Application of Artificial Neuron Network in Roughness Prediction: A Case Study in Turning of Stainless Steel

Open Access

Year : 2023 | Volume : | : | Page : –
By

Yogesh Navnath Jagdale,

Mandar Kirti Tambat,

Krushna Bhagvant Nemlekar,

Aditya Chandrashekhar Savekar,

Nalini Deepthi,

  1. Students, Saraswati College of Engineering, Navi Mumbai, Maharashtra, India
  2. Students, Saraswati College of Engineering, Navi Mumbai, Maharashtra, India
  3. Students, Saraswati College of Engineering, Navi Mumbai, Maharashtra, India
  4. Students, Saraswati College of Engineering, Navi Mumbai, Maharashtra, India
  5. Professor, Saraswati College of Engineering, Navi Mumbai, Maharashtra, India

Abstract

Artificial neural networks (ANNs) offer a practical and efficient way to choose the best machining parameters for the turning process to reduce surface roughness, the resulting cutting forces, and maximize tool life. Surface roughness is a significant aspect in the evaluation of cutting performance and plays a significant role in the manufacturing process. The goal of this project is to create a model based on an ANNs that can replicate hard turning of EN-19 steel with only a small amount of cutting fluid. In terms of cutting parameters, this model is meant to forecast the surface roughness. Following training with a set of training data for a specified number of cycles, various network topologies are assessed using input/output data sets specifically designated for this purpose. The root means the square error is determined for the selected architectures. Utilizing linear regression, the regression equation is established. By applying ANN to this equation, we can forecast the surface roughness of test data.

Keywords: Neuron network, artificial intelligence, linear regression, prediction of surface roughness

How to cite this article:
Yogesh Navnath Jagdale, Mandar Kirti Tambat, Krushna Bhagvant Nemlekar, Aditya Chandrashekhar Savekar, Nalini Deepthi. Application of Artificial Neuron Network in Roughness Prediction: A Case Study in Turning of Stainless Steel. International Journal of Computer Aided Manufacturing. 2023; ():-.
How to cite this URL:
Yogesh Navnath Jagdale, Mandar Kirti Tambat, Krushna Bhagvant Nemlekar, Aditya Chandrashekhar Savekar, Nalini Deepthi. Application of Artificial Neuron Network in Roughness Prediction: A Case Study in Turning of Stainless Steel. International Journal of Computer Aided Manufacturing. 2023; ():-. Available from: https://journals.stmjournals.com/ijcam/article=2023/view=91491


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Open Access Article
Volume
Received 26/05/2022
Accepted 30/07/2022
Published 30/01/2023