An Integrated Analytic Hierarchy Process–Fuzzy Inference System Framework for Assessing Industry 4.0 Digital Maturity in Manufacturing Organizations

The fourth industrial revolution, or Industry 4.0, is fundamentally transforming manufacturing through the integration of cyber-physical systems, the Internet of Things (IoT), big data analytics, artificial intelligence, and intelligent automation.Despite its potential benefits, digital transformation remains challenging because it requires substantial investment, workforce capability development, and organizational change.Existing Industry 4.0 maturity models inadequately address systematic criteria weighting and uncertainty in digital maturity assessment, limiting their ability to provide comprehensive and decision-oriented evaluations.This study develops a sevendimensional Industry 4.0 digital maturity framework by integrating the Analytic Hierarchy Process (AHP) and the Fuzzy Inference System (FIS).AHP is employed to derive expert-based priority weights among maturity dimensions, while FIS accommodates uncertainty and subjectivity in qualitative assessments through fuzzy reasoning.The research methodology comprises model conceptualization, criteria weighting using AHP, maturity evaluation using FIS, and validation through a case study of an automotive manufacturing company.The findings indicate that the Strategy, Culture and Expertise, and Organization and Change Management dimensions receive the highest priority weights, while Intelligent Manufacturing achieves the highest maturity score.The case organization obtained an overall maturity index of 0.73, corresponding to Stage 4, which indicates a high level of digitalization.The proposed AHP-FIS framework provides a structured, adaptive, and data-driven approach for evaluating Industry 4.0 maturity and offers decision support for prioritizing digital transformation initiatives and planning continuous improvement.The findings demonstrate the practical feasibility of the framework within the investigated automotive manufacturing context and provide methodological insights for future development of Industry 4.0 maturity assessment models.