Use this URL to cite or link to this record in EThOS:
Title: The selection of rapid prototyping processes based on feature extraction from STL models
Author: Wang, Yun-Feng
ISNI:       0000 0001 3562 4188
Awarding Body: Kingston University
Current Institution: Kingston University
Date of Award: 2000
Availability of Full Text:
Access from EThOS:
Access from Institution:
Rapid Prototyping & Manufacturing has recently emerged as a new manufacturing technology that allows the rapid creation of three-dimensional models and prototypes. It automates the fabrication of solid objects directly from designs created by CAD systems, without part-specific tooling or human intervention. From visualising designs to generating production tooling, the Rapid Prototyping & Manufacturing gives the advantages needed in today's competitive environment. There are many different rapid prototyping systems available. This proliferation of rapid prototyping systems has, to some degree, created some confusion in the market place. Whether the potential customer or user is thinking of using a rapid prototyping bureaux or purchasing a rapid prototyping system, the increasing number of systems coming onto the market and the ever improving capabilities of existing systems presents a significant problem in choosing the optimum system for a particular need. The aim of this project is to develop an intelligent rapid prototyping system selector based on the feature extraction from STL files to automatically select the most suitable rapid prototyping system for a given prototype. The combination of STL model feature extraction and expert system selection is an effective method of rapid prototyping process selection. By analysing the object's STL file, the object's feature representations are extracted. These features together with the user's requirements are used to determine the most suitable system on which to build, or the most suitable system to buy. Mathematical models for computing build time, accuracy, cost and mechanical properties are established. A knowledge-based system is developed for rapid prototyping system selection. An integrated software package for STL file feature extraction, rapid prototyping system simulation and knowledge-based rapid prototyping system selection has been developed.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Mechanical, aeronautical and manufacturing engineering