Journal of Polymer & Composites Review Article
AI-Driven Sustainable Supply Chain Framework for Polymer Composite Production
Abstract
As polymer composite processes become more difficult and environmental concerns increase, old supply chain models that just look at cost and operations have shown significant weaknesses when it comes to sustainability. The rising demand for environmentally friendly practices throughout a product’s life cycle requires a new process that makes sustainability a key element in making supply chain choices. The proposed framework was developed in response to this need by using AI to support sustainable supply chain management in the polymer composite sector and includes strong environmentally focused elements throughout the process. The proposed framework is structured into five interdependent layers, encompassing real-time data acquisition, sustainability-embedded predictive modeling, multi-objective optimization, adaptive feedback monitoring, and automated sustainability assessment. It seeks to replace traditional, budget-focused supply chains with clever, flexible, and green options. Applying advanced AI to the handling of materials' life cycles, the framework assists organizations in better managing environmental problems, maximizing resources, and making their operations follow circular economy theories. The benefits of using the framework can be improved operational sustainability, major cuts in carbon emissions, an increase in material recycling, and compliance with anticipated global sustainability rules. The model is recommended for use and refinement by industrial practitioners, members of academia, policymakers, and system developers. Adding AI into the supply of composite materials greatly contributes to the goal of having intelligent, flexible, and sustainable industrial systems.
Keywords
References (31)
- Oladele IO, Omotosho TF, Adediran AA. Polymer-Based Composites: An Indispensable Material for Present and Future Applications. International Journal of Polymer Science. 2020;2020:1-12. doi:10.1155/2020/8834518
- Chhipa SM, Sharma S, Kumar Bagha A. Recent development in polymer coating to prevent corrosion in metals: A review. Materials Today: Proceedings. 2024. doi:10.1016/j.matpr.2024.09.001
- Zaman AU, Gutub SA, Soliman MF, Wafa MA. Sustainability and human health issues pertinent to fibre reinforced polymer composites usage: A review. Journal of Reinforced Plastics and Composites. 2014;33(11):1069-1084. doi:10.1177/0731684414521087
- Drechsler K, Heine M, Mitschang P. 12.1 Carbon Fiber Reinforced Polymers*. Industrial Carbon and Graphite Materials, Volume I. 2021:697-739. doi:10.1002/9783527674046.ch12_1
- Nzimande MC, Mtibe A, Tichapondwa S, John MJ. A Review of Weathering Studies in Plastics and Biocomposites—Effects on Mechanical Properties and Emissions of Volatile Organic Compounds (VOCs). Polymers. 2024;16(8):1103. doi:10.3390/polym16081103
- Morici E, Dintcheva NT. Recycling of Thermoset Materials and Thermoset-Based Composites: Challenge and Opportunity. Polymers. 2022;14(19):4153. doi:10.3390/polym14194153
- Jha S, Akula B, Enyioma H, Novak M, Amin V, Liang H. Biodegradable Biobased Polymers: A Review of the State of the Art, Challenges, and Future Directions. Polymers. 2024;16(16):2262. doi:10.3390/polym16162262
- Koumoulos E, Trompeta AF, Santos RM, Martins M, Santos C, Iglesias V, et al. Research and Development in Carbon Fibers and Advanced High-Performance Composites Supply Chain in Europe: A Roadmap for Challenges and the Industrial Uptake. Journal of Composites Science. 2019;3(3):86. doi:10.3390/jcs3030086
- Uddin MH, Mulla MH, Abedin T, Manap A, Yap BK, Rajamony RK, et al. Advances in natural fiber polymer and PLA composites through artificial intelligence and machine learning integration. Journal of Polymer Research. 2025;32(3). doi:10.1007/s10965-025-04282-7
- Karuppusamy M, Thirumalaisamy R, Palanisamy S, et al. A review of machine learning applications in polymer composites: advancements, challenges, and future prospects. J Mater Chem A. Forthcoming 2025.
- Nasrin T, Pourkamali‐Anaraki F, Peterson AM. Application of machine learning in polymer additive manufacturing: A review. Journal of Polymer Science. 2023;62(12):2639-2669. doi:10.1002/pol.20230649
- Hasan MR, Khan MA, Wuest T. Towards Industry 5.0: A Systematic Literature Review on Sustainable and Green Composite Materials Supply Chains. arXiv. 2024. doi:10.48550/arXiv.2402.06100.
- Singh PK. Digital transformation in supply chain management: Artificial Intelligence (AI) and Machine Learning (ML) as Catalysts for Value Creation. Int J Supply Chain Manag. 2023; 12(6): 57-63p.
- Rolf B, Jackson I, Müller M, Lang S, Reggelin T, Ivanov D. A review on reinforcement learning algorithms and applications in supply chain management. International Journal of Production Research. 2022;61(20):7151-7179. doi:10.1080/00207543.2022.2140221
- Mohanty AK, Wu F, Mincheva R, Hakkarainen M, Raquez JM, Mielewski DF, et al. Sustainable polymers. Nature Reviews Methods Primers. 2022;2(1). doi:10.1038/s43586-022-00124-8
- Saeed MA, Kersten W. Drivers of Sustainable Supply Chain Management: Identification and Classification. Sustainability. 2019;11(4):1137. doi:10.3390/su11041137
- Ferdous J, Bensebaa F, Milani AS, Hewage K, Bhowmik P, Pelletier N. Development of a Generic Decision Tree for the Integration of Multi-Criteria Decision-Making (MCDM) and Multi-Objective Optimization (MOO) Methods under Uncertainty to Facilitate Sustainability Assessment: A Methodical Review. Sustainability. 2024;16(7):2684. doi:10.3390/su16072684
- Palazzo J, Geyer R, Suh S. A review of methods for characterizing the environmental consequences of actions in life cycle assessment. Journal of Industrial Ecology. 2020;24(4):815-829. doi:10.1111/jiec.12983
- Zhou X, Li T, Ma X. A bibliometric analysis of comparative research on the evolution of international and Chinese green supply chain research hotspots and frontiers. Environmental Science and Pollution Research. 2021;28(6):6302-6323. doi:10.1007/s11356-020-11947-x
- Olawumi MA, Oladapo BI, Olugbade TO, Omigbodun FT, Olawade DB. AI-Driven Data Analysis of Quantifying Environmental Impact and Efficiency of Shape Memory Polymers. Biomimetics. 2024;9(8):490. doi:10.3390/biomimetics9080490
- Paraye P, Sarviya RM. Advances in polymer composites, manufacturing, recycling, and sustainable practices. Polymer-Plastics Technology and Materials. 2024;63(11):1474-1497. doi:10.1080/25740881.2024.2339295
- Khalid MY, Arif ZU, Ahmed W, Arshad H. Recent trends in recycling and reusing techniques of different plastic polymers and their composite materials. Sustainable Materials and Technologies. 2022;31:e00382. doi:10.1016/j.susmat.2021.e00382
- Kaur G, Kander R. System Dynamics for Manufacturing: Supply Chain Simulation of Hemp-Reinforced Polymer Composite Manufacturing for Sustainability. Sustainability. 2025;17(2):765. doi:10.3390/su17020765
- Aminabadi SS, Tabatabai P, Steiner A, Gruber DP, Friesenbichler W, Habersohn C, et al. Industry 4.0 In-Line AI Quality Control of Plastic Injection Molded Parts. Polymers. 2022;14(17):3551. doi:10.3390/polym14173551
- Yaghoubi V, Kumru B. Retrosynthetic Life Cycle Assessment: A Short Perspective on the Sustainability of Integrating Thermoplastics and Artificial Intelligence Into Composite Systems. Advanced Sustainable Systems. 2024;8(5). doi:10.1002/adsu.202300543
- Kamble SS, Gunasekaran A, Parekh H, Mani V, Belhadi A, Sharma R. Digital twin for sustainable manufacturing supply chains: Current trends, future perspectives, and an implementation framework. Technological Forecasting and Social Change. 2022;176:121448. doi:10.1016/j.techfore.2021.121448
- Preethikaharshini J, Naresh K, Rajeshkumar G, Arumugaprabu V, Khan MA, Khan KA. Review of advanced techniques for manufacturing biocomposites: non-destructive evaluation and artificial intelligence-assisted modeling. Journal of Materials Science. 2022;57(34):16091-16146. doi:10.1007/s10853-022-07558-1
- Zhao Y, Mulder RJ, Houshyar S, et al. A review on the application of molecular descriptors and machine learning in polymer design. Polym Chem. 2023; 14(29): 3325-46p.
- Alexander A, Delabre I. Linking sustainable supply chain management with the sustainable development goals: Indicators, scales and substantive impacts. In: Sustainable development goals and sustainable supply chains in the post-global economy. 2019. 95-111p.
- Mengesha G. Advances in Composite Structures: A Systematic Review of Design, Performance, and Sustainability Trends. Performance, and Sustainability Trends. 2025 Jan 10.
- Amon F, Dahlbom S, Blomqvist P. Challenges to transparency involving intellectual property and privacy concerns in life cycle assessment/costing: A case study of new flame retarded polymers. Cleaner Environmental Systems. 2021;3:100045. doi:10.1016/j.cesys.2021.100045