| Title: |
QUALIBOT: AI assistant for implementing quality management systems in the transition to Enterprise 4.0 and Quality 4.0. |
| Authors: |
Gentil, Marie-Helene1 (AUTHOR) marie-helene.gentil@u-bordeaux.fr; Merle, Catherine1 (AUTHOR) catherine.merle@u-bordeaux.fr |
| Source: |
International Journal of Quality & Reliability Management. 2026, Vol. 43 Issue 6, p1517-1540. 24p. |
| Subject Terms: |
*Artificial intelligence; *Industry 4.0; *Digital transformation; *Total quality management |
| Abstract: |
Purpose: The purpose of this research is to analyze and assess the contributions and obstacles between quality function and Enterprise 4.0, proposing principles and advice for a relevant articulation between these two approaches. It also aims to outline the new tasks of the quality manager in the context of Quality 4.0 and present QUALIBOT, a conceptual explainable AI tool designed to facilitate quality management in the Enterprise 4.0. Design/methodology/approach: The cross-analysis of scientific literature and feedback from the field from around twenty industrial companies made it possible to situate the project in the state of the art and to highlight existing practices, their limitations and the main scientific and operational obstacles. The authors also propose a conceptual model, QUALIBOT, which integrates principles of explainable AI to support quality management in an Enterprise 4.0 environment. Findings: The research highlights that integrating Quality with technologies of industry 4.0, such as AI, IoT and digital twins, offers significant potential for enhancing performance, flexibility and competitiveness. However, this integration also presents challenges, including the need for a redefined role for quality managers and the adaptation of traditional quality management systems. QUALIBOT is introduced as a tool to address these challenges by providing transparency and efficiency in quality management processes. Research limitations/implications: The study is conceptual in nature and primarily focused on proposing principles and frameworks. Empirical validation and testing of the QUALIBOT model and the proposed recommendations are needed to assess their practical effectiveness and scalability. Practical implications: The research provides actionable insights for companies transitioning to Enterprise 4.0 by offering guidance on aligning quality management systems with advanced technologies. It underscores the importance of redefining the role of quality managers and leveraging explainable AI tools like QUALIBOT to enhance quality oversight and decision-making in digitally transformed organizations. Originality/value: This study contributes to the emerging discourse on Quality 4.0 by exploring the integration of traditional quality management principles with cutting-edge technologies of Enterprise 4.0. It introduces the innovative concept of QUALIBOT, an explainable AI framework tailored to quality management, thus adding a novel dimension to the field. [ABSTRACT FROM AUTHOR] |
| : |
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| Database: |
Business Source Premier |