Three-dimensional (3D) printers are widely used in rapid prototyping and mass customization. However, capacity planning for 3D printers is challenging because 3D printers are usually not dedicated, and estimating the demand for their capacity is not easy. To overcome this problem, in this study, a consistent-decomposition (CD) fuzzy-analytic-hierarchy-process (FAHP) approach is proposed. This approach extracts the various viewpoints of a capacity planner by decomposing his or her fuzzy judgment matrix into several fuzzy subjudgment matrices. On the basis of each fuzzy subjudgment matrix, the performances of various 3D printers are assessed and compared. The best-performing 3D printer from each viewpoint is chosen. The proposed methodology has been applied to a real-world case in which a diverse set of 3D printers was acquired by a manufacturer. The proposed methodology returned a diverse set of optimal 3D printers, whereas a competing set chosen using any existing method lacked diversity. In addition, a decision maker who applied the proposed methodology did not need to specify different requirements for various types of 3D printers.