USING AI TO DEVELOP AN OPTIMAL MANUFACTURING PROCESS FOR ELECTRONICS
Keywords:
Artificial Intelligence Manufacturing, Process Optimization, Quality Control, Smart Manufacturing, Decision Support SystemsAbstract
This article examines the transformative impact of artificial intelligence on electronics manufacturing processes and decision-making strategies. The article explores how AI systems optimize key manufacturing parameters including first pass yield, test coverage, cycle time, and cost of quality while revolutionizing supply chain management and quality control. The article analyzes the integration of historical data with real-time processing capabilities, demonstrating how AI-driven systems enhance batch size optimization, material selection, and production planning. Through comprehensive analysis of implementation cases across multiple manufacturing sectors, the research highlights AI's role in improving operational efficiency, reducing costs, and enhancing product quality while maintaining high order fulfillment rates and customer satisfaction levels. The article indicates that AI integration in manufacturing processes not only optimizes current operations but also provides predictive insights for strategic decision-making and future planning
References
Rakesh Kumar "AI-Driven Innovations in Electronics Manufacturing," OEM Secrets, 6 December 2024. [Online]. Available: https://www.oemsecrets.com/articles/ai-driven-innovations-in-electronics-manufacturing
Vinit Parida et al. "Artificial intelligence implementation in manufacturing SMEs: A resource orchestration approach," Journal of Manufacturing Systems, August 2024. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S026840122400029X
Luis M Molina "AI-enabled smart manufacturing boosts ecosystem value capture: The importance of servitization pathways within digital-intensive industries," International Journal of Production Economics, 2024. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0925527324002688
Siby Jose Plathottam, "A review of artificial intelligence applications in manufacturing operations," AIChE Journal of Advanced Manufacturing and Processing, 16 May 2023. [Online]. Available: https://aiche.onlinelibrary.wiley.com/doi/full/10.1002/amp2.10159
Javier Carinena et al "AI in Manufacturing: How the Technology is Poised to Revolutionize the Industry and its Players," Kearney Research Report, 9 December 2024. [Online]. Available: https://www.kearney.com/service/operations-performance/article/ai-in-manufacturing-how-the-technology-is-poised-to-revolutionize-the-industry-and-its-players
Robert X Gao et al., "Artificial Intelligence in Advanced Manufacturing: Current Status and Future Outlook," ASME Journal of Manufacturing Science and Engineering, November 2020. [Online]. Available: https://asmedigitalcollection.asme.org/manufacturingscience/article/142/11/110804/1085487/Artificial-Intelligence-in-Advanced-Manufacturing
Robert X Gao et al, "Artificial Intelligence in manufacturing: State of the art, perspectives, and future directions," International Journal of Production Economics, 2020. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S000785062400115X
Mohsen Soori et al., "AI-Based Decision Support Systems in Industry 4.0, A Review," Smart Manufacturing Research, 28 August 2024. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2949948824000374
Chao Liu et al., "Leveraging AI for energy-efficient manufacturing systems: Review and future prospectives," Journal of Manufacturing Systems, February 2025. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0278612524002711
Vispi Karkaria et al, "An optimization-centric review on integrating artificial intelligence and digital twin technologies in manufacturing," Engineering Optimization, 3 January 2025. [Online]. Available: https://www.tandfonline.com/doi/full/10.1080/0305215X.2024.2434201?src=#d1e141