Skip to main content
Top
Published in: Journal of Materials Engineering and Performance 9/2022

14-03-2022 | Technical Article

Sustainable Hard Machining of AISI 304 Stainless Steel Through TiAlN, AlTiN, and TiAlSiN Coating and Multi-Criteria Decision Making Using Grey Fuzzy Coupled Taguchi Method

Authors: C. Moganapriya, R. Rajasekar, R. Santhosh, S. Saran, S. Santhosh, V. K. Gobinath, P. Sathish Kumar

Published in: Journal of Materials Engineering and Performance | Issue 9/2022

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

High strength, high ductility, low thermal conductivity and high work hardening effects of austenitic stainless steels are the foremost factors that make their machinability difficult. Machining, especially dry machining of such steels, has been one of the most significant challenges for carbide cutting tools. In this research study, TiAlN, AlTiN and TiAlSiN coatings were successfully employed through HiPIMS coating system on cutting tools for dry machining of AISI 304 stainless steel. As-deposited coatings were confirmed through FESEM and XRD analysis. The input process parameters including coating material have been considered for optimizing the multiple objectives such as surface roughness Ra, Rz, tool wear rate and material removal rate. Multi-criteria decision making involving grey fuzzy coupled Taguchi method was adopted to solve the optimization for multiple response characteristics. Analysis of variance was conducted to analyze the contribution percentage of each process parameter. From the results of MCDM-based GFCT, the optimized setting for best output responses was determined as coating: TiAlSiN, cutting speed: 180 m/min, feed rate: 0.1mm/rev and depth of cut: 1.5 mm. Feed rate had significantly contributed about 42.74% on the output measures, followed by coating, depth of cut and cutting speed. The responses were predicted with an accuracy of 96.5% through GFCT technique. Finally, a confirmatory experiment was carried out to support the accuracy of optimal process parameters.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference S. Shankar, T. Mohanraj, and S.K. Thangarasu, Multi-Response Milling Process Optimization Using the Taguchi Method Coupled to Grey Relational Analysis, Mater. Test., 2016, 58(5), p 462–470.CrossRef S. Shankar, T. Mohanraj, and S.K. Thangarasu, Multi-Response Milling Process Optimization Using the Taguchi Method Coupled to Grey Relational Analysis, Mater. Test., 2016, 58(5), p 462–470.CrossRef
2.
go back to reference C. Moganapriya et al., Achieving Machining Effectiveness for AISI 1015 Structural Steel Through Coated Inserts and Grey-Fuzzy Coupled Taguchi Optimization Approach, Struct. Multidiscip. Optim., 2021, 63(3), p 1169–1186.CrossRef C. Moganapriya et al., Achieving Machining Effectiveness for AISI 1015 Structural Steel Through Coated Inserts and Grey-Fuzzy Coupled Taguchi Optimization Approach, Struct. Multidiscip. Optim., 2021, 63(3), p 1169–1186.CrossRef
3.
go back to reference D. Boing, A.J. de Oliveira, and R.B. Schroeter, Limiting Conditions for Application of PVD (TiAlN) and CVD (TiCN/Al2O3/TiN) Coated Cemented Carbide Grades in the Turning of Hardened Steels, Wear, 2018, 416–417, p 54–61.CrossRef D. Boing, A.J. de Oliveira, and R.B. Schroeter, Limiting Conditions for Application of PVD (TiAlN) and CVD (TiCN/Al2O3/TiN) Coated Cemented Carbide Grades in the Turning of Hardened Steels, Wear, 2018, 416–417, p 54–61.CrossRef
4.
go back to reference P.C. Jindal et al., Performance of PVD TiN, TiCN, and TiAlN Coated Cemented Carbide Tools in Turning, Int. J. Refract Metal Hard Mater., 1999, 17(1–3), p 163–170.CrossRef P.C. Jindal et al., Performance of PVD TiN, TiCN, and TiAlN Coated Cemented Carbide Tools in Turning, Int. J. Refract Metal Hard Mater., 1999, 17(1–3), p 163–170.CrossRef
5.
go back to reference C. Moganapriya et al., Tribomechanical Behavior of TiCN/TiAlN/WC-C Multilayer Film on Cutting Tool Inserts for Machining, Mater. Test., 2017, 59(7–8), p 703–707.CrossRef C. Moganapriya et al., Tribomechanical Behavior of TiCN/TiAlN/WC-C Multilayer Film on Cutting Tool Inserts for Machining, Mater. Test., 2017, 59(7–8), p 703–707.CrossRef
6.
go back to reference Z. Wu et al., Electrochemical and Tribological Properties of CrAlN, TiAlN, and CrTiN Coatings in Water-Based Cutting Fluid, J. Mater. Eng. Perform., 2020, 29(4), p 2153–2163.CrossRef Z. Wu et al., Electrochemical and Tribological Properties of CrAlN, TiAlN, and CrTiN Coatings in Water-Based Cutting Fluid, J. Mater. Eng. Perform., 2020, 29(4), p 2153–2163.CrossRef
7.
go back to reference M. Kaladhar, K.V. Subbaiah, and C.S. Rao, Optimization of Surface Roughness and Tool Flank Wear in Turning of AISI 304 Austenitic Stainless Steel with CVD Coated Tool, J. Eng. Sci. Technol., 2013, 8(2), p 165–176. M. Kaladhar, K.V. Subbaiah, and C.S. Rao, Optimization of Surface Roughness and Tool Flank Wear in Turning of AISI 304 Austenitic Stainless Steel with CVD Coated Tool, J. Eng. Sci. Technol., 2013, 8(2), p 165–176.
8.
go back to reference C. Moganapriya, M. Vigneshwaran, G. Abbas, A. Ragavendran, V.H. Ragavendra, and R. Rajasekar, Technical Performance of Nano-layered CNC Cutting Tool Inserts—An Extensive Review, Mater. Today Proc., 2020, 45, p 663–669.CrossRef C. Moganapriya, M. Vigneshwaran, G. Abbas, A. Ragavendran, V.H. Ragavendra, and R. Rajasekar, Technical Performance of Nano-layered CNC Cutting Tool Inserts—An Extensive Review, Mater. Today Proc., 2020, 45, p 663–669.CrossRef
9.
go back to reference T. Sampath Kumar, S. Balasivanandha Prabu, and G. Manivasagam, Metallurgical Characteristics of TiAlN/AlCrN Coating Synthesized by the PVD Process on a Cutting Insert, J. Mater. Eng. Perform., 2014, 23(8), p 2877–2884.CrossRef T. Sampath Kumar, S. Balasivanandha Prabu, and G. Manivasagam, Metallurgical Characteristics of TiAlN/AlCrN Coating Synthesized by the PVD Process on a Cutting Insert, J. Mater. Eng. Perform., 2014, 23(8), p 2877–2884.CrossRef
10.
go back to reference G. Zheng et al., Effect of Cutting Parameters on Wear Behavior of Coated Tool and Surface Roughness in High-Speed Turning of 300M, Measurement, 2018, 125, p 99–108.CrossRef G. Zheng et al., Effect of Cutting Parameters on Wear Behavior of Coated Tool and Surface Roughness in High-Speed Turning of 300M, Measurement, 2018, 125, p 99–108.CrossRef
11.
go back to reference N. Abburi and U. Dixit, Multi-objective Optimization of Multipass Turning Processes, Int. J. Adv. Manuf. Technol., 2007, 32(9–10), p 902–910.CrossRef N. Abburi and U. Dixit, Multi-objective Optimization of Multipass Turning Processes, Int. J. Adv. Manuf. Technol., 2007, 32(9–10), p 902–910.CrossRef
12.
go back to reference I. Asiltürk and H. Akkuş, Determining the Effect of Cutting Parameters on Surface Roughness in Hard Turning Using the Taguchi Method, Measurement, 2011, 44(9), p 1697–1704. I. Asiltürk and H. Akkuş, Determining the Effect of Cutting Parameters on Surface Roughness in Hard Turning Using the Taguchi Method, Measurement, 2011, 44(9), p 1697–1704.
13.
go back to reference C. Nian, W. Yang, and Y. Tarng, Optimization of Turning Operations with Multiple Performance Characteristics, J. Mater. Process. Technol., 1999, 95(1–3), p 90–96.CrossRef C. Nian, W. Yang, and Y. Tarng, Optimization of Turning Operations with Multiple Performance Characteristics, J. Mater. Process. Technol., 1999, 95(1–3), p 90–96.CrossRef
14.
go back to reference B. Zou et al., Study on Microstructure and its Formation Mechanism, and Mechanical Properties of TiB2–TiC Laminated Ti(C5N5) Composite Ceramic Cutting Tool Material, Int. J. Refract Metal Hard Mater., 2014, 42, p 169–179.CrossRef B. Zou et al., Study on Microstructure and its Formation Mechanism, and Mechanical Properties of TiB2–TiC Laminated Ti(C5N5) Composite Ceramic Cutting Tool Material, Int. J. Refract Metal Hard Mater., 2014, 42, p 169–179.CrossRef
15.
go back to reference R.Q. Sardinas, M.R. Santana, and E.A. Brindis, Genetic Algorithm-Based Multi-Objective Optimization of Cutting Parameters in Turning Processes, Eng. Appl. Artif. Intell., 2006, 19(2), p 127–133.CrossRef R.Q. Sardinas, M.R. Santana, and E.A. Brindis, Genetic Algorithm-Based Multi-Objective Optimization of Cutting Parameters in Turning Processes, Eng. Appl. Artif. Intell., 2006, 19(2), p 127–133.CrossRef
16.
go back to reference H. Zhao, G.C. Barber, and Q. Zou, A Study of Flank Wear in Orthogonal Cutting with Internal Cooling, Wear, 2002, 253(9), p 957–962.CrossRef H. Zhao, G.C. Barber, and Q. Zou, A Study of Flank Wear in Orthogonal Cutting with Internal Cooling, Wear, 2002, 253(9), p 957–962.CrossRef
17.
go back to reference C. Moganapriya et al., Influence of Coating Material and Cutting Parameters on Surface Roughness and Material Removal Rate in Turning Process Using Taguchi Method, Mater. Today Proc., 2018, 5(2), p 8532–8538.CrossRef C. Moganapriya et al., Influence of Coating Material and Cutting Parameters on Surface Roughness and Material Removal Rate in Turning Process Using Taguchi Method, Mater. Today Proc., 2018, 5(2), p 8532–8538.CrossRef
18.
go back to reference V.-C. Dinh, T.-P. Nguyen, and V.-C. Tong, Multi-response Optimization of 67Ni18Cr5Si4B Coating by HVOF Spray Using Taguchi-OEC Technique, J. Adhes. Sci. Technol., 2019, 33(3), p 314–327.CrossRef V.-C. Dinh, T.-P. Nguyen, and V.-C. Tong, Multi-response Optimization of 67Ni18Cr5Si4B Coating by HVOF Spray Using Taguchi-OEC Technique, J. Adhes. Sci. Technol., 2019, 33(3), p 314–327.CrossRef
19.
go back to reference V. Sivaraman, S. Sankaran, and L. Vijayaraghavan, Effect of Cutting Parameters on Cutting Force and Surface Roughness During Machining Microalloyed Steel: Comparison Between Ferrite–Pearlite, Tempered Martensite and Ferrite–Bainite–Martensite Microstructures, Proc. Inst. Mech. Eng. Part B J. Eng. Manuf., 2018, 232(1), p 141–150.CrossRef V. Sivaraman, S. Sankaran, and L. Vijayaraghavan, Effect of Cutting Parameters on Cutting Force and Surface Roughness During Machining Microalloyed Steel: Comparison Between Ferrite–Pearlite, Tempered Martensite and Ferrite–Bainite–Martensite Microstructures, Proc. Inst. Mech. Eng. Part B J. Eng. Manuf., 2018, 232(1), p 141–150.CrossRef
20.
go back to reference Y. Touggui et al., Multi-objective Optimization of Turning Parameters for Targeting Surface Roughness and Maximizing Material Removal Rate in Dry Turning of AISI 316L with PVD-Coated Cermet Insert, SN Appl. Sci., 2020, 2(8), p 1360.CrossRef Y. Touggui et al., Multi-objective Optimization of Turning Parameters for Targeting Surface Roughness and Maximizing Material Removal Rate in Dry Turning of AISI 316L with PVD-Coated Cermet Insert, SN Appl. Sci., 2020, 2(8), p 1360.CrossRef
21.
go back to reference K. Palanikumar et al., Analysis on Drilling of Glass Fiber–Reinforced Polymer (GFRP) Composites Using Grey Relational Analysis, Mater. Manuf. Process., 2012, 27(3), p 297–305.CrossRef K. Palanikumar et al., Analysis on Drilling of Glass Fiber–Reinforced Polymer (GFRP) Composites Using Grey Relational Analysis, Mater. Manuf. Process., 2012, 27(3), p 297–305.CrossRef
22.
go back to reference I. Shivakoti et al., ANFIS Based Prediction and Parametric Analysis during Turning Operation of Stainless Steel 202, Mater. Manuf. Process., 2019, 34(1), p 112–121.CrossRef I. Shivakoti et al., ANFIS Based Prediction and Parametric Analysis during Turning Operation of Stainless Steel 202, Mater. Manuf. Process., 2019, 34(1), p 112–121.CrossRef
23.
go back to reference A. Tamilvanan et al., Parameter Optimization of Copper Nanoparticle Synthesis by Electrodeposition Process Using RSM and CS, Mater. Today Proc., 2021, 45, p 751–756.CrossRef A. Tamilvanan et al., Parameter Optimization of Copper Nanoparticle Synthesis by Electrodeposition Process Using RSM and CS, Mater. Today Proc., 2021, 45, p 751–756.CrossRef
24.
go back to reference H. Kus, G. Basar, and F. Kahraman, Modeling and Optimization for Fly Ash Reinforced Bronze-Based Composite Materials Using Multi Objective Taguchi Technique and Regression Analysis, Ind. Lubr. Tribol., 2018, 70, p 1187–1192.CrossRef H. Kus, G. Basar, and F. Kahraman, Modeling and Optimization for Fly Ash Reinforced Bronze-Based Composite Materials Using Multi Objective Taguchi Technique and Regression Analysis, Ind. Lubr. Tribol., 2018, 70, p 1187–1192.CrossRef
25.
go back to reference G. Başar, F. Kahraman, and G.T. Önder, Mathematical Modeling and Optimization of Milling Parameters in AA 5083 Aluminum Alloy, Eur. Mech. Sci., 2019, 3(4), p 159–163.CrossRef G. Başar, F. Kahraman, and G.T. Önder, Mathematical Modeling and Optimization of Milling Parameters in AA 5083 Aluminum Alloy, Eur. Mech. Sci., 2019, 3(4), p 159–163.CrossRef
26.
go back to reference G. Dinde and G. Dhende, Study of Machining Parameters for Wet Turning of F55 Stainless Steel Using Grey Relational Analysis for Improvement in Surface Roughness, Optimization Methods in Engineering. Springer, Berlin, 2021, p 567–578CrossRef G. Dinde and G. Dhende, Study of Machining Parameters for Wet Turning of F55 Stainless Steel Using Grey Relational Analysis for Improvement in Surface Roughness, Optimization Methods in Engineering. Springer, Berlin, 2021, p 567–578CrossRef
27.
go back to reference I. Korkut et al., Determination of Optimum Cutting Parameters during Machining of AISI 304 Austenitic Stainless Steel, Mater. Des., 2004, 25(4), p 303–305.CrossRef I. Korkut et al., Determination of Optimum Cutting Parameters during Machining of AISI 304 Austenitic Stainless Steel, Mater. Des., 2004, 25(4), p 303–305.CrossRef
28.
go back to reference M. Xavior, Evaluating the Machinability of AISI 304 Stainless Steel Using Alumina Inserts, J. Achiev. Mater. Manuf. Eng., 2012, 55(2), p 841–847. M. Xavior, Evaluating the Machinability of AISI 304 Stainless Steel Using Alumina Inserts, J. Achiev. Mater. Manuf. Eng., 2012, 55(2), p 841–847.
29.
go back to reference Z. Tekıner and S. Yeşılyurt, Investigation of the Cutting Parameters Depending on Process Sound During Turning of AISI 304 Austenitic Stainless Steel, Mater. Des., 2004, 25(6), p 507–513.CrossRef Z. Tekıner and S. Yeşılyurt, Investigation of the Cutting Parameters Depending on Process Sound During Turning of AISI 304 Austenitic Stainless Steel, Mater. Des., 2004, 25(6), p 507–513.CrossRef
30.
go back to reference Y. Fedai et al., Optimization of Machining Parameters in Face Milling Using Multi-Objective Taguchi Technique, Tehnički glasnik, 2018, 12(2), p 104–108.CrossRef Y. Fedai et al., Optimization of Machining Parameters in Face Milling Using Multi-Objective Taguchi Technique, Tehnički glasnik, 2018, 12(2), p 104–108.CrossRef
31.
go back to reference G. Basar et al., Modeling and Optimization of Face Milling Process Parameters for AISI 4140 Steel, Tehnički glasnik, 2018, 12(1), p 5–10.CrossRef G. Basar et al., Modeling and Optimization of Face Milling Process Parameters for AISI 4140 Steel, Tehnički glasnik, 2018, 12(1), p 5–10.CrossRef
32.
go back to reference C. Ahilan, S. Kumanan, and N. Sivakumaran, Application of Grey Based Taguchi Method in Multi-Response Optimization of Turning Process, Adv. Prod. Eng. Manag., 2010, 5(3), p 171–180. C. Ahilan, S. Kumanan, and N. Sivakumaran, Application of Grey Based Taguchi Method in Multi-Response Optimization of Turning Process, Adv. Prod. Eng. Manag., 2010, 5(3), p 171–180.
33.
go back to reference I. Asiltürk and S. Neşeli, Multi Response Optimisation of CNC Turning Parameters via Taguchi Method-Based Response Surface Analysis, Measurement, 2012, 45(4), p 785–794.CrossRef I. Asiltürk and S. Neşeli, Multi Response Optimisation of CNC Turning Parameters via Taguchi Method-Based Response Surface Analysis, Measurement, 2012, 45(4), p 785–794.CrossRef
34.
go back to reference S.K. Khare and S. Agarwal, Optimization of Machining Parameters in Turning of AISI 4340 Steel under Cryogenic Condition using Taguchi Technique, Procedia CIRP, 2017, 63, p 610–614.CrossRef S.K. Khare and S. Agarwal, Optimization of Machining Parameters in Turning of AISI 4340 Steel under Cryogenic Condition using Taguchi Technique, Procedia CIRP, 2017, 63, p 610–614.CrossRef
35.
go back to reference Chinnasamy, M., et al., A Frontier Statistical Approach Towards Online Tool Condition Monitoring and Optimization for Dry Turning Operation of Sae 1015 Steel. Archives of Metallurgy & Materials, 2021. 66(3) Chinnasamy, M., et al., A Frontier Statistical Approach Towards Online Tool Condition Monitoring and Optimization for Dry Turning Operation of Sae 1015 Steel. Archives of Metallurgy & Materials, 2021. 66(3)
36.
go back to reference B. Das et al., Application of Grey Fuzzy Logic for the Optimization of CNC Milling Parameters for Al–4.5% Cu–TiC MMCs with Multi-Performance Characteristics, Eng. Sci. Technol. Int. J., 2016, 19(2), p 857–865. B. Das et al., Application of Grey Fuzzy Logic for the Optimization of CNC Milling Parameters for Al–4.5% Cu–TiC MMCs with Multi-Performance Characteristics, Eng. Sci. Technol. Int. J., 2016, 19(2), p 857–865.
37.
go back to reference S. Liu et al., Structural Optimization of the Cross-Beam of a Gantry Machine Tool Based on Grey Relational Analysis, Struct. Multidiscip. Optim., 2014, 50(2), p 297–311.CrossRef S. Liu et al., Structural Optimization of the Cross-Beam of a Gantry Machine Tool Based on Grey Relational Analysis, Struct. Multidiscip. Optim., 2014, 50(2), p 297–311.CrossRef
38.
go back to reference T. Muthuramalingam et al., Multi Criteria Decision Making of Abrasive Flow Oriented Process Parameters in Abrasive Water Jet Machining Using Taguchi–DEAR Methodology, SILICON, 2018, 10(5), p 2015–2021.CrossRef T. Muthuramalingam et al., Multi Criteria Decision Making of Abrasive Flow Oriented Process Parameters in Abrasive Water Jet Machining Using Taguchi–DEAR Methodology, SILICON, 2018, 10(5), p 2015–2021.CrossRef
39.
go back to reference Başar, G. and F. Kahraman, Prediction Of Surface Hardness in a Burnishing Process Using Taguchi Methot, Fuzzy Logic Model and Regression Analysis. 2018 Başar, G. and F. Kahraman, Prediction Of Surface Hardness in a Burnishing Process Using Taguchi Methot, Fuzzy Logic Model and Regression Analysis. 2018
40.
go back to reference P. Sathiya et al., Optimization of Laser Butt Welding Parameters Based on the Orthogonal Array with Fuzzy Logic and Desirability Approach, Struct. Multidiscip. Optim., 2011, 44(4), p 499–515.CrossRef P. Sathiya et al., Optimization of Laser Butt Welding Parameters Based on the Orthogonal Array with Fuzzy Logic and Desirability Approach, Struct. Multidiscip. Optim., 2011, 44(4), p 499–515.CrossRef
41.
go back to reference Zadeh, L.A., G.J. Klir, and B. Yuan, Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers. Vol. 6. 1996: World Scientific Zadeh, L.A., G.J. Klir, and B. Yuan, Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers. Vol. 6. 1996: World Scientific
42.
go back to reference Huu Phan, N. and T. Muthuramalingam, Multi Criteria Decision Making of Vibration Assisted EDM Process Parameters on Machining Silicon Steel Using Taguchi-DEAR Methodology. Silicon, 2020 Huu Phan, N. and T. Muthuramalingam, Multi Criteria Decision Making of Vibration Assisted EDM Process Parameters on Machining Silicon Steel Using Taguchi-DEAR Methodology. Silicon, 2020
43.
go back to reference Moganapriya, C., et al., Dry Machining Performance Studies on TiAlSiN Coated Inserts in Turning of AISI 420 Martensitic Stainless Steel and Multi-Criteria Decision Making Using Taguchi-DEAR Approach. Silicon, 2021: pp. 1–14 Moganapriya, C., et al., Dry Machining Performance Studies on TiAlSiN Coated Inserts in Turning of AISI 420 Martensitic Stainless Steel and Multi-Criteria Decision Making Using Taguchi-DEAR Approach. Silicon, 2021: pp. 1–14
44.
go back to reference G. Li et al., The Performance of TiAlSiN Coated Cemented Carbide Tools Enhanced by Inserting Ti Interlayers, Metals, 2019, 9(9), p 918.CrossRef G. Li et al., The Performance of TiAlSiN Coated Cemented Carbide Tools Enhanced by Inserting Ti Interlayers, Metals, 2019, 9(9), p 918.CrossRef
45.
go back to reference H. Pekşen and A. Kalyon, Optimization and Measurement of Flank Wear and Surface Roughness Via Taguchi Based Grey Relational Analysis, Mater. Manuf. Process., 2021, 36, p 1–10.CrossRef H. Pekşen and A. Kalyon, Optimization and Measurement of Flank Wear and Surface Roughness Via Taguchi Based Grey Relational Analysis, Mater. Manuf. Process., 2021, 36, p 1–10.CrossRef
46.
go back to reference Klir, G. and B. Yuan, Fuzzy sets and fuzzy logic. Vol. 4. 1995: Prentice hall New Jersey Klir, G. and B. Yuan, Fuzzy sets and fuzzy logic. Vol. 4. 1995: Prentice hall New Jersey
47.
go back to reference N. Senthilkumar, J. Sudha, and V. Muthukumar, A Grey-Fuzzy Approach for Optimizing Machining Parameters and the Approach Angle in Turning AISI 1045 Steel, Adv. Prod. Eng. Manag., 2015, 10(4), p 195–208. N. Senthilkumar, J. Sudha, and V. Muthukumar, A Grey-Fuzzy Approach for Optimizing Machining Parameters and the Approach Angle in Turning AISI 1045 Steel, Adv. Prod. Eng. Manag., 2015, 10(4), p 195–208.
48.
go back to reference D. Yu et al., Microstructure and Properties of TiAlSiN Coatings Prepared by Hybrid PVD Technology, Thin Solid Films, 2009, 517(17), p 4950–4955.CrossRef D. Yu et al., Microstructure and Properties of TiAlSiN Coatings Prepared by Hybrid PVD Technology, Thin Solid Films, 2009, 517(17), p 4950–4955.CrossRef
49.
go back to reference J. Liu et al., Cutting Performance and Wear Behavior of AlTiN- and TiAlSiN-Coated Carbide Tools During Dry Milling of Ti–6Al–4V, Acta Metallurgica Sinica (Engl. Lett.), 2020, 33(3), p 459–470.CrossRef J. Liu et al., Cutting Performance and Wear Behavior of AlTiN- and TiAlSiN-Coated Carbide Tools During Dry Milling of Ti–6Al–4V, Acta Metallurgica Sinica (Engl. Lett.), 2020, 33(3), p 459–470.CrossRef
50.
go back to reference O. Durand-Drouhin et al., Mechanical Properties and Failure Modes of TiAl (Si) N Single and Multilayer Thin Films, Surf. Coat. Technol., 2003, 163, p 260–266.CrossRef O. Durand-Drouhin et al., Mechanical Properties and Failure Modes of TiAl (Si) N Single and Multilayer Thin Films, Surf. Coat. Technol., 2003, 163, p 260–266.CrossRef
51.
go back to reference C. Ahilan, S. Kumanan, and N. Sivakumaran, Multi-objective Optimisation of CNC Turning Process Using Grey Based Fuzzy Logic, Int. J. Mach. Mach. Mater., 2009, 5(4), p 434–451. C. Ahilan, S. Kumanan, and N. Sivakumaran, Multi-objective Optimisation of CNC Turning Process Using Grey Based Fuzzy Logic, Int. J. Mach. Mach. Mater., 2009, 5(4), p 434–451.
52.
go back to reference J.T. Krishankant, M. Bector, and R. Kumar, Application of Taguchi Method for Optimizing Turning Process by the Effects of Machining Parameters, Int. J. Eng. Adv. Technol., 2012, 2(1), p 263–274. J.T. Krishankant, M. Bector, and R. Kumar, Application of Taguchi Method for Optimizing Turning Process by the Effects of Machining Parameters, Int. J. Eng. Adv. Technol., 2012, 2(1), p 263–274.
53.
go back to reference M.E. Abdelmoneim, and R. Scrutton, The Tribology of Cutting Tools During Finish Machining. I, Wear, 1973, 25(1), p 45–53.CrossRef M.E. Abdelmoneim, and R. Scrutton, The Tribology of Cutting Tools During Finish Machining. I, Wear, 1973, 25(1), p 45–53.CrossRef
Metadata
Title
Sustainable Hard Machining of AISI 304 Stainless Steel Through TiAlN, AlTiN, and TiAlSiN Coating and Multi-Criteria Decision Making Using Grey Fuzzy Coupled Taguchi Method
Authors
C. Moganapriya
R. Rajasekar
R. Santhosh
S. Saran
S. Santhosh
V. K. Gobinath
P. Sathish Kumar
Publication date
14-03-2022
Publisher
Springer US
Published in
Journal of Materials Engineering and Performance / Issue 9/2022
Print ISSN: 1059-9495
Electronic ISSN: 1544-1024
DOI
https://doi.org/10.1007/s11665-022-06751-2

Other articles of this Issue 9/2022

Journal of Materials Engineering and Performance 9/2022 Go to the issue

Premium Partners