Development of an Explainable Expert System for Smart Factory Readiness Assessment in Manufacturing Industries - Sandor Krizstian (Institute of Computer Science (IOCS), 2026)
Smart Factory adoption has become a critical strategy for manufacturing industries seeking to improve productivity, operational flexibility, and global competitiveness in the era of Industry 4.0. However, many organizations still lack a systematic, reliable, and transparent approach to evaluating their readiness for Smart Factory implementation. This study aims to develop an Expert System for determining industry readiness for Smart Factories by integrating expert knowledge and Explainable Artificial Intelligence (XAI). Expert knowledge was acquired through interviews with Industry 4.0 specialists, manufacturing practitioners, and automation experts, as well as an extensive literature review to identify readiness criteria related to technology, organization, human resources, processes, and financial capability. To enhance transparency and user trust, Explainable AI techniques were incorporated to provide interpretable explanations and feature contribution analyses for readiness recommendations. The system was validated through expert evaluation and case studies involving manufacturing organizations. The results indicate that the proposed system successfully classified organizations into five readiness levels and generated clear, understandable explanations for each recommendation. Validation findings demonstrated a high level of agreement between system outputs and expert assessments, confirming the reliability and practical applicability of the proposed approach. Furthermore, feature contribution analysis revealed that automation level, workforce digital skills, and IoT infrastructure were the most influential determinants of Smart Factory readiness.