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Erschienen in: Engineering with Computers 3/2017

15.09.2016 | Original Article

Application of JAYA algorithm for the optimization of machining performance characteristics during the turning of CFRP (epoxy) composites: comparison with TLBO, GA, and ICA

verfasst von: Kumar Abhishek, V. Rakesh Kumar, Saurav Datta, Siba Sankar Mahapatra

Erschienen in: Engineering with Computers | Ausgabe 3/2017

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Abstract

With the widespread application of carbon fibre-reinforced polymer (CFRP) composites, mostly in defence, automotive, and aerospace industries, the machining of those materials has become a major concern today. As the machinability of those composites differs from the conventional metals, a proper understanding of process behaviour and identification of the favourable machining environment (optimal setting of process parameters) are indeed necessary to improve product quality. The present work highlights the application potential of a multi-response optimization route by integrating nonlinear regression modelling, fuzzy inference system (FIS) in combination with the JAYA optimization algorithm, for the selection of optimal process parameter setting during the machining (turning) of carbon fibre-reinforced (epoxy) composites. Experiments have been carried out in consideration with spindle speed, feed rate, and depth of cut as process control parameters, whereas material removal rate (MRR), roughness average (R a), and net cutting force have been treated as machining performance characteristics. Attempt has been made to identify the best setting of process parameters for optimizing aforesaid output responses, simultaneously. The result of the JAYA algorithm has also been compared to that of TLBO (teaching–learning-based optimization) algorithm. In addition to this, the result obtained thereof has also been compared to that of two evolutionary optimization algorithms viz., GA (genetic algorithm) and ICA (imperialist competitive algorithm). Good agreement has been observed amongst the obtained results. The aforesaid case experimental study thus exhibits the application potential of a newly developed JAYA algorithm in the context of machining performance optimization during the turning of CFRP composites. The JAYA algorithm is basically a parameter-less optimization algorithm which does not require any algorithm-specific parameter and hence easy to implement.

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Literatur
1.
Zurück zum Zitat Abhishek K, Datta S, Mahapatra SS, Mandal G, Majumdar G (2013) Taguchi approach followed by fuzzy linguistic reasoning for quality-productivity optimization in machining operation a case study. J Manuf Technol Manag 24(6):929–951CrossRef Abhishek K, Datta S, Mahapatra SS, Mandal G, Majumdar G (2013) Taguchi approach followed by fuzzy linguistic reasoning for quality-productivity optimization in machining operation a case study. J Manuf Technol Manag 24(6):929–951CrossRef
2.
Zurück zum Zitat Abhishek K, Datta S, Mahapatra SS (2016) Multi-objective optimization in drilling of CFRP (polyester) composites: application of a fuzzy embedded harmony search (HS) algorithm. Measurement 77:222–239CrossRef Abhishek K, Datta S, Mahapatra SS (2016) Multi-objective optimization in drilling of CFRP (polyester) composites: application of a fuzzy embedded harmony search (HS) algorithm. Measurement 77:222–239CrossRef
3.
Zurück zum Zitat Abhishek K, Kumar VR, Datta S, Mahapatra SS (2015) Parametric appraisal and optimization in machining of CFRP composites by using TLBO (teaching–learning based optimization algorithm). J Intell Manuf. doi:10.1007/s10845-015-1050-8 Abhishek K, Kumar VR, Datta S, Mahapatra SS (2015) Parametric appraisal and optimization in machining of CFRP composites by using TLBO (teaching–learning based optimization algorithm). J Intell Manuf. doi:10.​1007/​s10845-015-1050-8
4.
Zurück zum Zitat Aghakhani M, Jalilian MM, Mehdiabadi M, Jalilian MM, Karami A (2011) Application of imperialist competitive algorithm in optimizing the width of heat affected zone in GMAW process. Int J Model Optim 1(3):221–225 Aghakhani M, Jalilian MM, Mehdiabadi M, Jalilian MM, Karami A (2011) Application of imperialist competitive algorithm in optimizing the width of heat affected zone in GMAW process. Int J Model Optim 1(3):221–225
5.
Zurück zum Zitat Ahilan C, Kumanan S, Sivakumaran N (2010) Application of grey based Taguchi method in multi-response optimization of turning process. Adv Prod Eng Manag 5(3):171–180 Ahilan C, Kumanan S, Sivakumaran N (2010) Application of grey based Taguchi method in multi-response optimization of turning process. Adv Prod Eng Manag 5(3):171–180
6.
Zurück zum Zitat Al-Aomar R (2006) A GA-based parameter design for single machine turning process with high-volume production. Comput Ind Eng 50(3):317–337CrossRef Al-Aomar R (2006) A GA-based parameter design for single machine turning process with high-volume production. Comput Ind Eng 50(3):317–337CrossRef
7.
Zurück zum Zitat Atashpaz-Gargari E, Lucas C (2007) Imperialist competitive algorithm: an algorithm for optimization inspired by imperialist competition. IEEE Congr Evol Comput, Singapore, pp 4661–4667 Atashpaz-Gargari E, Lucas C (2007) Imperialist competitive algorithm: an algorithm for optimization inspired by imperialist competition. IEEE Congr Evol Comput, Singapore, pp 4661–4667
8.
Zurück zum Zitat Bagci E, Isik B (2006) Investigation of surface roughness in turning unidirectional GFRP composites by using RS methodology and ANN. Int J Adv Manuf Technol 31(1–2):10–17CrossRef Bagci E, Isik B (2006) Investigation of surface roughness in turning unidirectional GFRP composites by using RS methodology and ANN. Int J Adv Manuf Technol 31(1–2):10–17CrossRef
9.
Zurück zum Zitat Cabrera FM, Beamud E, Hanafi I, Khamlichi A, Jabbouri A (2011) Fuzzy logic-based modeling of surface roughness parameters for CNC turning of PEEK CF30 by TiN-coated cutting tools. J Thermoplast Compos Mater 24:399–413CrossRef Cabrera FM, Beamud E, Hanafi I, Khamlichi A, Jabbouri A (2011) Fuzzy logic-based modeling of surface roughness parameters for CNC turning of PEEK CF30 by TiN-coated cutting tools. J Thermoplast Compos Mater 24:399–413CrossRef
10.
Zurück zum Zitat Caydas U, Hascalık A (2008) Use of the grey relational analysis to determine optimum laser cutting parameters with multi-performance characteristics. Opt Laser Technol 40(7):987–994CrossRef Caydas U, Hascalık A (2008) Use of the grey relational analysis to determine optimum laser cutting parameters with multi-performance characteristics. Opt Laser Technol 40(7):987–994CrossRef
11.
Zurück zum Zitat Datta S, Sahu RK, Mahapatra SS, Biswas A, Majumdar (2014) Optimisation of percent dilution and HAZ width of submerged arc weldment using Taguchi philosophy coupled with fuzzy inference system. Int J Prod Quality Manag 13(4):430–449CrossRef Datta S, Sahu RK, Mahapatra SS, Biswas A, Majumdar (2014) Optimisation of percent dilution and HAZ width of submerged arc weldment using Taguchi philosophy coupled with fuzzy inference system. Int J Prod Quality Manag 13(4):430–449CrossRef
12.
Zurück zum Zitat Davim JP (2012) Computational methods for optimizing manufacturing technology. IGI Global, HersheyCrossRef Davim JP (2012) Computational methods for optimizing manufacturing technology. IGI Global, HersheyCrossRef
13.
Zurück zum Zitat Davim JP (ed) (2012) Statistical and computational methods in manufacturing. Springer, Heidelberg. ISBN 978-3-642-25858-9 Davim JP (ed) (2012) Statistical and computational methods in manufacturing. Springer, Heidelberg. ISBN 978-3-642-25858-9
14.
Zurück zum Zitat Davim JP (ed) (2015) Machinability of fibre-reinforced plastics. DE Gruyter, Berlin. ISBN 9783110292220 Davim JP (ed) (2015) Machinability of fibre-reinforced plastics. DE Gruyter, Berlin. ISBN 9783110292220
15.
Zurück zum Zitat Davim JP, Mata F (2005) Optimisation of surface roughness on turning fibre-reinforced plastics (FRPS) with diamond cutting tools. Int J Adv Manuf Technol 26(4):319–323CrossRef Davim JP, Mata F (2005) Optimisation of surface roughness on turning fibre-reinforced plastics (FRPS) with diamond cutting tools. Int J Adv Manuf Technol 26(4):319–323CrossRef
16.
Zurück zum Zitat Davim JP, Mata F (2007) New machinability study of glass fibre reinforced plastics using polycrystalline diamond and cemented carbide (K15) tools. Mater Des 28(3):1050–1054CrossRef Davim JP, Mata F (2007) New machinability study of glass fibre reinforced plastics using polycrystalline diamond and cemented carbide (K15) tools. Mater Des 28(3):1050–1054CrossRef
17.
Zurück zum Zitat Davim JP, Mata F, Gaitonde VN, Karnik SR (2010) Machinability evaluation in unreinforced and reinforced PEEK composites using response surface models. J Thermoplast Compos Mater 23(1):5–18CrossRef Davim JP, Mata F, Gaitonde VN, Karnik SR (2010) Machinability evaluation in unreinforced and reinforced PEEK composites using response surface models. J Thermoplast Compos Mater 23(1):5–18CrossRef
18.
Zurück zum Zitat Davim JP, Silva LR, Festas A, Abrão AM (2009) Machinability study on precision turning of PA66 polyamide with and without glass fiber reinforcing. Mater Des 30(2):228–234CrossRef Davim JP, Silva LR, Festas A, Abrão AM (2009) Machinability study on precision turning of PA66 polyamide with and without glass fiber reinforcing. Mater Des 30(2):228–234CrossRef
19.
Zurück zum Zitat Davim JP, Reis P (2004) Machinability study on composite (polyetheretherketone reinforced with 30% glass fibre–PEEK GF 30) using polycrystalline diamond (PCD) and cemented carbide (K20) tools. Int J Adv Manuf Technol 23(5):412–418CrossRef Davim JP, Reis P (2004) Machinability study on composite (polyetheretherketone reinforced with 30% glass fibre–PEEK GF 30) using polycrystalline diamond (PCD) and cemented carbide (K20) tools. Int J Adv Manuf Technol 23(5):412–418CrossRef
20.
Zurück zum Zitat Gupta M, Gill SK (2012) Prediction of cutting force in turning of UD-GFRP using mathematical model and simulated annealing. Front Mech Eng 7(4):417–426CrossRef Gupta M, Gill SK (2012) Prediction of cutting force in turning of UD-GFRP using mathematical model and simulated annealing. Front Mech Eng 7(4):417–426CrossRef
21.
Zurück zum Zitat Haq AN, Sivakumar K, Saravanan R, Karthikeyan K (2006) Particle swarm optimization (PSO) algorithm for optimal machining allocation of clutch assembly. Int J Adv Manuf Technol 27(9–10):865–869 Haq AN, Sivakumar K, Saravanan R, Karthikeyan K (2006) Particle swarm optimization (PSO) algorithm for optimal machining allocation of clutch assembly. Int J Adv Manuf Technol 27(9–10):865–869
22.
Zurück zum Zitat He S, Prempain E, Wu QH (2004) An improved particle swarm optimizer for mechanical design optimization problems. Eng Optim 36(5):585–605MathSciNetCrossRef He S, Prempain E, Wu QH (2004) An improved particle swarm optimizer for mechanical design optimization problems. Eng Optim 36(5):585–605MathSciNetCrossRef
23.
Zurück zum Zitat Hsu CM (2015) Cost-based procedure for multi-response parameter design problems using GEP, Taguchi quality loss, and PSO: case study on heat sink design. Int J Comput Intell Sys 8(1):158–174CrossRef Hsu CM (2015) Cost-based procedure for multi-response parameter design problems using GEP, Taguchi quality loss, and PSO: case study on heat sink design. Int J Comput Intell Sys 8(1):158–174CrossRef
24.
Zurück zum Zitat Hussain SA, Pandurangadu V, Kumar KP, Bharathi VV (2011) A predictive model for surface roughness in turning glass fiber reinforced plastics by carbide tool (K-20) using soft computing. Jordan J Mech Ind Eng 5(5):433–438 Hussain SA, Pandurangadu V, Kumar KP, Bharathi VV (2011) A predictive model for surface roughness in turning glass fiber reinforced plastics by carbide tool (K-20) using soft computing. Jordan J Mech Ind Eng 5(5):433–438
25.
Zurück zum Zitat Jinturkar AM, Deshmukh SS, Agarkar SV, Chavhan GR (2010) Determination of water quality index by fuzzy logic approach: a case of ground water in an Indian town. Water Sci Technol 61(8):1987–1994CrossRef Jinturkar AM, Deshmukh SS, Agarkar SV, Chavhan GR (2010) Determination of water quality index by fuzzy logic approach: a case of ground water in an Indian town. Water Sci Technol 61(8):1987–1994CrossRef
26.
Zurück zum Zitat Kaveh A, Talatahari S (2010) Optimum design of skeletal structures using imperialist competitive algorithm. Comput Struct 88(21–22):1220–1229CrossRefMATH Kaveh A, Talatahari S (2010) Optimum design of skeletal structures using imperialist competitive algorithm. Comput Struct 88(21–22):1220–1229CrossRefMATH
27.
Zurück zum Zitat Khan MA, Kumar AS, Poomari A (2012) A hybrid algorithm to optimize cutting parameter for machining GFRP composite using alumina cutting tools. Int J Adv Manuf Technol 59(9–12):1047–1056CrossRef Khan MA, Kumar AS, Poomari A (2012) A hybrid algorithm to optimize cutting parameter for machining GFRP composite using alumina cutting tools. Int J Adv Manuf Technol 59(9–12):1047–1056CrossRef
28.
Zurück zum Zitat Krishnamoorthy A, Boopathy SR, Palanikumar K (2009) Delamination analysis in drilling of CFRP composites using response surface methodology. J Compos Mater 43(24):2885–2902CrossRef Krishnamoorthy A, Boopathy SR, Palanikumar K (2009) Delamination analysis in drilling of CFRP composites using response surface methodology. J Compos Mater 43(24):2885–2902CrossRef
29.
Zurück zum Zitat Krishnamoorthy A, Boopathy SR, Palanikumar K, Davim JP (2012) Application of grey fuzzy logic for the optimization of drilling parameters for CFRP composites with multiple performance characteristics. Measurement 45(5):1286–1296CrossRef Krishnamoorthy A, Boopathy SR, Palanikumar K, Davim JP (2012) Application of grey fuzzy logic for the optimization of drilling parameters for CFRP composites with multiple performance characteristics. Measurement 45(5):1286–1296CrossRef
30.
Zurück zum Zitat Krishnaraj V, Prabukarthi A, Ramanathan A, Elanghovan N, Senthil Kumar M, Zitoune R, Davim JP (2012) Optimization of machining parameters at high speed drilling of carbon fiber reinforced plastic (CFRP) laminates. Compos Part B 43(4):1791–1799CrossRef Krishnaraj V, Prabukarthi A, Ramanathan A, Elanghovan N, Senthil Kumar M, Zitoune R, Davim JP (2012) Optimization of machining parameters at high speed drilling of carbon fiber reinforced plastic (CFRP) laminates. Compos Part B 43(4):1791–1799CrossRef
31.
Zurück zum Zitat Kumar A, Bharaneeswaran P, Annamalai R (2012) Experimental investigation of K20 carbide and PCD insert on machining GFRP composite. Int Conf Ind Intell Inf Singapore 31:149–155 Kumar A, Bharaneeswaran P, Annamalai R (2012) Experimental investigation of K20 carbide and PCD insert on machining GFRP composite. Int Conf Ind Intell Inf Singapore 31:149–155
32.
Zurück zum Zitat Kumar J, Khamba JS (2010) Multi-response optimisation in ultrasonic machining of titanium using Taguchi’s approach and utility concept. Int J Manuf Res 5(2):139–160CrossRef Kumar J, Khamba JS (2010) Multi-response optimisation in ultrasonic machining of titanium using Taguchi’s approach and utility concept. Int J Manuf Res 5(2):139–160CrossRef
33.
Zurück zum Zitat Kumar KV, Sait AN, Panneerselvam R (2014) Machinability study of hybrid-polymer composite pipe using response surface methodology and genetic algorithm. J Sandw Struct Mat. doi:1099636214532115 Kumar KV, Sait AN, Panneerselvam R (2014) Machinability study of hybrid-polymer composite pipe using response surface methodology and genetic algorithm. J Sandw Struct Mat. doi:1099636214532115
34.
Zurück zum Zitat Lan TS (2009) Taguchi optimization of multi-objective CNC machining using TOPSIS. Inf Technol J 8(6):917–922CrossRef Lan TS (2009) Taguchi optimization of multi-objective CNC machining using TOPSIS. Inf Technol J 8(6):917–922CrossRef
35.
Zurück zum Zitat Mamdani EH (1976) Advances in the linguistic synthesis of fuzzy controllers. Int J Man Mach Stud 8(6):669–678CrossRefMATH Mamdani EH (1976) Advances in the linguistic synthesis of fuzzy controllers. Int J Man Mach Stud 8(6):669–678CrossRefMATH
36.
Zurück zum Zitat Mamdani EH (1977) Applications of fuzzy logic to approximate reasoning using linguistic synthesis. IEEE Trans Comput 26(12):1182–1191CrossRefMATH Mamdani EH (1977) Applications of fuzzy logic to approximate reasoning using linguistic synthesis. IEEE Trans Comput 26(12):1182–1191CrossRefMATH
37.
Zurück zum Zitat Mata F, Reis P, Davim JP (2006) Physical cutting model of polyamide composites (PA66 GF30). Mater Sci Forum 514–516:643–647CrossRef Mata F, Reis P, Davim JP (2006) Physical cutting model of polyamide composites (PA66 GF30). Mater Sci Forum 514–516:643–647CrossRef
38.
Zurück zum Zitat Meenu, Kumar S (2013) Prediction of surface roughness in turning of UD-GFRP using artifical neural network. Mech Confab 2(3):46–56 Meenu, Kumar S (2013) Prediction of surface roughness in turning of UD-GFRP using artifical neural network. Mech Confab 2(3):46–56
39.
Zurück zum Zitat Meenu, Kumar S, Satsangi PS, Sardana HK (2012) Optimization of surface roughness in turning unidirectional glass fiber reinforced plastics (UD-GFRP) composites using polycrystalline diamond (PCD) cutting tool. Indian J Eng Mat Sci 19(3):163–174 Meenu, Kumar S, Satsangi PS, Sardana HK (2012) Optimization of surface roughness in turning unidirectional glass fiber reinforced plastics (UD-GFRP) composites using polycrystalline diamond (PCD) cutting tool. Indian J Eng Mat Sci 19(3):163–174
40.
Zurück zum Zitat Mondal D, Pal SK, Saha P (2007) Modeling of electrical discharge machining process using back propagation neural network and multi-objective optimization using non-dominating sorting genetic algorithm-II. J Mater Process Technol 186(1–3):154–162CrossRef Mondal D, Pal SK, Saha P (2007) Modeling of electrical discharge machining process using back propagation neural network and multi-objective optimization using non-dominating sorting genetic algorithm-II. J Mater Process Technol 186(1–3):154–162CrossRef
41.
Zurück zum Zitat Nazari-Shirkouhi S, Eivazy H, Ghodsi R, Rezaie K, Atashpaz-Gargari E (2010) Solving the integrated product mix-outsourcing problem by a novel meta-heuristic algorithm: imperialist competitive algorithm. Expert Syst Appl 37(12):7615–7626CrossRef Nazari-Shirkouhi S, Eivazy H, Ghodsi R, Rezaie K, Atashpaz-Gargari E (2010) Solving the integrated product mix-outsourcing problem by a novel meta-heuristic algorithm: imperialist competitive algorithm. Expert Syst Appl 37(12):7615–7626CrossRef
42.
Zurück zum Zitat Palanikumar K (2009) Surface roughness model for machining glass fiber reinforced plastics by PCD tool using fuzzy logics. J Reinf Plast Compos 28(18):2273–2286CrossRef Palanikumar K (2009) Surface roughness model for machining glass fiber reinforced plastics by PCD tool using fuzzy logics. J Reinf Plast Compos 28(18):2273–2286CrossRef
43.
Zurück zum Zitat Palanikumar K, Davim JP (2009) Assessment of some factors influencing tool wear on the machining of glass fiber-reinforced plastics by coated cemented carbide tools. J Mater Process Technol 209(1):511–519CrossRef Palanikumar K, Davim JP (2009) Assessment of some factors influencing tool wear on the machining of glass fiber-reinforced plastics by coated cemented carbide tools. J Mater Process Technol 209(1):511–519CrossRef
44.
Zurück zum Zitat Palanikumar K, Karunamoorthy L, Karthikeyan R (2006) Multiple performance optimization of machining parameters on the machining of GFRP composites using Carbide (K10) tool. Mater Manuf Process 21(8):846–852CrossRef Palanikumar K, Karunamoorthy L, Karthikeyan R (2006) Multiple performance optimization of machining parameters on the machining of GFRP composites using Carbide (K10) tool. Mater Manuf Process 21(8):846–852CrossRef
45.
Zurück zum Zitat Palanikumar K, Karunamoorthy L, Karthikeyan R, Latha B (2006) Optimization of machining parameters in turning GFRP composites using a Carbide (K10) tool based on the Taguchi method with fuzzy logics. Met Mater Int 12(6):483–491CrossRef Palanikumar K, Karunamoorthy L, Karthikeyan R, Latha B (2006) Optimization of machining parameters in turning GFRP composites using a Carbide (K10) tool based on the Taguchi method with fuzzy logics. Met Mater Int 12(6):483–491CrossRef
46.
Zurück zum Zitat Palanikumar K, Latha B, Senthilkumar VS, Karthikeyan R (2009) Multiple performance optimization in machining of GFRP composites by a PCD tool using non-dominated sorting genetic algorithm (NSGA-II). Met Mater Int 15(2):249–258CrossRef Palanikumar K, Latha B, Senthilkumar VS, Karthikeyan R (2009) Multiple performance optimization in machining of GFRP composites by a PCD tool using non-dominated sorting genetic algorithm (NSGA-II). Met Mater Int 15(2):249–258CrossRef
47.
Zurück zum Zitat Pawar PJ, Rao RV (2013) Parameter optimization of machining processes using teaching–learning-based optimization algorithm. Int J Adv Manuf Technol 67(5):995–1006CrossRef Pawar PJ, Rao RV (2013) Parameter optimization of machining processes using teaching–learning-based optimization algorithm. Int J Adv Manuf Technol 67(5):995–1006CrossRef
48.
Zurück zum Zitat Puhan D, Mahapatra SS, Sahu J, Das L (2013) A hybrid approach for multi-response optimization of non-conventional machining on AlSiCp MMC. Measurement 46(9):581–3592CrossRef Puhan D, Mahapatra SS, Sahu J, Das L (2013) A hybrid approach for multi-response optimization of non-conventional machining on AlSiCp MMC. Measurement 46(9):581–3592CrossRef
49.
Zurück zum Zitat Rajasekaran T, Palanikumar K, Vinayagam BK (2011) Application of fuzzy logic for modeling surface roughness in turning CFRP composites using CBN tool. Prod Eng Res Dev 5(2):191–199CrossRef Rajasekaran T, Palanikumar K, Vinayagam BK (2011) Application of fuzzy logic for modeling surface roughness in turning CFRP composites using CBN tool. Prod Eng Res Dev 5(2):191–199CrossRef
50.
Zurück zum Zitat Rajasekaran T, Palanikumar K, Vinayagam BK (2012) Turning CFRP composites with ceramic tool for surface roughness analysis. Procedia Eng 38:2922–2929CrossRef Rajasekaran T, Palanikumar K, Vinayagam BK (2012) Turning CFRP composites with ceramic tool for surface roughness analysis. Procedia Eng 38:2922–2929CrossRef
51.
Zurück zum Zitat Rajmohan T, Palanikumar K, Prakash S (2013) Grey-fuzzy algorithm to optimise machining parameters in drilling of hybrid metal matrix composites. Compos B Eng 50:297–308CrossRef Rajmohan T, Palanikumar K, Prakash S (2013) Grey-fuzzy algorithm to optimise machining parameters in drilling of hybrid metal matrix composites. Compos B Eng 50:297–308CrossRef
52.
Zurück zum Zitat Rao RV, Waghmare GG (2016) A new optimization algorithm for solving complex constrained design optimization problems. Eng Optim. doi:10.1080%2F0305215X.2016.1164855 (Published online: 13 Apr 2016) Rao RV, Waghmare GG (2016) A new optimization algorithm for solving complex constrained design optimization problems. Eng Optim. doi:10.1080%2F0305215X.2016.1164855 (Published online: 13 Apr 2016)
53.
Zurück zum Zitat Rao RV (2016) Jaya: a simple and new optimization algorithm for solving constrained and unconstrained optimization problems. Int J Ind Eng Comput 7:19–34 Rao RV (2016) Jaya: a simple and new optimization algorithm for solving constrained and unconstrained optimization problems. Int J Ind Eng Comput 7:19–34
54.
Zurück zum Zitat Rao RV, More KC, Taler J, Ocłoń P (2016) Dimensional optimization of a micro-channel heat sink using Jaya algorithm. Appl Therm Eng 103:572–582CrossRef Rao RV, More KC, Taler J, Ocłoń P (2016) Dimensional optimization of a micro-channel heat sink using Jaya algorithm. Appl Therm Eng 103:572–582CrossRef
55.
Zurück zum Zitat Rao RV, Savsani VJ, Vakharia DP (2011) Teaching–learning-based optimization: a novel method for constrained mechanical design optimization problems. Comput Aided Design 43(3):303–315CrossRef Rao RV, Savsani VJ, Vakharia DP (2011) Teaching–learning-based optimization: a novel method for constrained mechanical design optimization problems. Comput Aided Design 43(3):303–315CrossRef
56.
Zurück zum Zitat Rao RV, Kalyankar VD (2013) Multi-pass turning process parameter optimization using teaching–learning-based optimization algorithm. Scientia Iranica 20(3):967–974 Rao RV, Kalyankar VD (2013) Multi-pass turning process parameter optimization using teaching–learning-based optimization algorithm. Scientia Iranica 20(3):967–974
57.
Zurück zum Zitat Rao RV, Kalyankar VD (2013) Parameter optimization of modern machining processes using teaching–learning-based optimization algorithm. Eng Appl Artif Intell 26(1):524–531CrossRef Rao RV, Kalyankar VD (2013) Parameter optimization of modern machining processes using teaching–learning-based optimization algorithm. Eng Appl Artif Intell 26(1):524–531CrossRef
58.
Zurück zum Zitat Sahoo P (2011) Optimization of turning parameters for surface roughness using RSM and GA. Adv Prod Eng Manag 6(3):197–208 Sahoo P (2011) Optimization of turning parameters for surface roughness using RSM and GA. Adv Prod Eng Manag 6(3):197–208
59.
Zurück zum Zitat Sahu J, Mahapatra SS, Puhan D (2013) Multi-response optimisation of electrical discharge machining process using combined approach of RSM and FIS. Int J Prod Qual Manag 13(2):185–208 Sahu J, Mahapatra SS, Puhan D (2013) Multi-response optimisation of electrical discharge machining process using combined approach of RSM and FIS. Int J Prod Qual Manag 13(2):185–208
60.
Zurück zum Zitat Sait AN, Aravindan S, Haq AN (2009) Optimisation of machining parameters of glass-fibre-reinforced plastic (GFRP) pipes by desirability function analysis using Taguchi technique. Int J Adv Manuf Technol 43(5–6):581–589CrossRef Sait AN, Aravindan S, Haq AN (2009) Optimisation of machining parameters of glass-fibre-reinforced plastic (GFRP) pipes by desirability function analysis using Taguchi technique. Int J Adv Manuf Technol 43(5–6):581–589CrossRef
61.
Zurück zum Zitat Sarma PMMS, Karunamoorthy L, Palanikumar K (2008) Modeling and analysis of cutting force in turning of GFRP composites by CBN tools. J Reinf Plast Compos 27(7):711–723CrossRef Sarma PMMS, Karunamoorthy L, Palanikumar K (2008) Modeling and analysis of cutting force in turning of GFRP composites by CBN tools. J Reinf Plast Compos 27(7):711–723CrossRef
62.
Zurück zum Zitat Shahriar M, Hossain J, Ahmad N (2014) Surface roughness prediction modelling for commercial dies using ANFIS, ANN and RSM. Int J Ind Sys Eng 16(2):156–183 Shahriar M, Hossain J, Ahmad N (2014) Surface roughness prediction modelling for commercial dies using ANFIS, ANN and RSM. Int J Ind Sys Eng 16(2):156–183
63.
Zurück zum Zitat Singh A, Datta S, Mahapatra SS (2011) Application of TOPSIS in the Taguchi method for optimal machining parameter selection. J Manuf Sci Prod 11(1–3):49–60 Singh A, Datta S, Mahapatra SS (2011) Application of TOPSIS in the Taguchi method for optimal machining parameter selection. J Manuf Sci Prod 11(1–3):49–60
64.
Zurück zum Zitat Singh H, Kumar P (2006) Optimizing multi-machining characteristics through Taguchi’s approach and utility concept. J Manuf Technol Manag 17(2):255–274MathSciNetCrossRef Singh H, Kumar P (2006) Optimizing multi-machining characteristics through Taguchi’s approach and utility concept. J Manuf Technol Manag 17(2):255–274MathSciNetCrossRef
65.
Zurück zum Zitat Thirumalai R, Senthilkumaar JS (2013) Multi-criteria decision making in the selection of machining parameters for Inconel 718. J Mech Sci Technol 27(4):1109–1116CrossRef Thirumalai R, Senthilkumaar JS (2013) Multi-criteria decision making in the selection of machining parameters for Inconel 718. J Mech Sci Technol 27(4):1109–1116CrossRef
66.
Zurück zum Zitat Vijayakumar K, Prabhaharan G, Asokan P, Saravanan R (2003) Optimization of multi-pass turning operations using ant colony system. Int J Mach Tools Manuf 43(15):1633–1639CrossRef Vijayakumar K, Prabhaharan G, Asokan P, Saravanan R (2003) Optimization of multi-pass turning operations using ant colony system. Int J Mach Tools Manuf 43(15):1633–1639CrossRef
67.
Zurück zum Zitat Zhang Y, Yang X, Cattani C, Venkata Rao R, Wang S, Phillips P (2016) Tea category identification using a novel fractional Fourier entropy and Jaya algorithm. Entropy 18(3):77. doi:10.3390/e18030077 CrossRef Zhang Y, Yang X, Cattani C, Venkata Rao R, Wang S, Phillips P (2016) Tea category identification using a novel fractional Fourier entropy and Jaya algorithm. Entropy 18(3):77. doi:10.​3390/​e18030077 CrossRef
68.
Zurück zum Zitat Zhang H, Tam CM, Shi JJ (2003) Application of fuzzy logic to simulation for construction operations. J Comput Civil Eng 17(1):38–45CrossRef Zhang H, Tam CM, Shi JJ (2003) Application of fuzzy logic to simulation for construction operations. J Comput Civil Eng 17(1):38–45CrossRef
Metadaten
Titel
Application of JAYA algorithm for the optimization of machining performance characteristics during the turning of CFRP (epoxy) composites: comparison with TLBO, GA, and ICA
verfasst von
Kumar Abhishek
V. Rakesh Kumar
Saurav Datta
Siba Sankar Mahapatra
Publikationsdatum
15.09.2016
Verlag
Springer London
Erschienen in
Engineering with Computers / Ausgabe 3/2017
Print ISSN: 0177-0667
Elektronische ISSN: 1435-5663
DOI
https://doi.org/10.1007/s00366-016-0484-8

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