Investigation on Prediction Capability of Artificial Neural Network on Responses of Wire Electro Discharge Machining

Hargovind Soni; P. M. Mashinini

doi:10.1007/978-981-15-9678-0_87

Investigation on Prediction Capability of Artificial Neural Network on Responses of Wire Electro Discharge Machining

Hargovind Soni
, P. M. Mashinini

Mechanical and Industrial Engineering Technology

University of Johannesburg

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Machining studies on wire electro discharge (WEDM) are performed on Ti₅₀Ni₄₉Co₁ shape memory alloy for the bone staple application in the present study. It has been observed that the input process parameters have highly influenced the machinability of the material. Hence, these two process parameters were selected for the study of surface roughness (Ra). Moreover, the experimental design is found with error difference between the simulated and experimentally predicted values. A biological trained data networking is used to calculate the simulated results with experimental data. The results are impressed and found very close to the experimental results. The study showed 8% maximum error during the comparative study.

Original language	English
Title of host publication	Recent Advances in Mechanical Engineering - Select Proceedings of RAME 2020
Editors	Anil Kumar, Amit Pal, Surendra Singh Kachhwaha, Prashant Kumar Jain
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	1045-1051
Number of pages	7
ISBN (Print)	9789811596773
DOIs	https://doi.org/10.1007/978-981-15-9678-0_87
Publication status	Published - 2021
Event	2nd International Conference on Recent Advances in Mechanical Engineering, RAME 2020 - Delhi, India Duration: 18 Sept 2020 → 19 Sept 2020

Publication series

Name	Lecture Notes in Mechanical Engineering
ISSN (Print)	2195-4356
ISSN (Electronic)	2195-4364

Conference

Conference	2nd International Conference on Recent Advances in Mechanical Engineering, RAME 2020
Country/Territory	India
City	Delhi
Period	18/09/20 → 19/09/20

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

Machining and neural network
TiNiCo
WEDM

ASJC Scopus subject areas

Automotive Engineering
Aerospace Engineering
Mechanical Engineering
Fluid Flow and Transfer Processes

Access to Document

10.1007/978-981-15-9678-0_87

Cite this

Soni, H., & Mashinini, P. M. (2021). Investigation on Prediction Capability of Artificial Neural Network on Responses of Wire Electro Discharge Machining. In A. Kumar, A. Pal, S. S. Kachhwaha, & P. K. Jain (Eds.), Recent Advances in Mechanical Engineering - Select Proceedings of RAME 2020 (pp. 1045-1051). (Lecture Notes in Mechanical Engineering). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-15-9678-0_87

Soni, Hargovind ; Mashinini, P. M. / Investigation on Prediction Capability of Artificial Neural Network on Responses of Wire Electro Discharge Machining. Recent Advances in Mechanical Engineering - Select Proceedings of RAME 2020. editor / Anil Kumar ; Amit Pal ; Surendra Singh Kachhwaha ; Prashant Kumar Jain. Springer Science and Business Media Deutschland GmbH, 2021. pp. 1045-1051 (Lecture Notes in Mechanical Engineering).

@inproceedings{b2ca5565ad7e423ca6d703fbff2b4069,

title = "Investigation on Prediction Capability of Artificial Neural Network on Responses of Wire Electro Discharge Machining",

abstract = "Machining studies on wire electro discharge (WEDM) are performed on Ti50Ni49Co1 shape memory alloy for the bone staple application in the present study. It has been observed that the input process parameters have highly influenced the machinability of the material. Hence, these two process parameters were selected for the study of surface roughness (Ra). Moreover, the experimental design is found with error difference between the simulated and experimentally predicted values. A biological trained data networking is used to calculate the simulated results with experimental data. The results are impressed and found very close to the experimental results. The study showed 8\% maximum error during the comparative study.",

keywords = "Machining and neural network, TiNiCo, WEDM",

author = "Hargovind Soni and Mashinini, \{P. M.\}",

note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 2nd International Conference on Recent Advances in Mechanical Engineering, RAME 2020 ; Conference date: 18-09-2020 Through 19-09-2020",

year = "2021",

doi = "10.1007/978-981-15-9678-0\_87",

language = "English",

isbn = "9789811596773",

series = "Lecture Notes in Mechanical Engineering",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "1045--1051",

editor = "Anil Kumar and Amit Pal and Kachhwaha, \{Surendra Singh\} and Jain, \{Prashant Kumar\}",

booktitle = "Recent Advances in Mechanical Engineering - Select Proceedings of RAME 2020",

address = "Germany",

}

Soni, H & Mashinini, PM 2021, Investigation on Prediction Capability of Artificial Neural Network on Responses of Wire Electro Discharge Machining. in A Kumar, A Pal, SS Kachhwaha & PK Jain (eds), Recent Advances in Mechanical Engineering - Select Proceedings of RAME 2020. Lecture Notes in Mechanical Engineering, Springer Science and Business Media Deutschland GmbH, pp. 1045-1051, 2nd International Conference on Recent Advances in Mechanical Engineering, RAME 2020, Delhi, India, 18/09/20. https://doi.org/10.1007/978-981-15-9678-0_87

Investigation on Prediction Capability of Artificial Neural Network on Responses of Wire Electro Discharge Machining. / Soni, Hargovind; Mashinini, P. M.
Recent Advances in Mechanical Engineering - Select Proceedings of RAME 2020. ed. / Anil Kumar; Amit Pal; Surendra Singh Kachhwaha; Prashant Kumar Jain. Springer Science and Business Media Deutschland GmbH, 2021. p. 1045-1051 (Lecture Notes in Mechanical Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Investigation on Prediction Capability of Artificial Neural Network on Responses of Wire Electro Discharge Machining

AU - Soni, Hargovind

AU - Mashinini, P. M.

PY - 2021

Y1 - 2021

N2 - Machining studies on wire electro discharge (WEDM) are performed on Ti50Ni49Co1 shape memory alloy for the bone staple application in the present study. It has been observed that the input process parameters have highly influenced the machinability of the material. Hence, these two process parameters were selected for the study of surface roughness (Ra). Moreover, the experimental design is found with error difference between the simulated and experimentally predicted values. A biological trained data networking is used to calculate the simulated results with experimental data. The results are impressed and found very close to the experimental results. The study showed 8% maximum error during the comparative study.

AB - Machining studies on wire electro discharge (WEDM) are performed on Ti50Ni49Co1 shape memory alloy for the bone staple application in the present study. It has been observed that the input process parameters have highly influenced the machinability of the material. Hence, these two process parameters were selected for the study of surface roughness (Ra). Moreover, the experimental design is found with error difference between the simulated and experimentally predicted values. A biological trained data networking is used to calculate the simulated results with experimental data. The results are impressed and found very close to the experimental results. The study showed 8% maximum error during the comparative study.

KW - Machining and neural network

KW - TiNiCo

KW - WEDM

UR - https://www.scopus.com/pages/publications/85111321832

U2 - 10.1007/978-981-15-9678-0_87

DO - 10.1007/978-981-15-9678-0_87

M3 - Conference contribution

AN - SCOPUS:85111321832

SN - 9789811596773

T3 - Lecture Notes in Mechanical Engineering

SP - 1045

EP - 1051

BT - Recent Advances in Mechanical Engineering - Select Proceedings of RAME 2020

A2 - Kumar, Anil

A2 - Pal, Amit

A2 - Kachhwaha, Surendra Singh

A2 - Jain, Prashant Kumar

PB - Springer Science and Business Media Deutschland GmbH

T2 - 2nd International Conference on Recent Advances in Mechanical Engineering, RAME 2020

Y2 - 18 September 2020 through 19 September 2020

ER -

Soni H, Mashinini PM. Investigation on Prediction Capability of Artificial Neural Network on Responses of Wire Electro Discharge Machining. In Kumar A, Pal A, Kachhwaha SS, Jain PK, editors, Recent Advances in Mechanical Engineering - Select Proceedings of RAME 2020. Springer Science and Business Media Deutschland GmbH. 2021. p. 1045-1051. (Lecture Notes in Mechanical Engineering). doi: 10.1007/978-981-15-9678-0_87

Investigation on Prediction Capability of Artificial Neural Network on Responses of Wire Electro Discharge Machining

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

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