Human-aware scheduling for sustainable manufacturing: A review of dynamic job shop scheduling in the era of Industry 5.0

Abstract

In the context of Industry 5.0, job scheduling must evolve beyond traditional efficiency-focused approaches to incorporate adaptability, sustainability, and human-centric approaches. Although Industry 4.0 technologies such as IoT, digital twins, and sensors have enabled real-time and dynamic-adaptive scheduling, most current systems still rely on static models and lack integrated consideration of environmental and human factors within dynamic scheduling contexts. To realize the vision of Industry 5.0 in practical applications, there is a growing need for dynamic scheduling methods that unify these dimensions. Given the limited research in this area, the present study proposes a comprehensive research framework for sustainable dynamic job scheduling, supported by structured conceptual models that explicitly outline how dynamic factors, environmental aspects, and human factors can be systematically incorporated into job scheduling problems. A systematic review of the literature is also conducted to assess recent progress and identify underexplored areas. The resulting framework is intended to provide a clear and structured foundation for future research aimed at developing intelligent, adaptive, eco-friendly, and human-aware scheduling systems aligned with the demands of Industry 5.0.