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Optimization of backpropagation neural network-based models in EDM process using particle swarm optimization and simulated annealing algorithms

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Abstract

In the present study, artificial neural network (ANN) along with heuristic algorithms, namely particle swarm optimization (PSO) and simulated annealing (SA), has been employed to carry out the modeling and optimization procedure of electrical discharge machining (EDM) process on AISI2312 hot worked steel parts. Surface roughness (SR), tool wear rate (TWR) and material removal rate (MRR) are the process quality measures considered as process output characteristics. Determination of a process variables (pulse on and off time, current, voltage and duty factor) combination to minimize TWR and SR and maximize MRR independently (as single objective) and also simultaneously (as multi-criteria) optimization is the main objective of this study. The experimental data are gathered using Taguchi L36 orthogonal array based on design of experiments approach. Next, the output measures are used to develop the ANN model. Furthermore, the architecture of the ANN has been modified using PSO algorithm. At the last step, in order to determine the best set of process output variables values for a desired set of process quality measures, the developed ANN model is embedded into proposed heuristic algorithms (SA and PSO) with which their derived results have been compared. It is evident that the proposed optimization procedure is quite efficient in modeling (with less than 1% error) and optimization (less than 4 and 7 percent error for single- and multi-objective optimizations, respectively) of EDM process variables.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Khayyam University of Mashhad, Mashhad, Iran

    Ali Saffaran

  2. Department of Mechanical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

    Masoud Azadi Moghaddam & Farhad Kolahan

Authors
  1. Ali Saffaran
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  2. Masoud Azadi Moghaddam
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  3. Farhad Kolahan
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Correspondence to Masoud Azadi Moghaddam.

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Technical Editor: Lincoln Cardoso Brandao.

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Saffaran, A., Azadi Moghaddam, M. & Kolahan, F. Optimization of backpropagation neural network-based models in EDM process using particle swarm optimization and simulated annealing algorithms. J Braz. Soc. Mech. Sci. Eng. 42, 73 (2020). https://doi.org/10.1007/s40430-019-2149-1

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  • DOI: https://doi.org/10.1007/s40430-019-2149-1

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