Abstract
Additive manufacturing (AM) or 3D printing has become one of the most popular technologies in the world. AM technology is capable 0of manufacturing regular as well as irregular shapes for small batches of customized products. The ability to customize unusually curved and rounded shapes makes the process particularly suitable for prosthetic products used in biomedical applications. These AM applications have created a substantial and sustainable market opportunity. This research develops a patent analysis algorithm based on R language to explore AM technology development trends applied in the biomedical field. First, the related patents are collected from a global patent database. Next, the key terms are extracted dynamically using text mining. This research derives a key terms selecting rule in order to reduce the bias of choosing similar terms. The extracted key terms form the base for similarity analysis and cluster validation. After cluster validation, the best clustering parameters are set to create clusters. According to the clustering result, some adjustments are made to refine the results into meaningful sets. Finally, the adjusted clustering result is used an import for patent evolution analysis which graphically displays the technology development trends. The patent evolution figure helps identify potential R&D opportunities in this technical field. The research provides a patent analysis algorithm based on R language, and this algorithm helps to extract information from patent documents to depict the trends of patent development. The extracted information and the trends of patent development help researchers and policy analysts formulate development strategies while avoiding patent infringement litigation.