ENHANCING QUALITY ASSURANCE THROUGH AUTONOMOUS POKA-YOKE SYSTEMS IN INDUSTRY 5.0 ENVIRONMENTS
Justyna Żywiołek,
Gilberto Santos,
Muhammad Asghar Khan,
Ghayur Ahmad,
Hana Štverková
Abstract: This study analyzes the integration of poka-yoke systems within the concept of Industry 5.0, where human-machine collaboration and intelligent autonomous systems play a key role. Poka-yoke, traditionally used to prevent errors at the source, is evolving into advanced, adaptive mechanisms supported by artificial intelligence (AI) and machine learning. This integration enables real-time process monitoring and predictive failure prevention, allowing poka-yoke to dynamically adapt to changing production conditions and demanding manufacturing environments. The analysis includes case studies that illustrate poka-yoke applications in smart factories, emphasizing proactive quality control, flexibility, and sustainability. Challenges related to implementing poka-yoke in Industry 5.0, such as technology interoperability, data security, and employee training needs, are also addressed. Findings indicate that poka-yoke in Industry 5.0 contributes to defect reduction, enhances product reliability, and supports the development of sustainable production systems aligned with modern standards of quality and efficiency.
Keywords: Poka-yoke, Industry 5.0, Quality management, Artificial intelligence, Machine learning, Automation
DOI: 10.24874/IJQR20.01-05
Recieved: 20.11.2024 Accepted: 02.06.2025 UDC:
Reads: 59 
