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  HomeContents of Chinese Journal of Mechanical Engineering (English Edition),2006 No.1PART BUILDING ORIENTATION OPTIMIZATION METHOD IN STEREOLITHOGRAPHY

HONG Jun

State Key Lab for Manufacturing
System Engineering,

Xi’ an Jiaotong University,

Xi’ an 710049, China

 

WANG Wei

College of Missile,

PLA Air Force Engineering University,

Sanyuan 713800, China

 

TANG Yiping

State Key Lab for Manufacturing

System Engineering,

Xi’ an Jiaotong University,

Xi’ an 710049, China

 

 

PART BUILDING ORIENTATION
OPTIMIZATION METHOD IN

STEREOLITHOGRAPHY*

 

Abstract: Aiming at the part quality and building time problems in stereolithography (SL) caused by unreasonable building orientation, a part building orientation decision method in SL rapid prototyping (RP) is carried out. Bringing into full consideration of the deformation, stair-stepping effect, overcure effect and building time related to the part fabrication orientation, and using evaluation function method, a multi-objective optimization model for the building orientation is defined. According to the difference in the angles between normal vectors of triangular facets in standard triangulation language (STL) model and z axis, the expressions of deformation area, stair-stepping area, overcure area are established. According to the characteristics in SL process, part building time is divided into four sections, that is, hatching scanning time, outline scanning time, support building time and layer wait-ing time. Expressions of each building time section are given. Considering the features of this optimization model, genetic algorithm (GA) is used to derive the optimization objective, related software is developed and optimization results are tested through experiments. Application shows that this method can effectively solve the quality and efficiency troubles caused by unreasonable part building orientation, an automatic orientation-determining program is developed and verified through test.

Key words: Stereolithography (SL)  Rapid prototyping (RP)  Orientation optimization  Genetic algorithm (GA)

 


* This project is supported by National Hi-tech Research and Development Program of China (863 Program, No.2005AA414020). Received June 10, 2005; received in revised form September 2, 2005; accepted October 11, 2005

 

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