ISSN : 2583-2646

AI-Driven Transformation in Furniture Production: Enhancing Supply Chains, Design, and Waste Reduction

ESP Journal of Engineering & Technology Advancements
© 2025 by ESP JETA
Volume 5  Issue 1
Year of Publication : 2025
Authors : Pratik Dahule
:10.56472/25832646/JETA-V5I1P109

Citation:

Pratik Dahule, 2025. "AI-Driven Transformation in Furniture Production: Enhancing Supply Chains, Design, and Waste Reduction", ESP Journal of Engineering & Technology Advancements  5(1): 80-84.

Abstract:

The integration of Artificial Intelligence (AI) in project management has emerged as a disruptive paradigm, reshaping traditional methodologies and operational frameworks across various industries. Among these, the furniture manufacturing sector presents a compelling case for AI adoption due to its intricate production processes,dynamic supply chain dependencies, and the growing demand for customization. This paper delves into the multifaceted role of AI in optimizing project planning, resource allocation, workflow automation, and inventory management within furniture manufacturing. By harnessing advanced machine learning algorithms, predictive analytics, and intelligent automation, AI-driven systems enhance decision-making precision, mitigate inefficiencies,and foster adaptive strategies that respond to real-time operational constraints. The study further investigates the impact of AI on streamlining production pipelines, from raw material procurement and quality assessment to final product assembly and distribution logistics.

References:

[1] P. Zhou, J. Li, and Y. He, "AI-based predictive maintenance for smart manufacturing,"Journal of Intelligent Manufacturing, vol. 29, no. 5, pp. 1153-1165, 2018.

[2] A. K. Parlikad, L. Macchi, and J. Redding, "Digital twin in manufacturing: An architectural framework for design and implementation," in Proc. IEEE Int. Conf. Ind. Eng. Appl. Manuf. Syst., 2019, pp. 1-6.

[3] T. Stock and G. Seliger, "Opportunities of sustainable manufacturing in Industry 4.0," Procedia CIRP, vol. 40, pp. 536-541, 2016.

[4] Y. Xu, C. Wu, and L. Zhang, "Artificial Intelligence in Smart Manufacturing: Challenges and Future Directions," IEEE Trans. Ind. Informat., vol. 17, no. 5, pp. 3010-3020, May 2021.

[5] M. Shahin, "AI and Internet of Things (IoT) in Smart Manufacturing," Journal of Manufacturing Systems, vol. 47, pp. 53-68, 2018.

[6] H. M. Hashemian, "AI-based quality control systems in manufacturing," IEEE Trans. Autom. Sci. Eng., vol. 16, no. 3, pp. 1287-1295, July 2019.

[7] A. Bartodziej, The Concept Industry 4.0: An Empirical Analysis of Technologies and Applications in Production Logistics, Springer, 2017.

[8] J. Lee, H. Kao, and S. Yang, "Service innovation and smart analytics for Industry 4.0 and big data environment," Procedia CIRP, vol. 16, pp. 3-8, 2014.

[9] L. Wang and A. Kusiak, "Predictive modeling and optimization for manufacturing systems: A review," Journal of Manufacturing Science and Engineering, vol. 136, no. 1, pp. 1-12, 2014.

[10] K. Siau and W. Wang, "Artificial Intelligence (AI) Ethics: A Review of AI Governance and Ethical Issues," IEEE Trans. Eng. Manag., vol. 67, no. 3, pp. 715-725, 2020.

[11] R. Baheti and H. Gill, "Cyber-physical systems," The Impact of Control Technology, vol. 12, no. 1, pp. 161-166, 2011.

[12] G. Schuh, T. Potente, and A. Hauptvogel, "Methodology for increasing production efficiency by using cyber-physical systems," Procedia CIRP, vol. 17, pp. 178-183, 2014.

[13] N. Jazdi, "Cyber Physical Systems in the context of Industry 4.0," in Proc. IEEE Int. Conf. Autom., Qual. Testing, Robot., 2014, pp. 1-4.

[14] M. Rüßmann, M. Lorenz, P. Gerbert, and M. Waldner, "Industry 4.0: The future of productivity and growth in manufacturing industries," Boston Consulting Group Report, 2015.

[15] K. He, L. Sun, and Y. Jiang, "AI-Powered Predictive Analytics for Smart Factories: A Case Study in Automotive Manufacturing," IEEE Access, vol. 8, pp. 10986-10995, 2020.

[16] J. Qin, Y. Liu, and R. Grosvenor, "A Categorical Framework of Manufacturing for Industry 4.0 and Beyond," IEEE Trans. Ind. Informat., vol. 13, no. 4, pp. 1897-1905, Aug. 2017.

[17] Pratik Dahule, Shubham Sawant, 2024. "Beyond Boundaries: Integrating Financial and Utility Systems for Industry-Wide Transformation " ESP International Journal of Advancements in Science & Technology (ESP-IJAST) Volume 3, Issue 1: 44-50.

[18] P. Michelberger, G. Harsanyi, and K. Tucci, "Artificial Intelligence in Digital Twins for Smart Factories," in Proc. IEEE Int. Conf. Smart Manuf. Tech., 2021, pp. 67-72.

[19] B. Huang, J. Tan, and C. Chen, "Deep Learning in Predictive Maintenance: A Survey," IEEE Trans. Ind. Electron., vol. 69, no. 6, pp. 5615-5626, June 2022.

Keywords:

Artificial Intelligence, Machine Learning, Project Management, Furniture Manufacturing, Smart Manufacturing, AI Optimization, Industrial Automation.