This study conducts a systematic literature review to explore the current state of the art of evolvable KGs in manufacturing, which have an important role in the era of Industry 4.0 and 5.0. These KGs leverage both machine learning algorithms and human expertise to enhance decision-making, operational efficiency, and predictive maintenance capabilities. Despite the advancements, challenges persist in quality assurance, process planning, and the integration of human expertise. Our findings advocate for the necessity of addressing these issues to foster wider adoption and optimization of KG technologies in manufacturing. Evolvable KGs address the changing nature of knowledge. We map existing literature based on the KGC process stages. By deepening the understanding of how KGs can evolve, this review sets the base for future research aimed at developing more dynamic and intelligent systems tailored to the emerging demands of Industry 5.0.