Proceedings of the 6th Mechanical Engineering, Science and Technology International conference (MEST 2022)

<Previous Article In Volume
Next Article In Volume>

Multi-objective Optimization of AISI 1045 on Drilling Process Based on Hybrid BPNN and Firefly Algorithm

Authors
Ridhani Anita Fajardini1, *, Mohammad Khoirul Effendi1, Bobby O. P. Soepangkat1, Mazwan1, Satrio Darma Utama1
1Department of Mechanical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, 60111, Indonesia
*Corresponding author. Email: ridhaniaf.id@gmail.com
Corresponding Author
Ridhani Anita Fajardini
Available Online 19 April 2023.
DOI
10.2991/978-94-6463-134-0_50How to use a DOI?
Keywords
BPNN-FA; Drilling; Thrust Force; Torque; Surface Roughness
Abstract

During the drilling process with minimum quantity lubrication (MQL) for AISI 1045, the thrust force and torque influence the drilled hole’s surface quality. Therefore, it is important to select the appropriate combination levels of machining parameters in order to minimize the thrust force, torque, and surface roughness of drilled holes simultaneously. This paper predicts the optimal value of thrust force, torque, and surface roughness of the AISI 1045 in the drilling process by implementing a hybrid method of backpropagation neural network (BPNN) and firefly algorithm (FA). BPNN was developed to obtain an appropriate model and then applied the firefly algorithm for multi-objective optimization. Several experiments on CNC machines were carried out using L18 orthogonal arrays based on the Taguchi technique. Tool type, point angle, feed rate, and cutting speed were selected as process parameters. Based on the prediction of BPNN and FA to achieve optimal responses, the cutting process was obtained using a tool type HSS-M2 with a point angle of 131°, feed rate of 0.04 mm/rev, and cutting speed of 32.5 m/min.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 6th Mechanical Engineering, Science and Technology International conference (MEST 2022)
Series
Advances in Engineering Research
Publication Date
19 April 2023
ISBN
978-94-6463-134-0
ISSN
2352-5401
DOI
10.2991/978-94-6463-134-0_50How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Ridhani Anita Fajardini
AU  - Mohammad Khoirul Effendi
AU  - Bobby O. P. Soepangkat
AU  - Mazwan
AU  - Satrio Darma Utama
PY  - 2023
DA  - 2023/04/19
TI  - Multi-objective Optimization of AISI 1045 on Drilling Process Based on Hybrid BPNN and Firefly Algorithm
BT  - Proceedings of the 6th Mechanical Engineering, Science and Technology International conference (MEST 2022)
PB  - Atlantis Press
SP  - 530
EP  - 540
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-134-0_50
DO  - 10.2991/978-94-6463-134-0_50
ID  - Fajardini2023
ER  -