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

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 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.

Language: Английский

Enhancing end-of-life product recyclability through modular design and social engineering optimiser DOI
Guangdong Tian,

Haowen Sheng,

Lele Zhang

et al.

International Journal of Production Research, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 19

Published: Nov. 12, 2024

Amidst the thriving landscape of manufacturing, vision sustainability in Industry 5.0 is becoming increasingly significant. The implementation recycling represents a crucial step pursuit sustainability, particularly light mounting challenge posed by proliferation end-of-life (EOL) products. Addressing this challenge, we propose novel Design for Modular Recyclability (DFMR) approach aimed at facilitating EOL Our study develops multi-objective optimisation model with focus on maximising green recyclability and independence while minimising aggregation. We introduce an innovative Social Engineering Optimiser (SEO) to simulate behavioural patterns complex environments, aiding identifying implementing effective strategies optimal or near-optimal results diverse scenarios. practical effectiveness proposed models algorithms demonstrated applying them real-life case internal combustion engine, followed performance comparisons existing well-established algorithms. findings our demonstrate efficacy DFMR model, offering decision-makers undertake product recovery. This contributes further exploration promising paths towards sustainable manufacturing production that are more line 5.0.

Language: Английский

Citations

4
Endüstri 4.0 dan Endüstri 5.0 a Geçiş: Dijital Dönüşümde Yapay Zeka ve Metaverse in Rolü (Transitioning From Industry 4.0 To Industry 5.0: The Role of Artificial Intelligence and The Metaverse in Digital Transformation) DOI Open Access
Kemal Gökhan NALBANT, Sevgi Aydın

Turk Turizm Arastirmalari Dergisi, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 4, 2025

Endüstri 4.0'dan 5.0'a geçiş, endüstriyel operasyonlarda önemli bir değişim anlamına gelmektedir. 4.0 otomasyon ve veri merkezli operasyonlara öncelik verirken, 5.0 kişiselleştirme, insan-makine işbirliği sürdürülebilir üretimi teşvik etmektedir. Yapay zeka (AI) bu dönüşümde çok rol oynamakta karar verme, tahmine dayalı analitik otonom sistemleri güçlendirmektedir. 5.0'da yapay zeka, insan yaratıcılığını otomasyonla bütünleştirerek daha akıllı uyarlanabilir süreçleri kolaylaştırır. Metaverse, insanlar, makineler robotlar arasında için sürükleyici sanal ortamlar sunarak değişimi Kuruluşlar, fiziksel uygulamadan önce artırılmış gerçeklik, dijital ikizler simülasyonlar kullanarak ortamda geliştirebilir yaratabilir. metaverse birlikte paradigma oluşturmakta, insanlar arasındaki ara yüzü geliştirirken yenilikçiliği verimliliği Bu çalışma, teknolojilerinin, iş birliği üretim gibi alanlarda 5.0’a sağladığı katkıları analiz etmeyi amaçlamaktadır. Özellikle, uygulamaları ile gerçeklik (metaverse) etkileşim ele alınarak, teknolojilerin yenilikçi çözümler geliştirme potansiyeli değerlendirilmektedir. Çalışma, süreçlerin verimli hale gelmesi metaverse’in nasıl kullanılabileceğine dair bütünsel çerçeve sunmaktadır.

Citations

0
Digital transformation in wine business – from Marketing 5.0 to Industry 5.0 in the world of wine adopting artificial intelligence DOI
Giuseppe Festa, Antonio D’Amato, Rosa Palladino

et al.

European Journal of Innovation Management, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 8, 2025

Purpose Artificial intelligence (AI) is vastly impacting the digital transformation of societies, economies, businesses, markets and enterprises, at a very fast pace, mostly after global success generative algorithms. In this respect, study, with an exploratory intention, aims to provide evidence about fundamental issues AI, particularly if generative, when adapted humanism, specific focus on wine business. Design/methodology/approach An analysis, conducted convenience sample business operators, has been performed investigate AI applications connected conceptual platform “Industry 5.0” framework. Findings The results survey in Specifically, research outcomes highlight that interviewees (wine operators) recognized high relevance potential use strategic operating management firms. Originality/value This study new empirical regard application real contexts. More specifically, investigation, interaction between sustainability highlighted industry, especially from environmental point view, i.e. for respectfully governing managing impact planet also increasing general efficiency process, peculiar managerial, economic financial side

Language: Английский

Citations

0
Utilizing Artificial Intelligence and Machine Learning for Enhanced Recycling Efforts DOI
Nikita Kandpal,

Nishant Singhal,

Harsh Vardhan Lavaniya

et al.

Advances in environmental engineering and green technologies book series, Journal Year: 2025, Volume and Issue: unknown, P. 65 - 82

Published: Jan. 16, 2025

One industry that has benefitted largely from the integration of Artificial Intelligence (AI) and machine learning (ML) in its processes is recycling, providing significant advancements waste management towards sustainability environmental conservation. This chapter highlights application AI ML various streams (plastic, electronic food, paper, textile, metal etc. wastage). These systems use AI-powered image recognition sorting to better separate materials, helping increasing efficiency chemical recycling technologies; meanwhile algorithms enable cleaner for handling chemicals material recovery. Increased precision removal valuable components via automated disassembly predictive analytics. Using helped increase operational efficiency, resources recovery but also shown clear contributions environment overall ensure sustainable future ahead.

Language: Английский

Citations

0
Ten industrial software towards smart manufacturing DOI

Tianyi Gao,

Lei Wang, Wenyan Song

et al.

Journal of Manufacturing Systems, Journal Year: 2025, Volume and Issue: 79, P. 255 - 285

Published: Feb. 1, 2025

Language: Английский

Citations

0
Transparent information fusion network: An explainable network for multi-source bearing fault diagnosis via self-organized neural-symbolic nodes DOI
Qi Li, Lichang Qin, Haifeng Xu

et al.

Advanced Engineering Informatics, Journal Year: 2025, Volume and Issue: 65, P. 103156 - 103156

Published: Feb. 1, 2025

Language: Английский

Citations

0
Systematic literature review on Industry 5.0: current status and future research directions with insights for the Asia Pacific countries DOI Creative Commons
Imran Ali, Khoa A. Nguyen, Ingyu Oh

et al.

Asia Pacific Business Review, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 28

Published: Feb. 4, 2025

Language: Английский

Citations

0
Cybersecurity in microgrids: A review on advanced techniques and practical implementation of resilient energy systems DOI Creative Commons
Ijaz Ahmed, Ali M. El‐Rifaie,

F. Akhtar

et al.

Energy Strategy Reviews, Journal Year: 2025, Volume and Issue: 58, P. 101654 - 101654

Published: Feb. 5, 2025

Language: Английский

Citations

0
Integrating large language model and digital twins in the context of industry 5.0: Framework, challenges and opportunities DOI
Chong Chen,

K Zhao,

Jiewu Leng

et al.

Robotics and Computer-Integrated Manufacturing, Journal Year: 2025, Volume and Issue: 94, P. 102982 - 102982

Published: Feb. 10, 2025

Language: Английский

Citations

0
Integrated registration and utility of mobile AR Human-Machine collaborative assembly in rail transit DOI
Jiu Yong, Jianguo Wei,

Xiaomei Lei

et al.

Advanced Engineering Informatics, Journal Year: 2025, Volume and Issue: 65, P. 103168 - 103168

Published: Feb. 17, 2025

Language: Английский

Citations

0