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Published in: The International Journal of Advanced Manufacturing Technology 3-4/2022

31-08-2022 | ORIGINAL ARTICLE

Optimization of EDM process parameters based on variable-fidelity surrogate model

Authors: Jun Ma, Chunyang Yin, Xiaoke Li, Xinyu Han, Wuyi Ming, Shiyou Chen, Yang Cao, Kun Liu

Published in: The International Journal of Advanced Manufacturing Technology | Issue 3-4/2022

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Abstract

To balance the cost and accuracy in the optimization of EDM process parameters, the variable-fidelity surrogate model (VFM) was introduced in this paper to replace the implicit relationship between the EDM process parameters (peak current, duty cycle, pulse period) and performance functions (material remove rate, MRR, and surface roughness, Ra). Low-fidelity (LF) samples were obtained by using the low-cost EDM heat flow simulation, and high-fidelity (HF) samples were obtained by using the EDM machining experiments. By fusing the LF and HF samples, it is possible to establish an accurate expression of the implicit relationship between the EDM process parameters and performance functions in the variable-fidelity framework. Finally, the EDM process parameter model was established, and sequential quadratic programming (SQP) was used to obtain the optimal solution by calling the VFM. Through the verification experiments, the results showed that the parameter combination obtained by VFM is 15.1% higher than the MRR of the low-fidelity model (LFM) and 13.0% higher than the high-fidelity model (HFM), which reaches 88.285 mg/min, while the Ra has slightly decreased and is within the constraint range. From the above research, it can be concluded that the proposed technology has significant advantages and application potential in the field of EDM machining optimization.

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Literature
1.
go back to reference Ming W, Shen F, Zhang G, Liu G, Du J, Chen Z (2021) Green machining: a framework for optimization of cutting parameters to minimize energy consumption and exhaust emissions during electrical discharge machining of Al 6061 and SKD 11. J Clean Prod 285:124889CrossRef Ming W, Shen F, Zhang G, Liu G, Du J, Chen Z (2021) Green machining: a framework for optimization of cutting parameters to minimize energy consumption and exhaust emissions during electrical discharge machining of Al 6061 and SKD 11. J Clean Prod 285:124889CrossRef
4.
go back to reference Akıncıoğlu S (2021) Taguchi optimization of multiple performance characteristics in the electrical discharge machining of the TiGr2. Facta Universitatis, Series, Mechanical Engineering Akıncıoğlu S (2021) Taguchi optimization of multiple performance characteristics in the electrical discharge machining of the TiGr2. Facta Universitatis, Series, Mechanical Engineering
5.
go back to reference Engin N, Akincioğlu S (2019) Kriyojenik işlem görmüş nikel esaslı süper alaşımın elektro-erozyon işleme performansı optimizasyonu. Acad Platform J Eng Sci 7(1):115–126 Engin N, Akincioğlu S (2019) Kriyojenik işlem görmüş nikel esaslı süper alaşımın elektro-erozyon işleme performansı optimizasyonu. Acad Platform J Eng Sci 7(1):115–126
8.
go back to reference Mohanty C, Sahu J, Mahapatra S (2012) Thermal-structural analysis of electrical discharge machining process. 3rd Nirma-University International Conference on Engineering (NUiCONE). Ahmedabad, India p. 508–513 Mohanty C, Sahu J, Mahapatra S (2012) Thermal-structural analysis of electrical discharge machining process. 3rd Nirma-University International Conference on Engineering (NUiCONE). Ahmedabad, India p. 508–513
10.
go back to reference Xie Z, Zheng J, Quan B (2010) Optimization by grey relational analysis of EDM parameters on machining Ti-6Al-4V. International Conference on Manufacturing Engineering and Automation. Guangzhou, Peoples R China p. 540-+ Xie Z, Zheng J, Quan B (2010) Optimization by grey relational analysis of EDM parameters on machining Ti-6Al-4V. International Conference on Manufacturing Engineering and Automation. Guangzhou, Peoples R China p. 540-+
12.
go back to reference Basha S, Raju M, Raju M, Kolli M (2019) Multi response optimization of EDM process parameters for inconel x–750 using MOORA. J Mech Eng Res Dev (JMERD) 42(1):30–40 Basha S, Raju M, Raju M, Kolli M (2019) Multi response optimization of EDM process parameters for inconel x–750 using MOORA. J Mech Eng Res Dev (JMERD) 42(1):30–40
14.
go back to reference Świercz R, Oniszczuk-Świercz D, Chmielewski T (2019) Multi-response optimization of electrical discharge machining using the desirability function. Micromachines 10(1):72CrossRef Świercz R, Oniszczuk-Świercz D, Chmielewski T (2019) Multi-response optimization of electrical discharge machining using the desirability function. Micromachines 10(1):72CrossRef
15.
go back to reference Dang X, Processes M (2018) Constrained multi-objective optimization of EDM process parameters using kriging model and particle swarm algorithm 33(4):397–404 Dang X, Processes M (2018) Constrained multi-objective optimization of EDM process parameters using kriging model and particle swarm algorithm 33(4):397–404
16.
go back to reference Nayak B, Mahapatra S (2017) An intelligent approach for prediction of angular error in taper cutting using wire-EDM. 7th International Conference of Materials Processing and Characterization (ICMPC). Gokaraju Rangaraju Inst Eng Technol, Hyderabad, India p. 6121–6127 Nayak B, Mahapatra S (2017) An intelligent approach for prediction of angular error in taper cutting using wire-EDM. 7th International Conference of Materials Processing and Characterization (ICMPC). Gokaraju Rangaraju Inst Eng Technol, Hyderabad, India p. 6121–6127
17.
go back to reference Sahayaraj J, Arravind R, Subramanian P, Marichamy S, Stalin B (2020) Artificial neural network based prediction of responses on eglin steel using electrical discharge machining process. Mater Today Proc 33:4417–4419CrossRef Sahayaraj J, Arravind R, Subramanian P, Marichamy S, Stalin B (2020) Artificial neural network based prediction of responses on eglin steel using electrical discharge machining process. Mater Today Proc 33:4417–4419CrossRef
18.
go back to reference Li X, Yan F, Ma J, Chen Z, Wen X, Cao Y (2019) RBF and NSGA-II based EDM process parameters optimization with multiple constraints. Math Biosci Eng 16(5):5788–5803MathSciNetCrossRef Li X, Yan F, Ma J, Chen Z, Wen X, Cao Y (2019) RBF and NSGA-II based EDM process parameters optimization with multiple constraints. Math Biosci Eng 16(5):5788–5803MathSciNetCrossRef
19.
go back to reference Haque R, Sekh M, Kibria G, Haidar S (2021) Comparative study of parametric effects on the performance of simple and powder mixed EDM using aluminium and graphite powder on Inconel X750 alloy. 3rd International Conference on Materials, Manufacturing and Modelling (ICMMM). Vellore, India p. 8366–8373 Haque R, Sekh M, Kibria G, Haidar S (2021) Comparative study of parametric effects on the performance of simple and powder mixed EDM using aluminium and graphite powder on Inconel X750 alloy. 3rd International Conference on Materials, Manufacturing and Modelling (ICMMM). Vellore, India p. 8366–8373
20.
go back to reference Li L, Guo C, Song Y (2017) Simulation analysis of the crater size for single-pulse dry electrical discharge machining. 19th CIRP Conference on Electro Physical and Chemical Machining. Bilbao, Spain p. 292–297 Li L, Guo C, Song Y (2017) Simulation analysis of the crater size for single-pulse dry electrical discharge machining. 19th CIRP Conference on Electro Physical and Chemical Machining. Bilbao, Spain p. 292–297
23.
go back to reference Nas E, Akncolu S, Gkkaya H, Akncolu G (2017) Surface roughness optimization of EDM process of Hastelloy C22 super alloy. Int Conf Adv Mater Manuf Technol Nas E, Akncolu S, Gkkaya H, Akncolu G (2017) Surface roughness optimization of EDM process of Hastelloy C22 super alloy. Int Conf Adv Mater Manuf Technol
24.
go back to reference McGeough J, Rasmussen H (1982) A macroscopic model of electro-discharge machining. Int J Mach Tool Des Res 22(4):333–339CrossRef McGeough J, Rasmussen H (1982) A macroscopic model of electro-discharge machining. Int J Mach Tool Des Res 22(4):333–339CrossRef
26.
go back to reference Zhao Y, Zhang X, Liu X, Yamazaki K (2004) Geometric modeling of the linear motor driven electrical discharge machining (EDM) die-sinking process. Int J Mach Tools Manuf 44(1):1–9CrossRef Zhao Y, Zhang X, Liu X, Yamazaki K (2004) Geometric modeling of the linear motor driven electrical discharge machining (EDM) die-sinking process. Int J Mach Tools Manuf 44(1):1–9CrossRef
29.
go back to reference Singh A, Ghosh A (1999) A thermo-electric model of material removal during electric discharge machining. Int J Mach Tools Manuf 39(4):669–682CrossRef Singh A, Ghosh A (1999) A thermo-electric model of material removal during electric discharge machining. Int J Mach Tools Manuf 39(4):669–682CrossRef
30.
go back to reference Zhang L, Du J, Zhuang X, Wang Z, Pei J (2015) Geometric prediction of conic tool in micro-EDM milling with fix-length compensation using simulation. Int J Mach Tools Manuf 89:86–94CrossRef Zhang L, Du J, Zhuang X, Wang Z, Pei J (2015) Geometric prediction of conic tool in micro-EDM milling with fix-length compensation using simulation. Int J Mach Tools Manuf 89:86–94CrossRef
32.
go back to reference Nas E, Akncolu S, Gkkaya H, Akncolu G (2017) The effect of deep cryogenic treatment on the roughness of Hastelloy C22 super alloy in electrical discharge machining. Int Conf Adv Mater Manuf Technol Nas E, Akncolu S, Gkkaya H, Akncolu G (2017) The effect of deep cryogenic treatment on the roughness of Hastelloy C22 super alloy in electrical discharge machining. Int Conf Adv Mater Manuf Technol
33.
go back to reference Meng Z, Zhao J, Jiang C (2021) An efficient semi-analytical extreme value method for time-variant reliability analysis. Struct Multidiscip Optim 64(3):1469–1480MathSciNetCrossRef Meng Z, Zhao J, Jiang C (2021) An efficient semi-analytical extreme value method for time-variant reliability analysis. Struct Multidiscip Optim 64(3):1469–1480MathSciNetCrossRef
34.
go back to reference Xiao N, Yuan K, Zhan H (2022) System reliability analysis based on dependent Kriging predictions and parallel learning strategy. Reliab Eng Syst Saf 218:108083CrossRef Xiao N, Yuan K, Zhan H (2022) System reliability analysis based on dependent Kriging predictions and parallel learning strategy. Reliab Eng Syst Saf 218:108083CrossRef
35.
go back to reference Jiang C, Hu Z, Liu Y, Mourelatos Z, Gorsich D, Jayakumar P (2020) A sequential calibration and validation framework for model uncertainty quantification and reduction. Comput Methods Appl Mech Eng 368:113172MathSciNetCrossRef Jiang C, Hu Z, Liu Y, Mourelatos Z, Gorsich D, Jayakumar P (2020) A sequential calibration and validation framework for model uncertainty quantification and reduction. Comput Methods Appl Mech Eng 368:113172MathSciNetCrossRef
36.
go back to reference Li X, Zhu H, Chen Z, Ming W, Cao Y, He W, Ma J (2022) Limit state Kriging modeling for reliability-based design optimization through classification uncertainty quantification. Reliab Eng Syst Saf 108539 Li X, Zhu H, Chen Z, Ming W, Cao Y, He W, Ma J (2022) Limit state Kriging modeling for reliability-based design optimization through classification uncertainty quantification. Reliab Eng Syst Saf 108539
37.
go back to reference Han Z, Görtz S, Zimmermann R (2013) Improving variable-fidelity surrogate modeling via gradient-enhanced kriging and a generalized hybrid bridge function. Aerosp Sci Technol 25(1):177–189CrossRef Han Z, Görtz S, Zimmermann R (2013) Improving variable-fidelity surrogate modeling via gradient-enhanced kriging and a generalized hybrid bridge function. Aerosp Sci Technol 25(1):177–189CrossRef
40.
go back to reference Forrester A, Sóbester A, Keane A (2007) Multi-fidelity optimization via surrogate modelling. Proceedings of the royal society a: mathematical, physical and engineering sciences 463(2088):3251–3269MathSciNetCrossRef Forrester A, Sóbester A, Keane A (2007) Multi-fidelity optimization via surrogate modelling. Proceedings of the royal society a: mathematical, physical and engineering sciences 463(2088):3251–3269MathSciNetCrossRef
41.
go back to reference Forrester A, Keane A (2009) Recent advances in surrogate-based optimization. Prog Aerosp Sci 45(1–3):50–79CrossRef Forrester A, Keane A (2009) Recent advances in surrogate-based optimization. Prog Aerosp Sci 45(1–3):50–79CrossRef
Metadata
Title
Optimization of EDM process parameters based on variable-fidelity surrogate model
Authors
Jun Ma
Chunyang Yin
Xiaoke Li
Xinyu Han
Wuyi Ming
Shiyou Chen
Yang Cao
Kun Liu
Publication date
31-08-2022
Publisher
Springer London
Published in
The International Journal of Advanced Manufacturing Technology / Issue 3-4/2022
Print ISSN: 0268-3768
Electronic ISSN: 1433-3015
DOI
https://doi.org/10.1007/s00170-022-09963-x

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