Title: Performance enhancement of electrochemical honing process using ANN approach for bevel gear finishing

Authors: Javed Habib Shaikh; Neelesh Kumar Jain; Sunil Pathak

Addresses: Mechanical Engineering, JSPM Narhe Technical Campus Pune, India Survey No. 12/2/2 & 14/9, Off Mumbai Pune Bypass Road, Narhe, Pune, Maharashtra 411041, India ' Discipline of Mechanical Engineering, Indian Institute of Technology Indore (MP), India; 113/2B, PACL Campus, Indore-Mhow Road, Indore 453 446, MP, India ' Discipline of Mechanical Engineering, Indian Institute of Technology Indore (MP), India; 113/2B, PACL Campus, Indore-Mhow Road, Indore 453 446, MP, India

Abstract: This paper reports on performance enhancement of electrochemical honing (ECH) through its multi-performance optimisation for finishing the bevel gears. Implicit nature of ECH, complex interactions among its process parameters and conflicting objectives makes the multi-performance optimisation very challenging. In such cases, soft-computing tools such as artificial neural network (ANN) are found to be very effective. In this work, multi-performance optimisation of five important ECH parameters (namely concentration, temperature and flow rate of the electrolyte, rotary speed of the workpiece gear and voltage) was performed by developing back-propagation neural network (BPNN) and multiple regression models of percentage improvement in average and maximum surface roughness and MRR. The experiments were conducted using Taguchi's L₂₇(3¹³) orthogonal array to generate the experimental data required for the models. The optimised results were validated through confirmation experiments. The BPNN-based models were found very effective and superior to regression models for the multi-performance optimisation. Use of optimal values of the ECH parameters yielded better surface finish and productivity of the gears.

Keywords: ECH; electrochemical honing; bevel gears; multi-performance optimisation; BPNN; back-propagation neural networks; regression analysis; surface finish; MRR; material removal rate; bevel gear finishing; surface roughness; surface quality; Taguchi methods; orthogonal arrays.

DOI: 10.1504/IJPTECH.2015.070640

International Journal of Precision Technology, 2015 Vol.5 No.2, pp.157 - 169

Received: 24 Sep 2014
Accepted: 16 May 2015
Published online: 15 Jul 2015 *

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