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Integrated ANN-LWPA for cutting parameter optimization in WEDM

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Abstract

In this paper, we present a new approach to determinate cutting parameters in wire electrical discharge machining (WEDM), integrated artificial neuron network (ANN), and wolf pack algorithm based on the strategy of the leader (LWPA). The cutting parameters considered in this paper are pulse-on, current, water pressure, and cutting feed rate. Models of the effects of the four parameters on machining time (T p ), machining cost (C p ), and surface roughness (Ra) are mathematically constructed. An ANN-LWPA integration system with multiple fitness functions is proposed to solve the modelling problem. By using the proposed approach, this study demonstrates that T p , C p , and Ra can be estimated at 164.1852 min, 239.5442 RMB, and 1.0223 μm in single objective optimization, respectively. For example, as for Ra, integrated ANN-LWPA has optimized the Ra value by the reduction of 0.1337 μm (11.6 %), 0.3377 μm (24.8 %), and 0.105 μm (10.3 %) compared to experimental data, regression model, and ANN model, respectively. Consequently, the ANN-LWPA integration system boasts some advantages over decreasing the value of fitness functions by comparison with the experimental regression model, ANN model, and conventional LWPA result. Moreover, the proposed integration system can be also utilized to obtain multiple solutions by uniform design-based exploration. Therefore, in order to solve complex machining optimization problems, an intelligent process scheme could be integrated into the numeric control system of WEDM.

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References

  1. Liao TW, Chen LJ (1998) Manufacturing process modeling and optimization based on multi-layer perceptron network. J Manuf Sci Eng 120(1):109–119

    Article  MathSciNet  Google Scholar 

  2. Yang RT, Tzeng CJ, Yang YK, Hsieh MH (2012) Optimization of wire electrical discharge machining process parameters for cutting tungsten. Int J Adv Manuf Technol 60(1–4):135–147

    Article  Google Scholar 

  3. Kumar K, Agarwal S (2012) Multi-objective parametric optimization on machining with wire electric discharge machining. Int J Adv Manuf Technol 62(5–8):617–633

    Article  Google Scholar 

  4. Zhang G, Zhang Z, Guo J, Ming W, Li M, Huang Y (2013) Modeling and optimization of medium-speed WEDM process parameters for machining SKD11. Mater Manuf Process 28(10):1124–1132

    Article  Google Scholar 

  5. Zhang G, Zhang Z, Ming W, Guo J, Huang Y, Shao X (2014) The multi-objective optimization of medium-speed WEDM process parameters for machining SKD11 steel by the hybrid method of RSM and NSGA-II. Int J Adv Manuf Technol 70(9–12):2097–2109

    Article  Google Scholar 

  6. Saha P, Tarafdar D, Pal SK, Saha P, Srivastava AK, Das K (2013) Multi-objective optimization in wire-electro-discharge machining of TiC reinforced composite through Neuro-Genetic technique. Appl. Soft Comput. 13(4):2065–2074

    Article  Google Scholar 

  7. Joshi SN, Pande SS (2011) Intelligent process modeling and optimization of die-sinking electric discharge machining. Appl Soft Comput 11(2):2743–2755

    Article  Google Scholar 

  8. Rajyalakshmi G, Ramaiah PV (2013) Multiple process parameter optimization of wire electrical discharge machining on Inconel 825 using Taguchi grey relational analysis. Int J Adv Manuf Technol 69(5–8):1249–1262

    Article  Google Scholar 

  9. Ji R, Liu Y, Zhang Y, Cai B, Li H, Ma J (2010) Optimizing machining parameters of silicon carbide ceramics with ED milling and mechanical grinding combined process. Int J Adv Manuf Technol 51(1–4):195–204

    Article  Google Scholar 

  10. Ji R, Liu Y, Zhang Y, Cai B, Shen R (2010) Electric discharge milling and mechanical grinding compound machining of silicon carbide ceramic. Mach Sci Technol 14(4):502– 521

    Article  Google Scholar 

  11. Ji R, Liu Y, Zhang Y, Wang F, Cai B, Dong X (2012) Machining performance optimization in end ED milling and mechanical grinding compound process. Mater Manuf Process 27(2):221– 228

    Article  Google Scholar 

  12. Mukherjee R, Chakraborty S, Samanta S (2012) Selection of wire electrical discharge machining process parameters using non-traditional optimization algorithms. Appl Soft Comput 12(8):2506–2516

    Article  Google Scholar 

  13. Kuriachen B, Somashekhar KP, Mathew J (2014) Multiresponse optimization of micro-wire electrical discharge machining process. Int J Adv Manuf Technol 76(1–4):91–104

    Google Scholar 

  14. Raja SB, Pramod CS, Krishna KV, Ragunathan A, Vinesh S (2015) Optimization of electrical discharge machining parameters on hardened die steel using Firefly Algorithm. Eng Comput 31(1):1–9

    Article  Google Scholar 

  15. Wu H S, Zhang F M (2014) Wolf Pack Algorithm for Unconstrained Global Optimization. Math Probl Eng

  16. Leung Y W, Wang Y (2000) Multiobjective programming using uniform design and genetic algorithm. IEEE Trans Syst Man Cybern Part C Appl Rev 30(3):293–304

    Article  Google Scholar 

  17. Zuperl U, Cus F (2003) Optimization of cutting conditions during cutting by using neural networks. Robot Comput Integr Manuf 19(1):189–199

    Article  MATH  Google Scholar 

  18. Cus F, Balic J (2003) Optimization of cutting process by GA approach. Robot Comput Integr Manuf 19 (1):113–121

    Article  Google Scholar 

  19. Haykin S, Network N (2004) A comprehensive foundation. Neural Netw 2

  20. Hagan M T, Demuth H B, Beale M H (1996) Neural network design. Pws Pub, Boston, pp 2–14

    Google Scholar 

  21. Rong Y, Zhang Z, Zhang G, Yue C, Gu Y, Huang Y, Shao X (2015) Parameters optimization of laser brazing in crimping butt using Taguchi and BPNN-GA. Opt Lasers Eng 67:94–104

    Article  Google Scholar 

  22. Liu C, Yan X, Liu C, Wu H (2011) The wolf colony algorithm and its application. Chin J Electron 20(2):212–216

    Google Scholar 

  23. Zhou Q, Zhou YQ (2013) Wolf colony search algorithm based on leader strategy. Chinese transaction of Allication Research of Computers 30(9):2629–2632

    Google Scholar 

  24. Solimanpur M, Ranjdoostfard F (2009) Optimisation of cutting parameters using a multi-objective genetic algorithm. Int J Prod Res 47(21):6019–6036

    Article  Google Scholar 

  25. Huang Y, Ming W, Guo J, Zhang Z, Liu G, Li M, Zhang G (2013) Optimization of cutting conditions of YG15 on rough and finish cutting in WEDM based on statistical analyses. Int J Adv Manuf Technol 69(5–8):993–1008

    Article  Google Scholar 

  26. Zhang G, Patuwo BE, Hu MY (1998) Forecasting with artificial neural networks: the state of the art. Int J Forecast 14(1):35– 62

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Electromechanical Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450002, China

    Wuyi Ming & Junjian Hou

  2. State Key Lab of Digital Manufacturing Equipment & Technology, School of Mechanical Science and Engineering, Huazhong University of Science & Technology, Wuhan, 430074, China

    Zhen Zhang, Hao Huang, Zhong Xu, Guojun Zhang & Yu Huang

  3. Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, 61801, IL, USA

    Zhen Zhang

Authors
  1. Wuyi Ming
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  2. Junjian Hou
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  3. Zhen Zhang
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  4. Hao Huang
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  5. Zhong Xu
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  6. Guojun Zhang
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  7. Yu Huang
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Correspondence to Zhen Zhang.

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Ming, W., Hou, J., Zhang, Z. et al. Integrated ANN-LWPA for cutting parameter optimization in WEDM. Int J Adv Manuf Technol 84, 1277–1294 (2016). https://doi.org/10.1007/s00170-015-7777-8

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  • DOI: https://doi.org/10.1007/s00170-015-7777-8

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