Gen AI systems text-based, vision-based, and multimodal, deployed both locally and in cloud-based environments, were found to be utilized in remanufacturing processes, with the majority of studies focusing on LLM models developed by OpenAI.
Abstract
In recent years, due to the high importance of raw materials, cost reduction pressures, and environmental concerns, remanufacturing processes have gained significant importance. In parallel, different Artificial Intelligence (AI) models especially, Generative AIs (Gen AIs) have been penetrating into work environments to improve efficiency and effectiveness of the tasks. Aim of this article is to provide a scoping review of studies addressing the use of Gen AI in remanufacturing processes. The literature search was conducted across four major databases, and the results were complemented using Google Scholar. In total, 23 articles were included in the final stage of analysis. Gen AI systems text-based, vision-based, and multimodal, deployed both locally and in cloud-based environments, were found to be utilized in these processes. The majority of studies focusing on LLM models developed by OpenAI. The most prominent contributions of Gen AI were observed in the following areas: Code Generation and Robotic Control, Safety and Risk, Supporting system performance as a powerful “eye”, and Intelligent Planning and Reasoning (as the strategist of the system). It appears that the initial phase of introducing diverse applications of generative AI models in remanufacturing processes is approaching its conclusion. In the coming years, with the rapid advancement of generative AI, a substantial portion of these processes is expected to be delegated to such systems, and it is even conceivable that they may partially replace robots in certain tasks.
The convergence of additive manufacturing (AM) and artificial intelligence (AI) is poised to redefine the landscape of modern production; however, the literature remains fragmented across isolated applications, lacking a unified perspective on the engineering impact and practical deployment of these technologies. This...
The 6th International Conference on Advanced Materials and Mechatronics (ICAMM 2026) convened in Dalian, China, from May 15 to 17, 2026, at a time when materials innovation and intelligent mechanical systems are increasingly converging into a unified research frontier. Rather than treating materials science and mechatr...
Unknown authors· Journal of Physics, Conferen...· 0 citations
Contact-rich manufacturing processes, such as surface cleaning, deburring, and polishing, require precise force regulation and complex trajectory tracking that are challenging to automate using conventional robot programming methods. Learning from Demonstration (LfD) offers a powerful alternative to transfer these expe...
Ercan Düzgün· Journal of Manufacturing and...· 0 citations
This framework facilitates a fully automated finite-element simulation workflow, significantly reducing the modeling threshold while improving efficiency and accuracy, thus offering a new, efficient, and cost-effective paradigm for the digital transformation of the apparel industry.
Ke-Ke Yang, Meng-Ting Ye, Yu-Xing Zhang et al.· Textile research journal· 0 citations
The evidence reveals an explainability-autonomy divide and substantial field-validation and reproducibility gaps in agentic/autonomous AI and/or XAI in agricultural systems using sensor, robotic or computer-vision data and reporting an evaluation.
Florin Militaru, C. Popescu, Ramona Ciolac et al.· Agronomy· 0 citations
A highly flexible, wireless, 5G-based system that serves as a versatile experimental testbed for applications including remanufacturing, operator training, and user studies, and revealed practical limitations related to interoperability in current 5G deployments that should be addressed in future works.
E. Takacs, Mátyás Hajós, Á. Juniki et al.· 0 citations
AI is moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post Building trustworthy AI: The role of AI harnesses, intent contracts and evals appeared first on GPT-Lab.
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
MIT News · Artificial Intelligence· news.mit.eduOct 13, 2026