A quantified method for patent development map generation is suggested.The method identifies patents' semantic succession and technological topics.Latent Dirichlet allocation is used to identify sub-topics of a given technology.The method visualizes a 3D printing patent development map as its application.The method is an efficient monitoring tool for understanding evolving technologies. Patent development maps (PDMs) are a useful visual and monitoring tool for technology-trend identification, and therefore proper technology planning, because they provide an overall understanding of a technology's historical development and current stage. The rapid increase in technical data, however, has made it costly and time-consuming to monitor the technology development progress manually. Although some studies have suggested how to identify development paths among patents, little attention has been paid to synthetic consideration of the two core factors for PDMs: (1) the succession relationship among patents in terms of technological content and (2) the technological taxonomies of individual patents. Therefore, this paper suggests a semantic patent topic analysis-based bibliometric method for PDM generation.The method consists of (1) collecting and preprocessing patents, (2) structuring each patent into a term vector, (3) identifying the technological taxonomies of patents by applying latent Dirichlet allocation, and (4) visualizing the development paths among patents through sensitivity analyses based on semantic patent similarities and citations. This method is illustrated using patents related to 3D printing technology. This method contributes to quantifying PDM generation and, in particular, will become a useful monitoring tool for effective understanding of the technologies including massive patents.