Multimodal Large Language Model-Based Fault Detection and Diagnosis in Context of Industry 4.0 DOI Open Access
Khalid Alsaif, Aiiad Albeshri, Maher Khemakhem

et al.

Electronics, Journal Year: 2024, Volume and Issue: 13(24), P. 4912 - 4912

Published: Dec. 12, 2024

In this paper, a novel multimodal large language model-based fault detection and diagnosis framework that addresses the limitations of traditional approaches is proposed. The proposed leverages Generative Pre-trained Transformer-4-Preview model to improve its scalability, generalizability, efficiency in handling complex systems various scenarios. Moreover, synthetic datasets generated via models augment knowledge base enhance accuracy imbalanced framework, hybrid architecture integrates online offline processing, combining real-time data streams with fine-tuned for dynamic, accurate, context-aware suited industrial settings, particularly focusing on security concerns, introduced. This comprehensive approach aims address challenges advance field toward more adaptive efficient systems. paper presents detailed literature review, including taxonomy methods their applications across domains. study discusses case results comparisons, exploring implications future developments within Industry 4.0 technologies.

Language: Английский

A generative pre-trained transformer industrial bot to improve operators’ working experience in a small Industry 5.0 factory DOI Creative Commons
Kahiomba Sonia Kiangala, Zenghui Wang

The International Journal of Advanced Manufacturing Technology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 22, 2025

Language: Английский

Citations

0
Accelerating Industry 4.0 and 5.0: The Potential of Generative Artificial Intelligence DOI
Pedro Antonio Boareto, Anderson Luis Szejka, Eduardo de Freitas Rocha Loures

et al.

Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 456 - 472

Published: Jan. 1, 2025

Language: Английский

Citations

0
High-speed machining of hardened steel during moldand die production: a critical review toward an Industry 5.0 environment DOI
Jonny Herwan, German Herrera-Granados,

Ichiro Ogura

et al.

The International Journal of Advanced Manufacturing Technology, Journal Year: 2025, Volume and Issue: unknown

Published: March 27, 2025

Language: Английский

Citations

0
Multimodal Large Language Model-Based Fault Detection and Diagnosis in Context of Industry 4.0 DOI Open Access
Khalid Alsaif, Aiiad Albeshri, Maher Khemakhem

et al.

Electronics, Journal Year: 2024, Volume and Issue: 13(24), P. 4912 - 4912

Published: Dec. 12, 2024

In this paper, a novel multimodal large language model-based fault detection and diagnosis framework that addresses the limitations of traditional approaches is proposed. The proposed leverages Generative Pre-trained Transformer-4-Preview model to improve its scalability, generalizability, efficiency in handling complex systems various scenarios. Moreover, synthetic datasets generated via models augment knowledge base enhance accuracy imbalanced framework, hybrid architecture integrates online offline processing, combining real-time data streams with fine-tuned for dynamic, accurate, context-aware suited industrial settings, particularly focusing on security concerns, introduced. This comprehensive approach aims address challenges advance field toward more adaptive efficient systems. paper presents detailed literature review, including taxonomy methods their applications across domains. study discusses case results comparisons, exploring implications future developments within Industry 4.0 technologies.

Language: Английский

Citations

0