Academic Journal
Modeling Organizational Resilience in Human-Cyber-Physical Systems (Industry 5.0) Through Collective Dynamics, Decision Scenarios and Crisis-Aware AI: A Multi-Method Simulation Approach
| Title: | Modeling Organizational Resilience in Human-Cyber-Physical Systems (Industry 5.0) Through Collective Dynamics, Decision Scenarios and Crisis-Aware AI: A Multi-Method Simulation Approach |
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| Authors: | Olga Bucovețchi, Andreea Elena Voipan, Daniel Voipan, Alexandru Georgescu, Razvan Mihai Dobrescu |
| Source: | Applied Sciences. 16:292 |
| Publisher Information: | MDPI AG, 2025. |
| Publication Year: | 2025 |
| Description: | Supply chain disruptions during the COVID-19 pandemic exposed structural vulnerabilities of centrally controlled manufacturing systems, motivating renewed interest in organizational resilience within the context of Industry 5.0 human–cyber–physical systems. This study investigates how organizational decision-making paradigms and crisis-aware artificial intelligence (AI) jointly influence performance, crisis response, and recovery. An agent-based modeling (ABM) framework is developed to compare centralized, distributed, and self-organized organizational structures across 650 simulation runs under a controlled supply side disruption. A crisis-aware Q-learning architecture enables AI agents to shift from efficiency-oriented to stability-oriented strategies when resource scarcity is detected. To avoid baseline-dependent bias, resilience is evaluated using an absolute, capacity-normalized metric. Results indicate that self-organized systems consistently outperform centralized and distributed structures in baseline performance, crisis throughput, and recovery speed. The integration of crisis-aware AI further increases absolute resilience by approximately 10.7% and enables substantially higher throughput during disruption compared to hierarchical control. Enhanced performance is primarily driven by adaptive coalition formation, proactive resource conservation, and rapid post-crisis recovery supported by preserved coordination structures. These findings provide quantitative support for Industry 5.0’s human-centric principles and show that decentralized decision-making augmented by context-adaptive AI offers a robust organizational design strategy for volatile manufacturing environments. |
| Document Type: | Article |
| Language: | English |
| ISSN: | 2076-3417 |
| DOI: | 10.3390/app16010292 |
| Rights: | CC BY |
| Accession Number: | edsair.doi...........0e0352f8b11549404053efa668b4de7e |
| Database: | OpenAIRE |
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