分层实体制造激光头切割路径的建模与优化

分层实体制造(LOM)技术中分层制造时间是由该层的切割速度与切割路径确定的，当切割工艺参数(如：切割功率、切割速度)确定之后，每一层制造的时间是由该层切割(扫描)路径确定的。因此优化切割(扫描)路径对提高成型效率有重要意义，而分层实体制造技术中激光切割路径优化的实质是空行程路径的优化。建立了切割路径空行程路径优化的数学模型。由于求解该模型的复杂性，采用了分级规划的两个分步算法：首先用改进的最近邻域算法求解轮廓边界线上的切割起点，然后当切割点确定后把路径优化问题归结为旅行售货员问题(TSP)，采用了高效的智能仿生算法一蚁群系统算法来求解。运行结果表明，该算法显著缩短了分层制造中的空行程，提高了快速原型制造的效率。

Modeling and Optimizing Laser Torch Path in Laminated Object Manufacturing Technology

Layer manufacturing time in laminated object manufacturing (LOM) technology is determined by the cutting speed and cutting path of each layer. When the parameters of cutting process such as cutting power and cutting speed are defined, the manufacturing time of each layer is determined by the cutting (scanning) path. So it is most important to optimize the cutting path in order to improve the manufacturing efficiency. In LOM technology, laser cutting path optimization is in fact vacancy course path optimization. The mathematical model of vacancy course path optimization is set up in this paper. Because of the complexity of solving the model, the two algorithms of grading planning are presented: start points in cutting contour are solved by using an improved nearest neighbor algorithm; when start points are determined, the problem of the path optimization turns into the traveling salesman problem (TSP), which is solved by using an high-efficiency intellectual biological algorithm--the ant colony system algorithm. The results of algorithm show that the algorithm remarkably shortens vacancy course in LOM and the manufacturing efficiency of rapid prototyping is improved.