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Machine Learning based Digital Twin Framework for Production Optimization in Petrochemical Industry

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  1. Danny Espín-Sarzosa & Rodrigo Palma-Behnke & Felipe Valencia-Arroyave, 2023. "Towards Digital Twins of Small Productive Processes in Microgrids," Energies, MDPI, vol. 16(11), pages 1-17, May.
  2. Mélanie Roux & Soumyadeb Chowdhury & Prasanta Kumar Dey & Emilia Vann Yaroson & Vijay Pereira & Amelie Abadie, 2025. "Small and medium-sized enterprises as technology innovation intermediaries in sustainable business ecosystem: interplay between AI adoption, low carbon management and resilience," Annals of Operations Research, Springer, vol. 355(2), pages 1537-1586, December.
  3. Lim, Kendrik Yan Hong & Dang, Le Van & Chen, Chun-Hsien, 2024. "Incorporating supply and production digital twins to mitigate demand disruptions in multi-echelon networks," International Journal of Production Economics, Elsevier, vol. 273(C).
  4. Genetti, Stefano & Scarton, Giorgio & Formentini, Marco & Iacca, Giovanni, 2026. "An intelligent Digital Twin based on machine learning for interpretable decision-making in manufacturing," International Journal of Production Economics, Elsevier, vol. 291(C).
  5. Francesco Pelella & Luca Viscito & Federico Magnea & Alessandro Zanella & Stanislao Patalano & Alfonso William Mauro & Nicola Bianco, 2023. "Comparison between Physics-Based Approaches and Neural Networks for the Energy Consumption Optimization of an Automotive Production Industrial Process," Energies, MDPI, vol. 16(19), pages 1-22, September.
  6. Zhiyuan Li & Xuesong Mei & Zheng Sun & Jun Xu & Jianchen Zhang & Dawei Zhang & Jingyi Zhu, 2025. "A reference framework for the digital twin smart factory based on cloud-fog-edge computing collaboration," Journal of Intelligent Manufacturing, Springer, vol. 36(5), pages 3625-3645, June.
  7. Liu, Yang & Jiang, Rui & Zhang, Yuan & Dai, Jingjing & Cheng, Jing, 2024. "Mitigating digital trade barriers: Strategies for enhancing national value chains performance," International Review of Economics & Finance, Elsevier, vol. 95(C).
  8. Saporiti, Nicolò & Cannas, Violetta Giada & Pozzi, Rossella & Rossi, Tommaso, 2023. "Challenges and countermeasures for digital twin implementation in manufacturing plants: A Delphi study," International Journal of Production Economics, Elsevier, vol. 261(C).
  9. Umashankar Samal, 2025. "Evolution of machine learning and deep learning in intelligent manufacturing: a bibliometric study," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 16(9), pages 3134-3150, September.
  10. Zhang, Chen & Li, Rongrong & Wang, Qiang, 2026. "Artificial intelligence and sustainable development: A global nonlinear analysis of the moderating roles of human capital and renewable energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 228(C).
  11. Danfeng Zhang & Xin Wang & Liang Zhao & Huaqing Xie & Chen Guo & Feizhou Qian & Hui Dong & Yun Hu, 2023. "Numerical Investigation on Heat Transfer and Flow Resistance Characteristics of Superheater in Hydrocracking Heat Recovery Steam Generator," Energies, MDPI, vol. 16(17), pages 1-15, August.
  12. Minna Saunila & Mina Nasiri & Juhani Ukko & Luca Gastaldi, 2025. "Managing Social Sustainability With IoT Implementation: An Industry 5.0 Perspective," Sustainable Development, John Wiley & Sons, Ltd., vol. 33(4), pages 5327-5335, August.
  13. Mustafa Musa Jaber & Mohammed Hassan Ali & Sura Khalil Abd & Mustafa Mohammed Jassim & Ahmed Alkhayyat & Ezzulddin Hasan Kadhim & Ahmed Rashid Alkhuwaylidee & Shahad Alyousif, 2023. "RETRACTED ARTICLE: AHI: a hybrid machine learning model for complex industrial information systems," Journal of Combinatorial Optimization, Springer, vol. 45(2), pages 1-22, March.
  14. Wan, Changfu & Li, Wenqiang & Yang, Bo & Ling, Sitong & Fu, Guozhong & Hong, Yida, 2025. "Digital Twin Model and Platform Based on a Dual System for Control Rod Drive Mechanism Safety," Reliability Engineering and System Safety, Elsevier, vol. 261(C).
  15. Carlos Andrés Mesa-Montoya & Néstor Iván Marín Peláez & Kevin David Ortega-Quiñones & German Andrés Holguín-Londoño & Libardo Vicente Vanegas-Useche & Gian Carlo Daraviña-Peña & Edwan Anderson Ariza-E, 2025. "Integration of a Digital Twin Framework for Trajectory Control of a 2RRR Planar Parallel Manipulator Using ROS/Gazebo and MATLAB," Future Internet, MDPI, vol. 17(4), pages 1-23, March.
  16. Jun Dong & A-Ru-Han Bao & Yao Liu & Xi-Hao Dou & Dong-Ran Liu & Gui-Yuan Xue, 2022. "Dynamic Differential Game Strategy of the Energy Big Data Ecosystem Considering Technological Innovation," Sustainability, MDPI, vol. 14(12), pages 1-24, June.
  17. Hanzhang Zhan & Bon‐Gang Hwang & Pramesh Krishnankutty, 2025. "Embracing digital transformation for sustainable development: Barriers to adopting digital twin in asset management within Singapore's energy and chemicals industry," Sustainable Development, John Wiley & Sons, Ltd., vol. 33(2), pages 2864-2887, April.
  18. Yu, Wei & Patros, Panos & Young, Brent & Klinac, Elsa & Walmsley, Timothy Gordon, 2022. "Energy digital twin technology for industrial energy management: Classification, challenges and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
  19. Alexandra I. Khalyasmaa & Alina I. Stepanova & Stanislav A. Eroshenko & Pavel V. Matrenin, 2023. "Review of the Digital Twin Technology Applications for Electrical Equipment Lifecycle Management," Mathematics, MDPI, vol. 11(6), pages 1-23, March.
  20. Amine Belhadi & Venkatesh Mani & Sachin S. Kamble & Syed Abdul Rehman Khan & Surabhi Verma, 2024. "Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: an empirical investigation," Annals of Operations Research, Springer, vol. 333(2), pages 627-652, February.
  21. Jiachao Peng & Hanfei Chen & Lei Jia & Shuke Fu & Jiali Tian, 2023. "Impact of Digital Industrialization on the Energy Industry Supply Chain: Evidence from the Natural Gas Industry in China," Energies, MDPI, vol. 16(4), pages 1-32, February.
  22. Alisha Lakra & Shubhkirti Gupta & Ravi Ranjan & Sushanta Tripathy & Deepak Singhal, 2022. "The Significance of Machine Learning in the Manufacturing Sector: An ISM Approach," Logistics, MDPI, vol. 6(4), pages 1-15, October.
  23. Benno Gerlach & Simon Zarnitz & Benjamin Nitsche & Frank Straube, 2021. "Digital Supply Chain Twins—Conceptual Clarification, Use Cases and Benefits," Logistics, MDPI, vol. 5(4), pages 1-24, December.
  24. Liu, Chunting & Liu, Ruyu & Liu, Xiufeng, 2026. "A digital twin framework for intelligent electric vehicle charging optimization in smart manufacturing systems," Applied Energy, Elsevier, vol. 406(C).
  25. Spinti, Jennifer P. & Smith, Philip J. & Smith, Sean T., 2022. "Atikokan Digital Twin: Machine learning in a biomass energy system," Applied Energy, Elsevier, vol. 310(C).
  26. Md. Ismail Hossain & Subrata Talapatra & Palash Saha & H. M. Belal, 2025. "From Theory to Practice: Leveraging Digital Twin Technologies and Supply Chain Disruption Mitigation Strategies for Enhanced Supply Chain Resilience with Strategic Fit in Focus," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 26(1), pages 87-109, March.
  27. Jayant Kalagnanam & Dzung T. Phan & Pavankumar Murali & Lam M. Nguyen & Nianjun Zhou & Dharmashankar Subramanian & Raju Pavuluri & Xiang Ma & Crystal Lui & Giovane Cesar da Silva, 2022. "AI-Based Real-Time Site-Wide Optimization for Process Manufacturing," Interfaces, INFORMS, vol. 52(4), pages 363-378, July.
  28. Gian Marco Paldino & Fabrizio De Caro & Jacopo De Stefani & Alfredo Vaccaro & Domenico Villacci & Gianluca Bontempi, 2022. "A Digital Twin Approach for Improving Estimation Accuracy in Dynamic Thermal Rating of Transmission Lines," Energies, MDPI, vol. 15(6), pages 1-17, March.
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