Enhancing Customer Experience with Advanced Artificial Intelligence-Based Predictive Modeling of Degradation Behavior in Polymer Nanocomposites

EasyChair Preprint 14683

Abstract

The integration of advanced artificial intelligence (AI) techniques with predictive modeling of degradation behavior in polymer nanocomposites has the potential to revolutionize customer experience in various industries. This study explores the development of AI-driven predictive models that forecast the degradation behavior of polymer nanocomposites, enabling proactive maintenance, reduced downtime, and enhanced product performance. By leveraging machine learning algorithms and data analytics, the proposed approach predicts degradation patterns, identifies key factors influencing material durability, and optimizes nanocomposite design for improved customer satisfaction. The results of this research can be applied to various sectors, including aerospace, automotive, and healthcare, leading to increased efficiency, reduced costs, and superior product quality, ultimately enhancing customer experience.

Keyphrases: Artificial Intelligence, customer experience, degradation behavior, polymer nanocomposites, predictive modeling

@booklet{EasyChair:14683,
  author    = {Abill Robert},
  title     = {Enhancing Customer Experience with Advanced Artificial Intelligence-Based Predictive Modeling of Degradation Behavior in Polymer Nanocomposites},
  howpublished = {EasyChair Preprint 14683},
  year      = {EasyChair, 2024}}