Artificial Intelligence in Nanomanufacturing for Optimizing Design, Fabrication, and Quality Control

Résumé fourni par la source

Together with nanomanufacturing, Digital Manufacturing (DM) is going to set the cutting edge for Industry 4.0, the fourth industrial revolution, as it enables the processing of materials over many dimensions of length. This overview outlines the development of nanomaterials and nanomanufacturing in the digital era, including use cases in consumer electronics, robotics, medical, sensory technologies, and semiconductors. It has also discussed the prospects of possible applications of complex AI algorithms, including expandable artificial intelligence (XAI), reinforced learning, and big data analytics in materials synthesis, innovation in industrial processes, and nanosystem integration. This work provides a thorough assessment of an amalgamation of AI in nanomanufacturing processes, thereby addressing a substantial gap in the field. The challenges of applying machine learning and deep learning to produce reliable and accurate predictions are explained in detail. This chapter examines how AI continues to evolve nanomanufacturing in Industry 4.0 through a thorough assessment, case studies, and data analysis. A detailed literature review is conducted to accumulate existing knowledge on nanomanufacturing, DM, and AI technologies. It also focuses on how AI may improve quality control and process control, including material synthesis in the nanomanufacturing industry. Additionally, it shows how AI may boost market relevance and competitiveness by lowering costs, speeding up time to market, alongside improving product quality. As a result, it provides key knowledge for businesses looking to improve and grow their production capacity.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.