The selection of rapid prototyping processes based on feature extraction from STL models

  • Yun-Feng Wang

Research output: ThesisDoctoral thesis

Abstract

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.
Original languageEnglish
QualificationDoctor of Philosophy (PhD)
Awarding Institution
  • Kingston University
Publication statusAccepted/In press - 2000
Externally publishedYes

Bibliographical note

Department: School of Mechanical, Aeronautical and Production Engineering

Physical Location: This item is held in stock at Kingston University Library.

Keywords

  • Mechanical, aeronautical and manufacturing engineering

PhD type

  • Standard route

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