Human‐Centric Job‐Shop Production Planning and Scheduling System Based on the Concept of I5.0

Production systems must constantly adapt to changing conditions, requiring planners to make complex decisions under uncertainty that significantly impact operational and financial performance. While digitalization of Production Planning and Scheduling (PPS) has been widely adopted using Artificial Intelligence (AI) and machine learning in Industry 4.0 (I4.0), I4.0 often overlooks human concentration and fatigue, which can compromise the robustness of production plans. Industry 5.0 (I5.0) addresses this limitation by leveraging human expertise and creativity to create intelligent, value‐driven, and sustainable production systems. This study develops a Digital Twin (DT)–based PPS system for a job‐shop production model, integrating Dynamic Break Integration (DBI). The framework actively involves operators via smartwatches, capturing real‐time data on microbreaks, operator status, and situational awareness. By combining human feedback, dynamic break management, and automated planning, the system improves decision‐making clarity, reduces fatigue, and enhances both worker welfare and productivity. Testing in a job‐shop scenario demonstrated significant improvements in schedule adherence, cycle time, and overall efficiency. These results confirm that incorporating DBI and human‐in‐the‐loop feedback into DT‐based PPS enables a responsive, human‐centric production environment, fully realizing the principles of I5.0 while achieving higher performance than conventional I4.0 approaches.