Build Orientation Optimization Problem in Additive Manufacturing
Additive manufacturing (AM) is an emerging type of production technology to create three-dimensional objects layer-by-layer directly from a 3D CAD model. AM is being extensively used by engineers and designers. Build orientation is a critical issue in AM since it is associated with the object accura...
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          | Published in | Computational Science and Its Applications - ICCSA 2018 Vol. 10961; pp. 669 - 682 | 
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| Main Authors | , , | 
| Format | Book Chapter Conference Proceeding | 
| Language | English | 
| Published | 
        Switzerland
          Springer International Publishing AG
    
        2018
     Springer International Publishing  | 
| Series | Lecture Notes in Computer Science | 
| Subjects | |
| Online Access | Get full text | 
| ISBN | 9783319951645 3319951645 9783319951652 3319951653  | 
| ISSN | 0302-9743 1611-3349 1611-3349  | 
| DOI | 10.1007/978-3-319-95165-2_47 | 
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| Summary: | Additive manufacturing (AM) is an emerging type of production technology to create three-dimensional objects layer-by-layer directly from a 3D CAD model. AM is being extensively used by engineers and designers. Build orientation is a critical issue in AM since it is associated with the object accuracy, the number of supports required and the processing time to produce the object. Finding the best build orientation in the AM will reduced significantly the building costs and will improve the object accuracy. This paper presents an optimization approach to solve the part build orientation problem considering the staircase effect, support area characteristics and the build time. Two global optimization methods, the Electromagnetism-like and the Stretched Simulated Annealing algorithms, are used to study the optimal orientation of four models. Preliminary experiments show that both optimization methods can effectively solve the build orientation problem in AM, finding several global solutions. | 
|---|---|
| ISBN: | 9783319951645 3319951645 9783319951652 3319951653  | 
| ISSN: | 0302-9743 1611-3349 1611-3349  | 
| DOI: | 10.1007/978-3-319-95165-2_47 |