[Computer aided design and rapid manufacturing of removable partial denture frameworks].

Zhonghua Kou Qiang Yi Xue Za Zhi

Research Center of Engineering and Technology for Dental Computing, Ministry of Health, Peking University School and Hospital of Stomatology, Beijing 100081, China.

Published: August 2010

Objective: To introduce a method of digital modeling and fabricating removable partial denture (RPD) frameworks using self-developed software for RPD design and rapid manufacturing system.

Methods: The three-dimensional data of two partially dentate dental casts were obtained using a three-dimensional crossing section scanner. Self-developed software package for RPD design was used to decide the path of insertion and to design different components of RPD frameworks. The components included occlusal rest, clasp, lingual bar, polymeric retention framework and maxillary major connector. The design procedure for the components was as following: first, determine the outline of the component. Second, build the tissue surface of the component using the scanned data within the outline. Third, preset cross section was used to produce the polished surface. Finally, different RPD components were modeled respectively and connected by minor connectors to form an integrated RPD framework. The finished data were imported into a self-developed selective laser melting (SLM) machine and metal frameworks were fabricated directly.

Results: RPD frameworks for the two scanned dental casts were modeled with this self-developed program and metal RPD frameworks were successfully fabricated using SLM method. The finished metal frameworks fit well on the plaster models.

Conclusions: The self-developed computer aided design and computer aided manufacture (CAD-CAM) system for RPD design and fabrication has completely independent intellectual property rights. It provides a new method of manufacturing metal RPD frameworks.

Download full-text PDF

Source

Publication Analysis

Top Keywords

rpd frameworks
20
rpd design
12
rpd
10
aided design
8
design rapid
8
rapid manufacturing
8
removable partial
8
partial denture
8
self-developed software
8
dental casts
8

Similar Publications

Adaptation of maxillary removable partial denture frameworks fabricated with a direct digital workflow: A randomized crossover clinical trial.

J Dent

January 2025

Department of Prosthodontics, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; Shanghai, 200011, China; College of Stomatology, Shanghai Jiao Tong University, National Center for Stomatology, National Clinical Research Center for Oral Diseases, Shanghai Key Laboratory of Stomatology, Shanghai Research Institute of Stomatology, Shanghai, 200011, China; Department of Stomatology, Fengcheng Hospital of Fengxian District, Shanghai, 201418, China. Electronic address:

Objectives: To compare the adaptation of maxillary removable partial denture (RPD) frameworks fabricated through direct digital workflows with that of traditional cast frameworks and indirect digital frameworks.

Methods: The workflow for fabricating the digital cobalt-chromium framework encompassed intraoral scanning (IOS) using Trios 3, computer-aided survey and design, and subsequently either the lost-wax technique from a printed resin framework pattern (Framework B) or direct selective laser melting (SLM) (Framework C). The traditional cast framework (Framework A) was selected as a control.

View Article and Find Full Text PDF

Evaluation of Retentive Forces in Three Types of Removable Partial Denture Framework Materials: An In Vitro Study.

Cureus

December 2024

Dentistry, Kurdistan Higher Council of Medical Specialties, Erbil, IRQ.

Introduction The utilization of Computer-Aided Design and Computer-Aided Manufacturing (CAD/CAM) technology in the production of polyetheretherketone (PEEK) and acetal frameworks enhances the precision and stability of partial denture frameworks. This study evaluates the retentive forces of CAD/CAM-fabricated PEEK, acetal, and cobalt-chromium (Co-Cr) frameworks in removable partial dentures (RPDs). Methods Forty-five frameworks were fabricated (15 each of PEEK, acetal, and Co-Cr) and tested for retentive forces using a universal testing machine at a crosshead speed of 5 mm/min.

View Article and Find Full Text PDF

Background: Computer-assisted learning (CAL) has the potential to enhance learning outcomes and satisfaction. However, there are limited reports in the literature that describe or evaluate the implementation of this method to promote competency-based learning in removable partial denture (RPD) design. Therefore, this study aimed to: (1) compare the effectiveness of different learning methods using a 3D software-aided RPD design program, (2) evaluate the learning outcomes associated with these different methods following active learning, and (3) assess students' satisfaction.

View Article and Find Full Text PDF

Objectives: To assess the effect of occlusion and implant number/position on stress distribution in Kennedy Class II implant-assisted removable partial denture (IARPD).

Materials And Methods: IARPDs were designed in six models: with one implant (bone level with a platform of 4 mm and length of 10 mm) at the site of (I) canine, (II) between first and second premolars, (III) first molar, (IV) second molar, or two implants at the sites of (V) canine-first molar, and (VI) canine-second molar. A conventional RPD served as control.

View Article and Find Full Text PDF

Soil cadmium (Cd) contamination significantly threatens ecosystems and human health. Traditional geochemical investigation, although accurate, is impractical for wide-area and frequent monitoring applications. Multi-spectral satellite images combined with the homologous pollution information (HPI) and the spectral and content information of soil organic matter (SOMSCI) is an unconventional and promising approach for large-scale, dynamic soil heavy metal (SHM) monitoring.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!