Pre-processing methodology for optimizing stereolithography apparatus build performance

The performance of a rapid prototyping technology depends, to a great extent, on the way parts are oriented and packed on the machine's build platform. The present work focuses on stereolithography systems. It describes a pre-processing methodology that 'automates' the procedure of finding 'good' fabrication orientations and packing arrangements. The method proposed consists of two separate, but interrelated, stages: the orientation and the packing stage. At first, each part is appropriately oriented to achieve better surface quality and either minimal support structure or lower build time or minimal projection area. The second stage considers the projections of the parts on the fabrication platform. The associated 2D bin-packing problem is addressed by a genetic algorithm in conjunction with a new improved placement rule. The performance of the present approach is demonstrated via two sets of case studies, which concern simple nearly orthogonal-shaped parts and representative 'real-world' objects/parts.

[1]  David Casasent Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling , 1995 .

[2]  S. Jakobs,et al.  European Journal Ofoperational Research on Genetic Algorithms for the Packing of Polygons , 2022 .

[3]  E. Hopper,et al.  A genetic algorithm for a 2D industrial packing problem , 1999 .

[4]  Tzung-Pei Hong,et al.  Evolution of Appropriate Crossover and Mutation Operators in a Genetic Process , 2001, Applied Intelligence.

[5]  Kathryn A. Dowsland,et al.  An algorithm for polygon placement using a bottom-left strategy , 2002, Eur. J. Oper. Res..

[6]  David W. Rosen,et al.  A process planning method for improving build performance in stereolithography , 2001, Comput. Aided Des..

[7]  Shuo-Yan Chou,et al.  Determining fabrication orientations for rapid prototyping with Stereolithography apparatus , 1997, Comput. Aided Des..

[8]  K. Dowsland,et al.  Solution approaches to irregular nesting problems , 1995 .

[9]  George K. Knopf,et al.  A moment based metric for 2-D and 3-D packing , 2000, Eur. J. Oper. Res..

[10]  Lance D. Chambers Practical handbook of genetic algorithms , 1995 .

[11]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[12]  J. Giannatsis,et al.  A study of the build-time estimation problem for Stereolithography systems , 2001 .

[13]  George K. Knopf,et al.  Serial packing of arbitrary 3D objects for optimizing layered manufacturing , 1998, Other Conferences.

[14]  Hongfei Teng,et al.  An improved BL-algorithm for genetic algorithm of the orthogonal packing of rectangles , 1999, Eur. J. Oper. Res..

[15]  Tzung-Pei Hong,et al.  Simultaneously Applying Multiple Mutation Operators in Genetic Algorithms , 2000, J. Heuristics.

[16]  E. Hopper,et al.  An empirical investigation of meta-heuristic and heuristic algorithms for a 2D packing problem , 2001, Eur. J. Oper. Res..

[17]  Seok-Hee Lee,et al.  Determination of fabricating orientation and packing in SLS process , 2001 .

[18]  Marvin D. Troutt,et al.  Applications of genetic search and simulated annealing to the two-dimensional non-guillotine cutting stock problem , 2001 .

[19]  Anikó Ekárt,et al.  Genetic algorithms in computer aided design , 2003, Comput. Aided Des..