Multi-Objective Optimization of the Cylindrical Grinding Process of SCM440 Steel Using Preference Selection Index Method
 
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1
Faculty of Mechanical Engineering, Ha Noi University of Industry, Viet Nam
 
2
HaUI Institute of Technology - HIT, Hanoi University of Industry, Hanoi city, Viet Nam
 
 
Submission date: 2021-08-05
 
 
Final revision date: 2021-08-25
 
 
Acceptance date: 2021-08-25
 
 
Online publication date: 2021-08-28
 
 
Publication date: 2021-09-30
 
 
Corresponding author
Dung Hoang Tien   

Faculty of Mechanical Engineering, Ha Noi University of Industry, No 298 Cau Dien Street, Bac Tu Liem District, Ha N, 084, Ha Noi, Viet Nam
 
 
Journal of Machine Engineering 2021;21(3):110-123
 
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ABSTRACT
This paper presents a study to ensure the minimum value of Ra and Rz, and the maximum value of MRR when external cylindrical grinding by the PSI. The experiments performed according to the orthogonal Taguchi L9 matrix with the input parameters were workpiece speed, feed rate, and depth of cut in the conventional grinding machine. Analysis of experimental results by Pareto chart showed that the feed rate and the depth of cut most influence Ra, Rz, respectively. Feed rate and depth of cut all have a great influence on MRR. Meanwhile, the workpiece speed has a negligible effect on all three output parameters. The research results showed that to obtain the minimum values of Ra and Rz, and maximum of MRR, the workpiece speed, feed rate, and depth of cut were 400 rev/min 37.7 mm/min, 0.09 mm/rev, and 0.02 mm, respectively.
 
REFERENCES (39)
1.
NGUYEN N.-T., TRUNG D.D., 2021, Investigation of the Surface Roughness in Infeed Centerless Grinding of SCM435 Steel, International Journal of Automation Technology, 15/1, 123–130.
 
2.
THIAGARAJAN C., RANGANATHAN S., SHANKA P., 2015, Cylindrical grinding process parameters optimization of Al / SiC metal matrix composites, International Journal of Scientific & Engineering Research, 6/2, 738–743.
 
3.
BHAVSAR T., NOKALJE A.M., 2020, Optimization of Cylindrical Grinding Process Parameters for EN353 Steel using Taguchi Technique, International Journal for Research in Applied Science & Engineering Technology, 8/11, 225–231.
 
4.
SINGLA S., DEV D.K., 2018, Optimization of Cylindrical Grinding Process Parameters for Heat Treated AISI 4150 Steel, International Journal on Theoretical and Applied Research in Mechanical Engineering, 7/2–3, 5–10.
 
5.
MOIHITE D.D., TIWARI N., SONTAKKE S., MISHRA U., 2017, Modelling and Optimization of Dressing Parameters of CNC Cylindrical Grinding Wheel for Minimum Surface Roughness, International Journal of Engineering Research and General Science, 5/4, 102–111.
 
6.
KUMAR N., TRIPATHI H., GANDOTRA S., 2015, Optimization of Cylindrical Grinding Process Parameters on C40E Steel Using Taguchi Technique, International Journal of Engineering Research and Applications, 5/1, 100–104.
 
7.
PANTHAGI R.K., Naduvinamani V., 2017, Optimization of Surface Roughness in Cylindrical Grinding Process, International Journal of Applied Engineering Research, 12/18, 7350–7354.
 
8.
SANGALE S.S., DONGARE A.D., 2019, Optimization of the parameter in cylindrical grinding of mild steel rod (EN19) by Taguchi method, International Journal Of Creative and Innovative Research In All Studies, 4/4, 66–73.
 
9.
GURUCHANDRA N., REDDY B.A.K., REDDY M.C.S., 2017, Optimization of Cylindrical Grinding Process Parameters on Material Removal Rate of EN21AM steel, International Journal of Engineering Research & Technology, 6/6, 623–631.
 
10.
GEORGE L.P., JOB K.V., CHANDRAN I.M., 2013, Study on Surface Roughness and its Prediction in Cylindrical Grinding Process based on Taguchi method of Optimization, International Journal of Scientific and Research Publications, 3/5, 1–5.
 
11.
NGUYEN N.–T., TRUNG D.D., 2020, A study on the surface grinding process of the SUJ2 steel using CBN slotted grinding wheel, AIMS Materials Science, 7/6, 871–886.
 
12.
KUMAR S., BHATIA O.S., 2015, Review of Analysis & Optimization of Cylindrical Grinding Process Parameters on Material Removal Rate of En15AM Steel, IOSR Journal of Mechanical and Civil Engineering, 12/4, 35–43.
 
13.
MEKALA K., CHANDRADAS J., CHANDRASEKARAN K., KANNAN T.T.M., RAMESH E., BABU R.N., 2014, Optimization of cylindrical grinding parameters of austenitic stainless steel rods (AISI 316) by Taguchi method, International Journal of Mechanical Engineering and Robotics Research, 3/2, 208–215.
 
14.
SINGH T., GOYAL K., KUMAR P., 2015, Effect of process parameters for optimum material removal rate cylindrical grinding of AISI 1045 steel, Journal of Mechanical Engineering, 44/2, 100–104.
 
15.
SRIDHAR M.M.J., MANICKAM M., KALAIYARASAN V., 2014, Optimization of Cylindrical Grinding Process Parameters of OHNS Steel (AISI 0-1) Rounds Using Design of Experiments Concept, International Journal of Engineering Trends and Technology, 17/3, 109–114.
 
16.
UPADHYAY G., RAMPRASAD, HASSAN K., 2015, Optimization of Metal Removal Rateon Cylindrical Grinding For Is 319 Brass Using Taguchi Method, International Journal of Engineering Research and Applications, 5/6, 63–68.
 
17.
HUNG L.X., HONG T.T., KY L.H., TUNG L.A., NGA N.T.T., PI V.N., 2018, Optimum dressing parameters for maximum material removal rate when internal cylindrical grinding using Taguchi method, International Journal of Mechanical Engineering and Technology, 9/12, 123–129.
 
18.
AHMED K.N., AHER A.S., 2020, A Review on Optimization of Process Parameter in Cylindrical Grinding of Austenitic Stainless Steel Rod (AISI 316 L) by Taguchi Method, Mukt Shabd Journal, 9/6, 2346–2352.
 
19.
PATIL K.R., KARANDE R.J., MOHITE D.D., JADHAV V.S., 2017, Modeling and Optimization of cylindrical grinding parameters for MRR and surface roughness, International Journal of Engineering Sciences & Research Technology, 6/4, 498–503.
 
20.
THAKOR S.P., PATEL D.M., 2014, An Experimental Investigation on Cylindrical Grinding Process Parameters for En 8 Using Regression Analysis, International Journal of Engineering Development and Research, 2/2, 2486–2491.
 
21.
SINGH K., KUMAR P., GOYAL K., 2014, To Study the Effect of Input Parameters on Surface Roughness of Cylindrical Grinding of Heat Treated AISI 4140 Steel, American Journal of Mechanical Engineering, 2/3, 58–64.
 
22.
KOKLU U., 2013, Optimization of machining parameters in interrupted cylindrical grinding using the Grey-based Taguchi method, International Journal of Computer Integrated Manufacturing, 26/8, 696–702.
 
23.
STIPKOVIK M.A., BORDINASSI E.C., FARIAS A.D., DELIJAICOV S., 2017, Surface Integrity Analysis in Machining of Hardened AISI 4140 Steel, Materials Research, 20/2, 387–394.
 
24.
KWAK J.-S., SIM S.-B., JEONG Y.-D., 2006, An analysis of grinding power and surface roughness in external cylindrical grinding of hardened SCM440 steel using the response surface method, International Journal of Machine Tools & Manufacture, 46, 304–312.
 
25.
OZDEMIR M., KAYA M.T., AKYILDIZ H.K., 2020, Analysis of Surface Roughness and Cutting Forces in Hard Turning of 42CrMo4 Steel using Taguchi and RSM Method, Mechanika, 26/3, 231–241.
 
26.
RUDRAPATI R., BANDYOPADHYAY A., PAL P.K., 2013, Multi-Objective Optimization in Traverse Cut Cylindrical Grinding, Advanced Materials Manufacturing & Characterization, 3/1, 335–339.
 
27.
RUDRAPATI R., BANDYOPADHWAY A., PAL P.K., 2018, Parametric Optimization of Cylindrical Grinding Process through Hybrid Taguchi Method and RSM Approach using Genetic Algorithm, Iranian Journal of Mechanical Engineering, 19/1, 34–62.
 
28.
ATTRI R., GROVER S., 2015, Application of preference selection index method for decision making over the design stage of production system life cycle, Journal of King Saud University – Engineering Sciences, 27/2, 207–216.
 
29.
VAHDANI B., MOUSAVI S.M., EBRAHIMNEJAD S., 2014, Soft computing-based preference selection index method for human resource management, Journal of Intelligent & Fuzzy Systems, 26, 393–403.
 
30.
SAHIR S.H., AFRIANI J., GINTING G., FACHRI B., SIREGAR D., et al., 2018, The Preference Selection Index Method in Determining the Location of Used Laptop Marketing, International Journal of Engineering & Technology, 7/3.4 260–263.
 
31.
PRASAD R.V., RAO C.M., RAJU B.N., 2018, Application of preference selection index (PSI) method for the Optimization of the turning process parameters, International Journal of Modern Trends in Engineering and Research, 5/5, 140–144.
 
32.
MANIYA K., BHATT M.G., 2010, A selection of material using a novel type decision-making method: Preference selection index method, Materials and Design, 31, 1785–1789.
 
33.
MALKIN S., GUO C., 2008, Grinding technology: Theory and Applications of Machining with Abrasives, Industrial press, New York.
 
34.
LONG B.T., LUC T.T., TUY T.S., 2001, Material processing principles, Science and technics publishing House, Hanoi.
 
35.
SON N.H., TRUNG D.D., 2020, An experimental study on surface roughness – Applied to determine the optimal value of cutting parameters when milling 40Cr steel, International Journal of Mechanical and Production Engineering Research and Development, 10/2, 101–110.
 
36.
PATHAK B.N., SAHOO K.L., MISHRA M., 2013, Effect of Machining Parameters on Cutting Forces and Surface Roughness in Al-(1-2) Fe-1V-1Si Alloys, Materials and Manufacturing Processes, 28, 463–469.
 
37.
MARINESCU I.D., HITCHINER M.P., UHLMAN E., ROWE W.B., INASAKI I., 2006, Handbook of machining with grinding wheels, CRC Press.
 
38.
TRUNG D.D., THIEN N.V., NGUYEN N.-T., 2021, Application of TOPSIS Method in Multi-Objective Optimization of the Grinding Process Using Segmented Grinding Wheel, Tribology in Industry, 43/1, 12–22.
 
39.
GUHA S., PROTIM D.P., CHAKRABPRTY S., 2019, Improvement in the performance with less stiff air layer formation around the rubber tube-pasted grinding wheel, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 233/15, 5175–5189.
 
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