Advances in Polymer-Modified Concrete using XAI

Year : 2025 | Volume : 13 | Special Issue 05 | Page : 133 144
    By

    Shalini Puri,

  • Anjali Dadhich,

  1. Associate Professor, Department of Information Technology, Manipal University Jaipur, Rajasthan, India
  2. Assistant Professor, Department of Management Studies, Bharati Vidyapeeth Deemed to be University, Off Campus, Pune, Maharashtra, India

Abstract

Industry 4.0 technologies are being quickly adopted by the construction sector, opening new avenues for enduring operational and environmental issues. This sector looks at how explainable AI can forecast air and enhance the quality of building materials. XAI, AI, ML, and big data drive a new paradigm in polymeric material development. The effective XAI and ML-assisted design creates innovative, high-performance polymeric materials. It covers building a database and representing structures, creating a model for predicting properties based on XAI and ML, creating a virtual design, and a high-throughput system. Training ML models that identify structure and material properties from available polymer data is essential because it makes it possible to ensure that promising polymers meet the desired property requirements. So, the main concern of this study is the use of XAI and machine learning to address these needs and their related problems. This study examines the use of XAI approaches in sustainable structural materials optimization in PMC and PCC to ensure that concrete construction projects for buildings have no adverse environmental effects. It describes various XAI-PMC models from 2021 to 2025 and compares them based on several parameters. Further, it provides analytical results based on these existing XAI-PMC models, including analysis on existing research contributions using XAI/AI techniques, year-wise research contributions and progress, and %usage of classifiers in existing XAI-PMC models

Keywords: ML, XAI-PMC, compressive strength, industry innovation, sustainable economic growth, productivity growth, machining technologies, concrete technology, sustainable manufacturing

[This article belongs to Special Issue under section in Journal of Polymer and Composites (jopc)]

How to cite this article:
Shalini Puri, Anjali Dadhich. Advances in Polymer-Modified Concrete using XAI. Journal of Polymer and Composites. 2025; 13(05):133-144.
How to cite this URL:
Shalini Puri, Anjali Dadhich. Advances in Polymer-Modified Concrete using XAI. Journal of Polymer and Composites. 2025; 13(05):133-144. Available from: https://journals.stmjournals.com/jopc/article=2025/view=222446


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Special Issue Subscription Review Article
Volume 13
Special Issue 05
Received 05/05/2025
Accepted 19/06/2025
Published 17/07/2025
Publication Time 73 Days
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