Applying Industry 4.0Industry 4.0 enabling technologies to the production planning and control (PPC) area has become a prolific resource for researchers in the last decade. Machine learning is among the technologies that have recently boomed in this field, with reinforcement learning among the currently various existing machine learning formats being one of those with the greatest evolution. The basis of this progress lies, to a large extent, in boosting reinforcement learning by deep learning and in the wealth of high-level frameworks that, with their specialized open-source libraries, have brought increasingly simple, powerful methods, and tools to both the academic community and practitioners. This paper aims to point out how the deep learning-reinforcement learning association, called deep reinforcement learningDeep reinforcement learning (DRL), impacts recent research works, particularly on one of the most representative problems in PPC, the job shopJob shop schedulingScheduling problem (JSSP), by means of identifying not only the main tools and approaches employed in its modellingModelling, implementation, and validation, but also the direction in which future research moves.