The Industry 5.0 framework: viability-based integration of the resilience, sustainability, and human-centricity perspectives

International Journal of Production Research, Journal Year: 2022, Volume and Issue: 61(5), P. 1683 - 1695

Published: Sept. 12, 2022

Industry 5.0 is a combination of organisational principles and technologies to design manage operations supply chains as resilient, sustainable, human-centric systems. While the general notion has been elaborated, its implications for future remain underexplored. This paper contributes conceptualisation from perspective viability. We contextualise framework through lens viable chain model, reconfigurable chain, ecosystems. Our study uncovers major dimensions that characterise technological-organisational framework. First, technological are collaboration, coordination, communication, automation, data analytics processing, identification. Second, covers four areas: organisation, management, technology, performance assessment. Third, spans three levels: society level, network plant level. Last but not least, frames new triple bottom line: resilient value creation, human well-being, sustainable society. provide definition discuss by elaborating on understanding in 5.0, which profit, people, also open research areas.

Language: Английский

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Supply chain disruption during the COVID-19 pandemic: Recognizing potential disruption management strategies

International Journal of Disaster Risk Reduction, Journal Year: 2022, Volume and Issue: 75, P. 102983 - 102983

Published: April 22, 2022

Language: Английский

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Cloud supply chain: Integrating Industry 4.0 and digital platforms in the “Supply Chain-as-a-Service”

Transportation Research Part E Logistics and Transportation Review, Journal Year: 2022, Volume and Issue: 160, P. 102676 - 102676

Published: March 17, 2022

Language: Английский

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Toward the Next Generation of Digitalization in Agriculture Based on Digital Twin Paradigm

Sensors, Journal Year: 2022, Volume and Issue: 22(2), P. 498 - 498

Published: Jan. 10, 2022

Digitalization has impacted agricultural and food production systems, makes application of technologies advanced data processing techniques in field possible. Digital farming aims to use available information from assets solve several existing challenges for addressing security, climate protection, resource management. However, the sector is complex, dynamic, requires sophisticated management systems. The digital approaches are expected provide more optimization further decision-making supports. twin agriculture a virtual representation farm with great potential enhancing productivity efficiency while declining energy usage losses. This review describes state-of-the-art concepts along different contexts. It presents general framework twins soil, irrigation, robotics, machineries, post-harvest field. Data recording, modeling including artificial intelligence, big data, simulation, analysis, prediction, communication aspects (e.g., Internet Things, wireless technologies) discussed. systems can support farmers as next generation digitalization paradigm by continuous real-time monitoring physical world (farm) updating state world.

Language: Английский

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Blockchain-supported business model design, supply chain resilience, and firm performance

Transportation Research Part E Logistics and Transportation Review, Journal Year: 2022, Volume and Issue: 163, P. 102773 - 102773

Published: June 2, 2022

Language: Английский

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Adapting supply chain operations in anticipation of and during the COVID-19 pandemic

Omega, Journal Year: 2022, Volume and Issue: 110, P. 102635 - 102635

Published: March 7, 2022

Language: Английский

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A review on reinforcement learning algorithms and applications in supply chain management

International Journal of Production Research, Journal Year: 2022, Volume and Issue: 61(20), P. 7151 - 7179

Published: Nov. 3, 2022

Decision-making in supply chains is challenged by high complexity, a combination of continuous and discrete processes, integrated interdependent operations, dynamics, adaptability. The rapidly increasing data availability, computing power intelligent algorithms unveil new potentials adaptive data-driven decision-making. Reinforcement Learning, class machine learning algorithms, one the methods. This semi-systematic literature review explores current state art reinforcement chain management (SCM) proposes classification framework. framework classifies academic papers based on drivers, sources, industrial sectors. conducted revealed few critical insights. First, classic Q-learning algorithm still most popular one. Second, inventory common application chains, as it pivotal element synchronisation. Last, reviewed address toy-like SCM problems driven artificial data. Therefore, shifting to industry-scale will be crucial challenge next years. If this shift successful, vision decision-making real-time could become reality.

Language: Английский

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Role of flexibility, agility and responsiveness for sustainable supply chain resilience during COVID-19

Journal of Cleaner Production, Journal Year: 2022, Volume and Issue: 362, P. 132431 - 132431

Published: May 27, 2022

Language: Английский

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Industry 5.0 challenges for post-pandemic supply chain sustainability in an emerging economy

International Journal of Production Economics, Journal Year: 2023, Volume and Issue: 258, P. 108806 - 108806

Published: Feb. 11, 2023

Language: Английский

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Convergence of Distributed Ledger Technologies with Digital Twins, IoT, and AI for fresh food logistics: Challenges and opportunities

Journal of Industrial Information Integration, Journal Year: 2022, Volume and Issue: 31, P. 100393 - 100393

Published: Sept. 29, 2022

Language: Английский

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