Title: Prediction of life of piercing punches using artificial neural network and adaptive neuro fuzzy inference systems

Authors: Sachin Salunkhe; D. Rajamani; Esakki Balasubramanian; U. Chandrasekhar

Addresses: Department of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala, R&D Institute of Science and Technology, Chennai, 600062, India ' Department of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala, R&D Institute of Science and Technology, Chennai, 600062, India ' Department of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala, R&D Institute of Science and Technology, Chennai, 600062, India ' Department of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala, R&D Institute of Science and Technology, Chennai, 600062, India

Abstract: Predicting the life of piercing punch is one of the major concerns in the design of compound dies. Finite element analysis is performed to determine the maximum and minimum principal stresses through which fatigue limit of punch is estimated. The factors affecting the life of punch are examined and a mathematical model is established using artificial neural network (ANN) and adaptive neuro fuzzy inference systems (ANFIS). The developed model is utilised to evaluate the life of punch for varied load conditions. Comparative evaluation of ANN and ANFIS results suggested that the later model is superior in predicting the life of punch and it can be effectively utilised in machine tool applications.

Keywords: piercing punch; compound die; finite element analysis; artificial neural network; ANN; adaptive neuro fuzzy inference systems; ANFIS.

DOI: 10.1504/IJMATEI.2019.10019116

International Journal of Materials Engineering Innovation, 2019 Vol.10 No.1, pp.20 - 33

Received: 23 Jan 2018
Accepted: 18 May 2018

Published online: 22 Feb 2019 *

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