid is used as wet coolant with water in the ratio of 1 : 10. The prepared nanofluids were used in the flood form during experimentation.
4.4. The Work Piece
Based on the demand of its applications including dice ball and roller bearings, swaging dies spinning tools, punches, taps, ejector pins, gauges, and cylindrical, conical, and needle rollers, the EN31 steel is preferred for this study. EN31 steel is most commonly used high carbon steel which poses a good quality for wear resisting machine parts and for press tools. The work piece size is 50 × 50 × 10 mm (with centrally drilled with depth of 5 mm for temperature measurement).
5. Experimentation
The experimentation is to investigate the influence of machining environments and nanofluid performance evaluation in high wheel speed (29830 mm/sec) surface grinding; the other factors are feed (mm/sec) and depth of cut (microns). The measure of performance is the surface roughness in μm and cutting zone temperature in degree centigrade. The omega makes HH801 A dual input K/J digital thermometer with thermocouple accuracy. ±1.1°C is employed for measuring temperature. The K-type mode is used for the measurement. The work piece has a drilled hole of 5 mm deep from bottom and the thermocouple end attached. The temperature measurements are up to 5 mm deep of from the surface. The Taylor Hobson Surtronic3+ contact type profile meter was employed in surface roughness measurement with 0.8 mm cut of length, and the sampling number is five. Initially, the dry grinding environment is considered. The minimum feed 100 mm/sec was set and was kept constant, and the depth of cut varied from 10 μm to 40 μm with the step of 10 μm. Then, the feed is increased to 125 mm/sec, 150 mm/sec, and finally 175 mm/sec. For each feed setting, the trials are conducted with four different depth-of-cut settings say 10 μm, 20 μm, 30 μm, and 40 μm. These settings were repeated for wet cooling environment and nanofluid environment. Each trial is repeated five times, and the temperature and roughness values were recorded. The average of values is considered for minimizing the observation error. The experimental setting and observed values are tabulated in Tables 5–7 as responses for the experimental design. Table 5 is observation at dry machining environment, Table 6 is for conventional coolant (TIRM SOL LC sf), and Table 7 is for nanofluid machining environment.
6. Result and Discussion
The cutting zone temperature reduction is the primary objective of this work. It is observed that the cutting zone temperature variation is significant with respect to the grinding environment, feed, and depth of cut in which the cutting zone temperature with respect to grinding environment is most significant. At first, the depth of cut is kept constant and varying machining environment and feed. The behavior is plotted in Figure 1 such as first row graphs are when the depth of cut is 10 μm and 20 μm, the second row is when the depth of cut is 30 μm and 40 μm. The percentage of heat reduction was computed. The surface temperature was found higher in dry than wet in nanofluid environment. Hence, Table 8 shows the percentage of reduction for each case. The average reduction of temperature was considered for the calculation in percentage. It was the ratio of average of temperature reduced by wet machining to the average of temperature in the conventional method (dry machining) by using equation (3). The comparison of nanofluid performance by using the ratio of average of temperature reduced by nanofluid to the average of temperature observed with the use of the conventional method (conventional coolant) by using equation (4).
Similarly to the behaviour at constant feed rate, the temperature reduction performance by varying the depth of cut and machining environment was considered. The graphical representation is presented in Figure 2. The first row is the surface temperature with respect to depth of cut and cutting fluid and lubricant used at a constant feed of 100 and 125 mm/sec, and the second row is when 150 mm/sec i and 175 mm/sec. The percentage of temperature reduction for the abovesaid cases is consolidated in Table 9. From Figure 2 and Table 9, it is evident that the nanofluid temperature reduction is significant than conventional cutting fluid.
The nanofluid performance with respect to various feed and depth of cut was analysed. The surface temperature increases with increase of DoC or feed (refer Figure 3). But in all the cases, the temperature was maintained by nanofluid considerably very lesser than conventional cutting fluid.
The upgrading performance of surface finish can be measured in terms of degree of downsizing the surface roughness. In general observation, the surface roughness reduction is significant with respect to machining environment. The analysis is performance of machining environment at constant feed rate and constant depth of cut. Figures 4 furnishes the graphical representation of machining environment behaviour with constant feed rate of 100 mm/sec and 125 mm/sec (first row) and 150 mm/sec and 175 mm/sec (second row). The percentage of roughness reductions is consolidated in Table 10 for constant feed rate cases. The average reduction of surface roughness was considered for the calculation in percentage. It was the ratio of average of surface roughness reduced by wet machining to the average of surface roughness in the conventional method (dry machining) by using equation (1). The comparison n of nanofluid performance by using the ratio of average of surface roughness reduced by nanofluid to average of surface roughness observed with use of conventional grinding method (conventional coolant) by using equation (2).
The roughness reduction performances were analysed with respect to various feeds and machining environments at constant DoC (depth of cut). Figure 5 is graphical illustration of the same, i.e., in first row graphs are performance of grinding environments with respect to various feed at 10 μm and 20 μm DoC; similarly, the second row is for 30 μm and 40 μm DoCs. Roughness reduction in percentage is presented in Table 11.
Figure 6 shows the nanofluid performance with respect to feed and depth of cut. The increase of MRR (both depth of cut and feed rate) increases the surface roughness. But the maximum roughness 0.48 μm is acceptable, that is, better surface finish than conventional coolant performance. Hence, it is obvious that the nanofluid coolant out performs better than conventional coolant significantly in improving surface finish as well as temperature
7. Thermal Analysis
The purpose of the finite element method heat transfer modeling and analysis is used for analysing energy partition in work piece. This model traces the heat distribution in the work piece. The finite element model was created by COMSOL Multiphysics 5.0 package to analyze heat distribution on the work. The heat was measured at the center of the work piece through thermo couple. The measured values are used in the FEM to observe the behavior in the work piece. The surrounding temperature is considered as 30°C or 303 K, and the peripheral velocity is 32 m/s with 0.5 mm from surface. The forced convection is at the top surface of the natural convection on side and the conductive heat transfer at the bottom of the work piece. The meshed geometry has 5032 domain elements and 240 boundary elements. The output of the FEA is presented in Figure 7.
8. Conclusion
The experimental investigation of alumina nanofluid (as cutting fluid) for high-speed grinding of EN31 steel in reduction of surface roughness and surface temperature was discussed, and the following are the findings:(i)The two extreme parameters settings are as follows: all inputs are low and high. At low depth of cut of 10 μm and low feed rate of 100 mm/sec, the nanofluid-based grinding reduced surface temperature by 48.37% than conventional coolant and lubricant.(ii)At high depth of cut of 40 μm and high feed rate of 170 mm/sec, the temperature reduction performance with the use of alumina nanofluid was observed as 40.09% than conventional cutting fluid.(iii)At constant feed rate averagely 45.63.69%, 44.85%, 43.56%, and 42.24%, temperature reduced at feed rates 100, 125, 150, and 175 mm/sec, respectively, than use of conventional coolant for grinding EN31 steel at various depth cuts of 10, 20, 30, and 40 μm in each feed rate.(iv)The surface finish performance is also appreciable at low and high MRR settings. The surface roughness reduction at low and high parameters setting are 4.17% and 34.16%, respectively.(v)The average surface roughness reduction by alumina nanofluid than conventional cutting fluid 15.69%, 17.07%, 16.75%, and 20.93% for the feed rates 100, 125, 150, and 175 mm/sec, respectively, for various depth cuts of 10, 20, 30, and 40 μm.(vi)The thermal analysis reports were presented, and the fluid was kept the surface temperature in safe limit.
Data Availability
The data used to support the findings of this study are included in the article. Further data or information required can be available from the corresponding author upon request.
Disclosure
This work was performed as a part of the Employment Hawassa University, Ethiopia.
Conflicts of Interest
The authors declare that they have no conflicts of interest.
Acknowledgments
The authors appreciate the technical assistance to complete this experimental work from the Department of Mechanical Engineering, Faculty of Manufacturing, Institute of Technology, Hawassa University, Ethiopia.