Artificial Intelligence Optimization of Processing Parameters in Nanocomposite Manufacturing

EasyChair Preprint 14577

Abstract

The manufacturing of nanocomposites poses significant challenges due to the complex interplay of processing parameters, which can significantly impact the final product's properties. Artificial intelligence (AI) offers a promising solution to optimize these parameters, leading to improved product quality and reduced production costs. This study explores the application of AI techniques, including machine learning and deep learning, to optimize processing parameters in nanocomposite manufacturing. By analyzing data from various processing conditions, AI algorithms can identify optimal parameter combinations, predict product properties, and adapt to new materials and processes. The results demonstrate the potential of AI to revolutionize nanocomposite manufacturing by enhancing product performance, reducing trial-and-error approaches, and enabling real-time process control. This research contributes to the development of intelligent nanocomposite manufacturing systems, paving the way for innovative applications in various industries.

Keyphrases: Artificial Intelligence, Nanocomposite Manufacturing, Optimization

@booklet{EasyChair:14577,
  author    = {Abey Litty},
  title     = {Artificial Intelligence Optimization of Processing Parameters in Nanocomposite Manufacturing},
  howpublished = {EasyChair Preprint 14577},
  year      = {EasyChair, 2024}}