Innovations in Marketing of Printed Circuit Board Assembly by Optimization Techniques for Enhanced Performance
Published 2024-12-02
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Keywords
- Marketing,
- Machine Learning Integration,
- Printed Circuit Board,
- Adaptive Optimization,
- Multi-Faceted Optimization
How to Cite
Copyright (c) 2024 International Journal of Industrial Engineering and Management
This work is licensed under a Creative Commons Attribution 4.0 International License.
Abstract
This study investigates novel digital marketing optimization methodologies tailored specifically for the Printed Circuit Board (PCB) assembly process, aiming to address existing challenges and inefficiencies. Through a comprehensive review of marketing strategies, we introduce innovative approaches designed to revolutionize production processes in PCB assembly. Focused on a specific optimization problem within PCB assembly, namely the placement and routing of components, we elucidate its intricacies and underscore the need for groundbreaking solutions to achieve marketing condition. Our research yields several significant innovations: (I) Integration of hybrid marketing techniques, combining optimization of particle swarm optimization with differential evolution, resulting in a notable 18% acceleration in convergence rates and marketing. (II) Adoption of machine learning methodologies, demonstrating a 22% reduction in optimization inaccuracies compared to conventional static configurations. (III) Emphasis on multi-faceted optimization objectives, leading to a remarkable 30% enhancement in balancing cost-efficiency trade-offs through dynamic Pareto-based marketing. (IV) Introduction of adaptive optimization algorithms capable of swiftly adapting to fluctuating production demands, thereby curtailing decision latency by an impressive 35%, which can enhance digital marketing.
Article history: Received (March 17, 2024); Revised (July 22, 2024); Accepted (August 15, 2024); Published online (September 25, 2024)