Jun 2026· Computing· Vol 108· 0 citations· 45 references
Computer Science
TL;DR
This systematic review synthesizes advancements in ML-based process optimization from 2015 to 2025, analyzing 185 peer-reviewed articles from Scopus, Web of Science, and IEEE Xplore to provide a comprehensive foundation for advancing ML applications in modern manufacturing systems.
The development of AI-enabled advisory systems for casting processes are presented, integrating singular value decomposition (SVD)-based reduced-order models with a Variational Autoencoder with Arbitrary Conditioning (AC-VAE) and hybrid simulation frameworks to support real-time process prediction and optimization.
Sofija Milicic, A. Horr, S. Elgeti et al.· Processes· 0 citations
Key performance indicators, including production efficiency, resource utilization, product quality, energy efficiency, downtime reduction, and system reliability, demonstrate the effectiveness of the proposed Digital Twins framework.
Suresh Babu Reddy· International Journal of App...· 0 citations
An AI-enabled process optimization framework that combines real-time sensor data, predictive analytics, machine learning, reinforcement learning, optimization algorithms, and closed-loop feedback to improve manufacturing performance is proposed.
N. Wirth· International Journal of Int...· 0 citations
The findings show that machine learning, deep learning, computer vision, computer vision, reinforcement learning, knowledge-driven approaches, digital twins, and explainable AI contribute to improvements in predictive maintenance, quality inspection, production scheduling, adaptive safety, and collaborative decision-ma...
Zaliha Baso, N. Yadav, P. Faujdar· Cureus Journal of Computer S...· 0 citations
It is argued that first-principles models (FPMs) remain essential for mission- and business-critical workflows in industrial automation, both in process design and operations and hybrid intelligence integrates mechanistic rigor with data-driven insights to deliver smarter design, safer operations, and more sustainable...
Hong Zhao, Shu Wang, Salvador I. Pérez-Uresti et al.· Industrial & Engineering...· 0 citations
Comparative analysis shows that the RL-based approach outperforms the rule-based and heuristic strategies and reports remarkable energy efficiency and operational sustainability.
A. Jain· Materials Research Proceedin...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
