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Process parameters optimization for area-forming rapid prototyping system

Process parameters optimization for area-forming rapid prototyping system Purpose – The aim of this study is to optimize the process parameters of area-forming rapid prototyping system to improve the model dimensional repeatability and to minimize the process time as well. Design/methodology/approach – Model dimensional repeatability is based on the dimensional standard deviation of the test sample. The significant factors that affect the model dimensional repeatability and process time are established by the fractional factorial design. Response surface methodology, based on the central composite design, is applied to evaluate the regression models of the response variables including prototype’s dimensional repeatability and processing time. Finally, a desirability function for each individual response variables is constructed to obtain the optimal process parameters. Findings – The significant factors that have an impact on the main effects of response variables model dimensional repeatability and process time found by the fractional factorial design are curing time, light flux and platform moving velocity. Originality/value – All previous studies were concerned with product accuracy in area-forming rapid prototyping system. In this work, we focus on optimization of model dimensional repeatability. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Rapid Prototyping Journal Emerald Publishing

Process parameters optimization for area-forming rapid prototyping system

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1355-2546
DOI
10.1108/RPJ-12-2012-0114
Publisher site
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Abstract

Purpose – The aim of this study is to optimize the process parameters of area-forming rapid prototyping system to improve the model dimensional repeatability and to minimize the process time as well. Design/methodology/approach – Model dimensional repeatability is based on the dimensional standard deviation of the test sample. The significant factors that affect the model dimensional repeatability and process time are established by the fractional factorial design. Response surface methodology, based on the central composite design, is applied to evaluate the regression models of the response variables including prototype’s dimensional repeatability and processing time. Finally, a desirability function for each individual response variables is constructed to obtain the optimal process parameters. Findings – The significant factors that have an impact on the main effects of response variables model dimensional repeatability and process time found by the fractional factorial design are curing time, light flux and platform moving velocity. Originality/value – All previous studies were concerned with product accuracy in area-forming rapid prototyping system. In this work, we focus on optimization of model dimensional repeatability.

Journal

Rapid Prototyping Journal – Emerald Publishing

Published: Jan 19, 2015

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