Surface-mount device design cycle time reduction using hybrid predictive modeling and optimization algorithm

Ngo, Hea Choon and Chiah, Chin Lim and Hashim, Ummi Rabaah and Hasan, Mohd Hilmi (2025) Surface-mount device design cycle time reduction using hybrid predictive modeling and optimization algorithm. Bulletin of Electrical Engineering and Informatics, 14 (4). pp. 2889-2898. ISSN 2089-3191

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Abstract

This study develops a hybrid predictive and optimization model for surface-mount device (SMD) design, addressing the extended design cycle times in the semiconductor industry caused by high computational demands. Challenges are tackled effectively through integration of convolutional neural network (CNN) for high-accuracy predictions and simulated annealing (SA) algorithm for optimization of SMD physical parameters. CNN model that trained on Monte Carlo simulation (MCS) data, achieved a predictive accuracy of 99.91% in forecasting SMD design errors. Concurrently, SA algorithm refined design parameters and substantially reducing error rates to nearly zero after 800 iterations. Our results indicate that combining predictive modeling with an optimization algorithm significantly enhances SMD design efficiency, providing a robust tool for mitigating time-to-market risks in semiconductor manufacturing.

Item Type:	Article
Uncontrolled Keywords:	Convolutional neural networks, Design optimization, Hybrid algorithm approach, Monte Carlo simulation, Predictive modeling, Simulated annealing
Divisions:	Faculty of Artificial Intelligence and Cyber Security
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	17 Jul 2026 08:04
Last Modified:	17 Jul 2026 08:04
URI:	http://eprints.utem.edu.my/id/eprint/29995
Statistic Details:	View Download Statistic

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