2018· International Journal of Machine Learning and Predictive Analytics· Vol 1, pp. 01-12· 0 citations
TL;DR
An AI-based framework for dynamic reconfiguration of modular smart manufacturing cells, enabling rapid adaptation to changing production demands, equipment failures, and optimization goals is presented.
Abstract
The evolution of Industry 4.0 has brought forth an increasing demand for flexibility, adaptability, and intelligence in manufacturing systems. Modular smart manufacturing cells, with their inherent reconfigurability, are becoming essential components in modern production environments. This paper presents an AI-based framework for dynamic reconfiguration of such cells, enabling rapid adaptation to changing production demands, equipment failures, and optimization goals. Leveraging machine learning and real-time data analytics, the proposed system autonomously identifies optimal reconfiguration strategies with minimal human intervention. A case study is presented to validate the framework, demonstrating significant improvements in operational efficiency and system responsiveness. The results highlight the transformative potential of AI in achieving truly autonomous and resilient manufacturing systems.
This paper introduces an extended outline of the AI-based decision-making in manufacturing facilities with the application of real-time sensor data, machine learning, and adaptive control and puts emphasis on the possibilities of AI-powered systems to reach Industry 4.0 goals.
Davinder Singh· Materials Research Proceedin...· 0 citations
The Industry 5.0 demands flexibility, resilience, and human-centricity in manufacturing systems. To address the lengthy changeover times and complexities in discrete manufacturing, this study proposes a comprehensive flexible reconfiguration and intelligent scheduling framework to achieve production line optimization....
Qing-Xin Li· Journal of Physics, Conferen...· 0 citations
Smart manufacturing represents the confluence of digital transformation and
industrial evolution, redefining manufacturing paradigms through seamless integration,
artificial intelligence (AI)-driven intelligence, and continuous innovation. This paper
explores the future development of smart manufacturing, highlighting...
Vidosav Majstorović· SMART MANUFACTURING ON THE H...· 0 citations
As the global manufacturing industry accelerates its digital and intelligent transformation, the deep integration of Artificial Intelligence (AI) with the Internet of Things (IoT) is emerging as a central driver behind the evolution of smart manufacturing systems. This paper provides a comprehensive review of the techn...
Xuan-Yi Chen· Applied and Computational En...· 0 citations
This review examines recent advances in the integration of Artificial Intelligence with Autonomous Mobile Robots (AMRs) for real-time material flow optimization in EV manufacturing ecosystems to identify key performance improvements in throughput, operational efficiency, and cost reduction attributed to AI-AMR integrat...
Olasubomi Akanbi· International Journal of Eng...· 0 citations
The results show that AI can greatly decrease the time spent on design iterations, increase the accuracy of predictions of process parameters, and allow in-situ defect detection with high accuracy.
