This paper presents a novel jerk minimization algorithm in the context of multi-axis flank CNC machining. The toolpath of the milling axis in a flank milling process, a ruled surface, is reparameterized by a B-spline function, whose control points and knot vector are unknowns in an optimization-based framework. The total jerk of the tool’s motion is minimized, implying the tool is moving as smooth as possible, without changing the geometry of the given toolpath. Our initialization stage stems from measuring the ruling distance metric (RDM) of the ruled surface. We show on several examples that this initialization reliably finds close initial guesses of jerk-minimizers and is also computationally efficient. The applicability of the presented approach is illustrated by some practical case studies.

本文提出了一种新的在多轴侧面CNC加工中的最小冲击率算法。侧面铣削过程中的铣削轴的刀具路径（直纹曲面）由B样条函数重新参数化，该函数的控制点和结矢量在基于优化的框架中是未知的。刀具运动的总跳动被最小化，这意味着刀具在不改变给定刀具路径的几何形状的情况下尽可能平稳地运动。我们的初始化阶段源于测量直纹曲面的标尺距离度量（RDM）。我们在几个示例上表明，此初始化可靠地找到了逼近最小化器的近似初始猜测，并且在计算上也很有效。通过一些实际案例研究说明了所提出方法的适用性。