ABSTRACT Process planning for sheet metal bending involves the determination of a near-optimal bend sequence for a given part. The problem is complex since the search space of possible solutions is factorial with respect to the number of bends. In this paper, a two-stage algorithm is described that allows for the quick identification of a near-optimal bend sequence for a given part and set of tools. In the first stage, a Bend Feasibility Matrix is constructed to map the entire search space by taking a geometric approach to the problem. The matrix helps to quickly establish whether the part can be manufactured using the given set of tools. The second stage uses best-first search (graph) algorithm to identify the bend sequence. During search, infeasible sequences are never evaluated and expensive collision tests are not done since the necessary computations are already done in the first stage. Performance of the proposed algorithm is compared with that of genetic algorithm and it is demonstrated that the best-first search algorithm is better than genetic algorithm (GA) to solve the bend sequencing problem.

中文翻译：

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基于几何的折弯可行性矩阵，用于钣金零件的折弯顺序规划

摘要 钣金折弯的工艺规划涉及为给定零件确定接近最佳的折弯顺序。这个问题很复杂，因为可能解决方案的搜索空间是关于弯曲数量的阶乘。在本文中，描述了一种两阶段算法，该算法允许快速识别给定零件和一组工具的近乎最佳的折弯顺序。在第一阶段，通过对问题采取几何方法，构建弯曲可行性矩阵以映射整个搜索空间。该矩阵有助于快速确定是否可以使用给定的一组工具制造零件。第二阶段使用最佳优先搜索（图形）算法来识别弯曲序列。在搜索过程中，永远不会评估不可行的序列，也不会进行昂贵的碰撞测试，因为必要的计算已经在第一阶段完成。将所提算法的性能与遗传算法进行了比较，证明了最佳优先搜索算法在解决弯曲排序问题上优于遗传算法(GA)。