Integrating Artificial Intelligence for Real-time Quality Control in the Production of Polymer Nanocomposites with Bio-Based Components

EasyChair Preprint 14518

Abstract

The integration of Artificial Intelligence (AI) in real-time quality control presents a transformative approach to the production of polymer nanocomposites, particularly those incorporating bio-based components. This paper explores the application of AI-driven techniques to enhance the precision, efficiency, and consistency of the manufacturing process. By leveraging advanced machine learning algorithms and computer vision systems, real-time monitoring and control of critical parameters such as material composition, temperature, and processing conditions can be achieved. These AI systems can detect deviations from desired quality standards instantaneously, allowing for immediate corrective actions, thereby minimizing waste and ensuring high-quality output. The study also investigates the challenges and potential solutions in implementing AI for quality control in the context of sustainable, bio-based polymer nanocomposites, emphasizing the importance of integrating explainable AI models for better decision-making and risk management. The findings demonstrate that AI-driven quality control not only improves product performance and reliability but also contributes to more sustainable manufacturing practices by reducing material consumption and energy usage.

Keyphrases: Artificial Intelligence, Real-time Quality Control, polymer nanocomposites

@booklet{EasyChair:14518,
  author    = {Abey Litty},
  title     = {Integrating Artificial Intelligence for Real-time Quality Control in the Production of Polymer Nanocomposites with Bio-Based Components},
  howpublished = {EasyChair Preprint 14518},
  year      = {EasyChair, 2024}}