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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.00067 |
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| _version_ | 1866918152227520512 |
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| author | Maciel, Rafael da Silva Veraldo Jr, Lucio |
| author_facet | Maciel, Rafael da Silva Veraldo Jr, Lucio |
| contents | The evolution of the 5S methodology with the support of artificial intelligence techniques represents a significant opportunity to improve industrial organization audits in the automotive chain, making them more objective, efficient and aligned with Industry 4.0 standards. This work developed an automated 5S audit system based on large-scale language models (LLM), capable of assessing the five senses (Seiri, Seiton, Seiso, Seiketsu, Shitsuke) in a standardized way through intelligent image analysis. The system's reliability was validated using Cohen's concordance coefficient (kappa = 0.75), showing strong alignment between the automated assessments and the corresponding human audits. The results indicate that the proposed solution contributes significantly to continuous improvement in automotive manufacturing environments, speeding up the audit process by 50% of the traditional time and maintaining the consistency of the assessments, with a 99.8% reduction in operating costs compared to traditional manual audits. The methodology presented establishes a new paradigm for integrating lean systems with emerging AI technologies, offering scalability for implementation in automotive plants of different sizes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_00067 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Intelligent 5S Audit: Application of Artificial Intelligence for Continuous Improvement in the Automotive Industry Maciel, Rafael da Silva Veraldo Jr, Lucio Computer Vision and Pattern Recognition Artificial Intelligence Human-Computer Interaction 68T05, 90B30 I.2.1; H.4.2; J.6 The evolution of the 5S methodology with the support of artificial intelligence techniques represents a significant opportunity to improve industrial organization audits in the automotive chain, making them more objective, efficient and aligned with Industry 4.0 standards. This work developed an automated 5S audit system based on large-scale language models (LLM), capable of assessing the five senses (Seiri, Seiton, Seiso, Seiketsu, Shitsuke) in a standardized way through intelligent image analysis. The system's reliability was validated using Cohen's concordance coefficient (kappa = 0.75), showing strong alignment between the automated assessments and the corresponding human audits. The results indicate that the proposed solution contributes significantly to continuous improvement in automotive manufacturing environments, speeding up the audit process by 50% of the traditional time and maintaining the consistency of the assessments, with a 99.8% reduction in operating costs compared to traditional manual audits. The methodology presented establishes a new paradigm for integrating lean systems with emerging AI technologies, offering scalability for implementation in automotive plants of different sizes. |
| title | Intelligent 5S Audit: Application of Artificial Intelligence for Continuous Improvement in the Automotive Industry |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence Human-Computer Interaction 68T05, 90B30 I.2.1; H.4.2; J.6 |
| url | https://arxiv.org/abs/2510.00067 |