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Patole, P. B.
- Experimental Investigation and Analysis of Relationship between Surface Roughness and Cutting Force during MQL Turning of AISI 4340 with Nano Fluid
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Authors
Affiliations
1 Department of Mechanical Engineering, Bharati Vidyapeeth’s College of Engineering, Kolhapur, Maharashtra, IN
2 Department of Mechanical Engineering, Sanjay Ghodawat Group of Institution, Kolhapur, Maharashtra, IN
1 Department of Mechanical Engineering, Bharati Vidyapeeth’s College of Engineering, Kolhapur, Maharashtra, IN
2 Department of Mechanical Engineering, Sanjay Ghodawat Group of Institution, Kolhapur, Maharashtra, IN
Source
Manufacturing Technology Today, Vol 16, No 2 (2017), Pagination: 3-10Abstract
The objective of this research work is focused on to establish the relationship between surface and cutting force under Minimum Quantity Lubrication using nano fluid in turning of AISI 4340. A study of effect of cutting parameters in turning of AISI 4340 under MQL condition with nano fluid on the cutting force generated and machined surface roughness is carried out. In the experiment conducted, five values of feed rate, three values of depth of cut, two values of cutting speed and tool nose radius respectively, are used. The test pieces were turned on a CNC lathe machine under MQL mode using nano fluid with different levels of cutting parameters by using full factorial design of experiment orthogonal array. From result analysis, it was found that, feed rate played a major role in producing lower surface roughness followed by depth of cut whereas cutting speed has least significance in producing lower surface roughness under MQL using nano coolant. It was observed that at constant depth of cut and cutting speed for tool nose radius 0.8 mm and 0.4 mm as feed increases, surface roughness and cutting force values increases. From Least square technique the curve fitting equation (power equation) between surface roughness and cutting force is obtained. Also it is found that, agreements between surface roughness and calculated cutting force is excellent (99%) and confidence interval for co-relation coefficient r1, r2, r3, r4 is significant. So from the analysis of result the relationship between surface roughness and cutting force is established.Keywords
MQL, Nano Fluid, Confidence Interval, Cutting Force, Surface Roughness.
References
- Narayana Rao, S; Dr. Satyanarayana, B; Dr. Venkatasubbaiah, K: Experimental Estimation of Tool Wear and Cutting Temperatures in MQL using Cutting Fluids with CNT Inclusion, 'International Journal of Industrial Engineering Science and Technology', ISSN: 0975-5462, vol. 3, no. 4, Apr 2011.
- Ashok Kumar Sahoo; Bidyadhar Sahoo: Experimental Investigation on Machinability Aspects in Finish Hard Turning of AISI 4340 Steel using Uncoated and Multilayer Coated Carbide Inserts, 'Measurement', vol. 45, no. 8, 2012, 2153-2165.
- Hasib, Md. Abdul; Al-farukh, Abdudish; Ahmed, Naseem: Mist application of cutting fluid, 'International Journal of Mechanical and Mechatronics Engineering IJMME-IJENS, vol. 10, no. 4, 10-14.
- Rakurty, CS; Varela, PI; Balaji, AK: Effects of Targeted Minimum Quantity Fluid Application on Surface Integrity, 14thCIRP Conference On Modeling of Machining Operations, 'Procedia CIRP', vol. 8, 2013, 462-468.
- Stephenson, DA; Skerlos, SJ; King, AS, Supekar, SD: Rough Turning Inconel 750 With Supercritical Co2- Based Minimum Quantity lubrication, 'Journal of Material Processing Technology', 2014, 673-680.
- Tasdelen, B; Thordenberg, H; Olofsson, D: An Experimental Investigation on Contact Length During MQL Machining, 'Journal of Material Processing Technology', vol. 203, no. 1-3, 2008, 221-231.
- Prabhu, S; Vinayagam, BK: Fractal Dimensional Surface Analysis of AISI D2 Tool Steel Material with Nano fluids in Grinding Process Using Atomic Force Microscopy, 'Journal of the Brazilian Society of Mechanical Sciences and Engineering', vol. 33, no. 4, 2011.
- Shen Bin: Minimum Quantity Lubrication Grinding Using Nano fluids, A Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy (Mechanical Engineering) in the University of Michigan, 2008.
- Lohar, DV; Nanavte, CR:Performance Evaluation of Minimum Quantity Lubrication (MQL) Using CBN Tool during Hard Turning of AISI 4340 and its Comparison with Dry and Wet Turning, 'International Journal of Industrial Engineering and Management Science', vol. 3, no. 3, 2013.
- Grewal, BS: Numerical Methods, Khanna Publisher, 2005, 106-109.
- Johnsen, Richard A; Gupta, CB: Probability and Statistics for Engineers, Pearson Education, 2005, 326-365
- Experimental Investigation and Analysis of Effect of Process Parameters on Surface Roughness of AISI 4340 during MQL Turning with Nano Fluid
Abstract Views :173 |
PDF Views:2
Authors
Affiliations
1 Department of Mechanical Engineering, Bharati Vidyapeeth’s College of Engineering, Kolhapur, Maharashtra, IN
2 Department of Mechanical Engineering, Sanjay Ghodawat Group of Institution, Kolhapur, Maharashtra, IN
1 Department of Mechanical Engineering, Bharati Vidyapeeth’s College of Engineering, Kolhapur, Maharashtra, IN
2 Department of Mechanical Engineering, Sanjay Ghodawat Group of Institution, Kolhapur, Maharashtra, IN
Source
Manufacturing Technology Today, Vol 16, No 7 (2017), Pagination: 11-20Abstract
The selection of cooling system and effective optimization of machining cutting parameters affects cost and production time of quality of machined work piece material. This research work represents an investigation on response parameters such as surface roughness and metal removal rate during MQL turning of AISI 4340 with nano fluid along with comparative analysis of different cooling systems. Three values of feed rate and depth of cut respectively were chosen to study the effect on surface roughness. As per Taguchi design L9 orthogonal array design matrix has been selected for conducting of experiments. The optimal conditions are obtained from Grey Relational Analysis (GRA) as Feed (0.04 mm/rev.) and Depth of cut (1.5 mm). The Signal to Noise ratio plot for GRA shows similar optimum condition therefore the results achieved from ANOVA are closely matching to the results of GRA. Improvement in grey relational grade is near about 1.24%. From the comparative result analysis, it was observed that Minimum Quantity Lubrication (MQL1) with nano fluid (MWCNT) showed lowest surface roughness compared to MQL2, dry and flood condition. Also it is found that the percentage error is below ±5%. For MQL1 at optimum condition (Feed rate 0.04 mm/rev. and Depth of cut 1.5 mm) the obtained surface roughness (Ra = 1.01μm). The findings of this study show that MQL with nano fluid can substitute the flood lubrication for better surface finish and performance characteristics can be improved effectively through this approach.Keywords
MQL, Nano Fluid, GRA, Surface Roughness, Metal Removal Rate.References
- Narana Rao S., Satyanarayana B. S., (2011), Experimental Estimation of Tool Wear and Cutting Temperatures in MQL using Cutting Fluids with CNT Inclusion, International Journal of Industrial Engineering Science and Technology, ISSN:0975-5462.
- Sahoo Ashok Kumar, Sahoo Bidyadhar, (2012) Experimental Investigation on Machinability Aspects in Finish Hard Turning of AISI 4340 Steel using Uncoated and Multilayer Coated Carbide Inserts, Measurement 45, pp2153-2165.
- Young Kug Hwang and Choon Man Lee, (2010), Surface roughness and cutting force prediction in MQL and wet turning process of AISI 1045 using design of experiments, Journal of Mechanical Science and Technology 24(8), 1669-1677.
- Suhil Adheil H., Ismail N., (2010), Optimization of Cutting Parameters of Turning Operations by using Geometric Programming, American J. of Engineering and Applied sciences, 3(1) pp102-108.
- Dhar N. R., Islam S. and Kamruzzaman M., (2007), Effect of Minimum Quantity Lubrication(MQL) on Tool Wear, Surface Roughness and Dimensional Deviation in Turning AISI-4340 Steel, G. U. Journal of Science 20(2), pp23-32.
- Lohar D. V., Nanavte C. R., (2013), Performance Evaluation of Minimum Quantity Lubrication (MQL) Using CBN Tool during Hard Turning of AISI 4340 and its Comparison with Dry and Wet Turning, International Journal of Industrial Engineering and Management Science, Vol. 3, No. 3.
- Tasdelen B., Thordenberg H., Olofsson D., (2008), An Experimental Investigation on Contact Length During MQL Machining, Journal of Material Processing Technology, pp221-231.
- Shen Bin, (2008), Minimum Quantity Lubrication Grinding Using Nano fluids, A Dissertation Submitted in Partial Fulfilment of the Requirements for the Degree of Doctor of Philosophy (Mechanical Engineering) in the University of Michigan.
- Prabhu S., Vinayagam B. K., (2011), Fractal Dimensional Surface Analysis of AISI D2 Tool Steel Material with Nano fluids in Grinding Process Using Atomic Force Microscopy, 466 / Vol. XXXIII, No. 4.
- Berger P. D. and R. E. Maurer, (2001), Experimental Design with Applications in Management, Engineering and the Sciences, 1st edition, Duxbury Press, USA, ISBN:10: 0534358225, pp:496
- Patole P. B. and Kulkarni V. V., (2017), Experimental Investigation and Analysis of Relationship between Surface Roughness and Cutting Force during MQL Turning of AISI 4340 with Nano Fluid, Manufacturing Technology Today (CMTI), Vol. 16 No.1, pp 1-9.
- Patole P. B. and Kulkarni V.V., (2017), Experimental investigation and optimization of cutting parameters with multi response characteristics in MQL turning of AISI 4340 using nano fluid, Cogent Engineering (Taylor and Francis group), 4: 1303956.
- Patole P. B. and Kulkarni V.V., (2016), Optimization of Process Parameters based on Surface Roughness and Cutting Force in MQL Turning of AISI 4340 using Nano Fluid, Materials Today Procedings: PMME 2016.
- Attanasio Gelfi A., Giardini C. and Remino C., (2006) Minimal quantity lubrication in turning: effect on tool wear, International Journal on the Science and Technology of Friction, Lubrication and Wear, 260, pp333-338.
- Kumar and Sing, (2016), Multi response optimization in wire electrical discharge machining of Inconel x- 750 using Taguchi technique and grey relational analysis, International Journal of Cogent Engineering, 3: 1266123
- Chang C.L., Tsai C. H., Chen L. Applying grey relational analysis to the decathlon evaluation model, International journal of Computer Internet Manage 2003;11(3):54-62.
- Ulas Caydas, Ahmet Hascalik., (2008), Use of the Grey Relational Analysis to determine optimum laser cutting parameters with multi-performance characteristics, Elsevier, Optics and Laser Technology 40 pp 987-994.
- Sing Dilbag and Venkteshewara Rao P. (2007), A surface roughness prediction model for hard turning process, International Journal of Advanced Manufacturing Technology, 32: 1115-1124.
- Fung C. P., Manufacturing process optimization for wear property of fiber–reinforced polbutylene terephthalate composites with grey relation analysis. Wear 254: 298-306.
- Pujari Shrinivasa Rao, Koona Ramji and Beela Satyanarayna, (2010), Prediction of Material removal rate for Aluminium BIS-24345 alloyin wire cut EDM, International Journal of Engineering Science and Technology, Vol. 2(12), 7729-7739.
- Nalbant M. H., Gokkaya and G. Sur, (2007), Application of Taguchi method in the optimization of cutting parameters for surface roughness in turning, Materials and Design, 28, pp. 1379-1385.
- Patel P., Modi. B. S., Shet S and Patel. T. (2015), Experimental Investigation, Modelling and Comparison of kerf width in laser cutting of GFRP. Bonfring International Journal of Industrial Engineering and Management and Science, 5 (2), pp. 55-62.
- Douglas C. Montgomery, (2001), Design and Analysis of Experiments, John Wiley and Sons, pp1-17.
- P. J. (1996), Taguchi Techniques for Quality Engineering, New York, McGraw Hill.
- FEA Modeling And Prediction Of Surface Roughness Of Aluminum Alloy (LM4) During Turning Process
Abstract Views :239 |
PDF Views:0
Authors
Affiliations
1 Bharati Vidyapeeth’s College of Engineering, Kolhapur, Maharashtra, IN
2 SGI Atigre, Kolhapur, Maharashtra, IN
1 Bharati Vidyapeeth’s College of Engineering, Kolhapur, Maharashtra, IN
2 SGI Atigre, Kolhapur, Maharashtra, IN
Source
Manufacturing Technology Today, Vol 19, No 11 (2020), Pagination: 20-27Abstract
Different cutting parameters have different influences on the surface finish. A study of effect of some of these parameters on the surface roughness of Aluminum alloy grade LM4 (AlSi5Cu3) is carried out in this work. In the experiment conducted, six values of cutting speed, three values of depth of cut, six values of feed and two values of tool nose radius are used. The experimentation was carried out using a three factor experiment principle from design of experiment. The chemical composition of the work material was tested using arc spectrometer and verified to be of grade LM 4. The values of parameters like cutting speed, feed rate and depth of cut were selected from the recommended ranges from the tool manufacturer catalogue. The test pieces were turned on a center lathe machine under different levels of these parameters. The surface roughness of the machined surface was measured using surface measurement tester. From the analysis of results the relationship between surface roughness and equivalent stress is established.Keywords
Turning, surface Roughness, Equivalent Stress, Cutting Parameters.- Analysis of Effect of Cutting Parameters on Surface Roughness and Cutting Force During Turning of Aluminum Alloy (AlSi5Cu3)
Abstract Views :178 |
PDF Views:0
Authors
Affiliations
1 Bharati Vidyapeeth’s College of Engineering, Kolhapur, Maharashtra, IN
1 Bharati Vidyapeeth’s College of Engineering, Kolhapur, Maharashtra, IN
Source
Manufacturing Technology Today, Vol 20, No 1-2 (2021), Pagination: 3-8Abstract
The aim of this research work is focused on analysis of process parameters during turning of aluminium alloy (AlSi5Cu3). A study of effect of cutting parameters in turning of Aluminum Alloy (AlSi5Cu3) on the cutting force generated and machined surface roughness is carried out. In the experiment conducted, six values of feed rate, three values of depth of cut, and two values of cutting speed respectively, are used. The test pieces were turned on a centre lathe machine with different levels of cutting parameters by using full factorial design of experiment orthogonal array. The surface roughness of the machined surface was measured using surface measurement tester. Taguchi methodology was used to optimize process parameters. The results were analyzed by using Analysis of variance. From result analysis, it was found that, feed rate played a major role in producing lower surface roughness followed by cutting speed whereas depth of cut has least significance in producing lower surface roughness. To achieve better machining performance, the optimum condition parameters for surface roughness and cutting force, are as feed rate (FR = 0.045 m/min.), the cutting speed (CS = 90 m/min.), depth of cut (DOC = 0.5 mm). From analysis it is also seen that the cutting force equation and surface roughness equations are appropriate for accurate prediction. Thus, with proper selection of cutting parameters, it is possible to achieve good surface roughness, reduce tool wear while maintaining the cutting forces and temperatures at reasonable levels.Keywords
Turning, Surface Roughness, Cutting Force, Cutting Parameters.References
- Amini, S., Khakbaz, H., & Barani, A. (2015). Improvement of Near-Dry Machining and It’s Effect on Tool Wear in Turning of AISI 4142. Journal of Materials and Manufacturing Processes, 30, 241–247.
- Aouici, H., Yallese, M. A., Belbah, A., Mfameur & Elbah, M. (2013). Experimental Investigation of Cutting Parameters Influence on Surface Roughness and Cutting Forces in Hard Turning of X38CrMoV5-1 with CBN tool. Journal of Sadhana Indian Academy of Sciences, 38 (Pt 3), 429-445.
- Chen Lu (2008). Study on Prediction of Surface Quality in Machining Process. Journal of Materials Processing Technology, 205, 439-450.
- CMTI (1982). Machine Tool Design Handbook. Tata Mc-Graw Hill, New Delhi, 637-650.
- Montgomery, D. C. (2001). Design and Analysis of Experiments. John Wiley and Sons, 1-17.
- Patole, P. B., & Kulkarni, V. V. (2017a). Experimental Investigation and Analysis of Effect of Process Parameters on Surface Roughness of AISI 4340 during MQL Turning with Nano Fluid. Manufacturing Technology Today, 16(7), 11-20.
- Patole, P. B., & Kulkarni, V. V. (2017b). Experimental Investigation and Optimization of Cutting Parameters with Multi Response Characteristics in MQL Turning of AISI 4340 using Nano Fluid. Journal of Cogent Engineering, 4(1), 1-14.
- Patole, P. B., & Kulkarni, V. V. (2018). Prediction of Surface Roughness and Cutting Force under MQL Turning of AISI 4340 with Nano Fluid by using Response Surface Methodology. Journal of Manufacturing Review, 5, 2018.
- Singh, C. S., Amrit Pal & Singh, T. (2016). Performance Evaluation of Aluminium 6063 Drilling under the Influence of Nano fluid Minimum Quantity Lubrication. Journal of Cleaner Production, 137, 537-545.
- Sripathi, P. S. (2009). Investigation into the Effects of Tool Geometry and Metal Working Fluids on Tool Forces and Tool Surfaces during Orthogonal Tube Turning of Aluminum 6061 Alloy.
- Suhail, A. H., Ismail, N., Wong, S. V., and Jalil, A. N. A. (2010). Team Mechanics Materials and High Speed Machining, Optimization of Cutting Parameters of Turning Operations by using Geometric Programming. American Journal of Engineering and Applied sciences, 3(1), 102-108.
- Vinay, V., Ramesh, M. R., & Chakradhar, D. (2018). Experimental Investigation and Optimization of Machining Parameters for Sustainable Machining. Journal of Materials and Manufacturing Processes, 33, 1782-1792.