Optimization of waterjet paint removal operation using artificial neural network

Alzaghir, Abdullah Faisal and Mohd Nazir, Mat Nawi and Asmelash, Mebrahitom Asmelash and Azmir, Azhari (2022) Optimization of waterjet paint removal operation using artificial neural network. In: Lecture Notes in Electrical Engineering; Innovative Manufacturing, Mechatronics and Materials Forum, iM3F 2021 , 20 September 2021 , Gambang. pp. 11-20., 900 (277979). ISSN 1876-1100 ISBN 978-981192094-3

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Paint removal of automotive parts without environmental effects has become a critical issue around the world. The high pressure waterjet technology has received a wider acceptance for various applications involving machining, cleaning, surface treatment and material cutting. It offers an advantage to remove the automotive paint due to its superior environmental benefits over mechanical cleaning methods. Therefore, it is important to predict the waterjet cleaning process for a successful application for the paint removal in the automotive industry. In the present work, ANN model was used to predict the surface roughnes after the paint removel process of automotive component using the waterjet cleaning operation. A response surface methodology approach was employed to develop the experimental design involving the first order model and the second order model of central composite design. Into training and testing, a back-propagation algorithm used in the ANN model has successfully predicted the surface roughness with an average of 80% accuracy and 3.02 mean square error. This summarizes that ANN model can sufficiently estimate surface roughness in waterjet paint removal process with a reasonable error range.

Item Type: Conference or Workshop Item (Lecture)
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Artificial neural network; Multiple jet passes; Paint removal; Surface roughness; Waterjet cleaning
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TJ Mechanical engineering and machinery
T Technology > TK Electrical engineering. Electronics Nuclear engineering
T Technology > TS Manufactures
Faculty/Division: Institute of Postgraduate Studies
College of Engineering
Faculty of Manufacturing and Mechatronic Engineering Technology
Depositing User: Mr Muhamad Firdaus Janih@Jaini
Date Deposited: 01 Dec 2023 04:00
Last Modified: 01 Dec 2023 04:00
URI: http://umpir.ump.edu.my/id/eprint/39462
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