Reshoring Decisions in Supply Chains and Industry 5.0 Optimization: AI Based Sustainable Decision Support Model DOI
Muhammet Mustafa Akkan

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Апрель 2, 2025

Abstract Global supply chains face increasingly uncertain phenomena and reshoring decisions have become a strategic necessity. This paper presents an artificial intelligence-based decision support model for optimizing processes in connection with sustainability Industry 5.0 principles. The developed supports multidimensional decision-making chain management by using big data analytics, machine learning optimization techniques. proposed framework evaluates critical factors such as lead time, cost, operational risks, environmental impact, resilience integrated approach. Combining different sources, the allows makers to determine most appropriate strategies conducting dynamic scenario analyses. approach, which adopts human-machine collaboration approach of 5.0, not only increases economic efficiency, but also contributes principles sustainable production management. With study, it is aimed make significant contributions academic literature industrial applications presenting new perspective on decisions.

Язык: Английский

Engineering The Future of Higher Education: A VOSviewer Analysis of Smart University Trends in The Digitalization and Industry 5.0 Era DOI Creative Commons
Joanna Rosak-Szyrocka

Management Systems in Production Engineering, Год журнала: 2025, Номер 33(1), С. 8 - 23

Опубликована: Фев. 17, 2025

Abstract This manuscript aims to map the changing landscape of smart universities within frameworks digitalization and Industry 5.0, identifying key trends, challenges, opportunities for observation. study analyzes 8,061 Scopus database research papers from 2016 2024 by using VOSviewer network visualization bibliometric analysis. Centering around explores literature that spans both “smart” “university” landscapes. The findings suggest a rich fast-evolving field with strong focus on inclusion advanced technologies, intelligent systems pedagogies in higher education contexts, as well significant international collaboration. Significant issues include use IoT, AI, cloud computing enhancing processes, learning environments, safety campus. paper fills an important gap providing thorough exploration university ecosystem through lenses noting point technology will be integral determinant future faculty educational institutions. It sets out exact blueprint way become more responsive, efficient networked

Язык: Английский

Процитировано

0
A large language model-based manufacturing process planning approach under industry 5.0 DOI
Mingzhe Ni,

Tao Wang,

Jiewu Leng

и другие.

International Journal of Production Research, Год журнала: 2025, Номер unknown, С. 1 - 20

Опубликована: Фев. 24, 2025

Язык: Английский

Процитировано

0
A Strategic Data‐Driven Roadmap for Enhancing Energy Security in Taiwan Under Industry 5.0 DOI Open Access
Tat‐Dat Bui, Jiun‐Wei Tseng, Anthony S.F. Chiu

и другие.

Expert Systems, Год журнала: 2025, Номер 42(4)

Опубликована: Март 11, 2025

ABSTRACT Energy security performs a decisive position in the economic sustainability and societal development. As Taiwan attempts for sustainable expansion, decoupling energy is fundamental requires advanced information technologies infrastructure application, especially connection to Industry 5.0 era. However, two concepts proxy manifest multi‐dimensional nature with vast literature; there an absence of strategic roadmap implementation tactics. This study presents systematic data‐driven analysis combining text mining, fuzzy Delphi method, interpretive structural modelling, decision‐making trial evaluation laboratory, analytic network process outline distinct unveil contributions. There are 22 valid indicators generated allocated into five aspects. The causal interrelation model obtained. technological advancement integration, environmental climate actions, public demand perception categorised as causative top indicated change mitigation, cyber‐physical systems, investment, perception, supply–demand side technologies. enriches theoretical literature serves valuable practical locus improve 5.0.

Язык: Английский

Процитировано

0
Assembly Time Standard Setting Based on Kernel Estimators DOI Creative Commons

Izabela Kutschenreiter-Praszkiewicz

Journal of Machine Engineering, Год журнала: 2025, Номер unknown

Опубликована: Март 22, 2025

Time standards belong to vital indicators of the production process that facilitate making decisions related product and improvement. The presented issues concern determination assembly time standard using kernel estimators. development neural networks offers possibility identify begin-end points in can provide big data standard. problem addressed this paper is a method analysis, on basis which be determined. In approach adequate formulas are developed together with some examples. presents an application theory estimators as well results proposed approach.

Язык: Английский

Процитировано

0
Reshoring Decisions in Supply Chains and Industry 5.0 Optimization: AI Based Sustainable Decision Support Model DOI
Muhammet Mustafa Akkan

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Апрель 2, 2025

Abstract Global supply chains face increasingly uncertain phenomena and reshoring decisions have become a strategic necessity. This paper presents an artificial intelligence-based decision support model for optimizing processes in connection with sustainability Industry 5.0 principles. The developed supports multidimensional decision-making chain management by using big data analytics, machine learning optimization techniques. proposed framework evaluates critical factors such as lead time, cost, operational risks, environmental impact, resilience integrated approach. Combining different sources, the allows makers to determine most appropriate strategies conducting dynamic scenario analyses. approach, which adopts human-machine collaboration approach of 5.0, not only increases economic efficiency, but also contributes principles sustainable production management. With study, it is aimed make significant contributions academic literature industrial applications presenting new perspective on decisions.

Язык: Английский

Процитировано

0