五軸側銑被廣泛應用於直紋曲面的加工，包括汽車、航太、模具與能源等產業的關鍵零件。其刀具路徑規劃能轉換為數學規劃問題，透過全域最佳化演算法求解，藉此降低曲面的加工誤差。然而轉換後的問題具有高維度、高度非線性的特性，以往研究嘗試使用粒子群最佳化演算法、遺傳演算法、螞蟻演算法等方法，然而求解過程的計算效率，或是收斂解的品質仍然不佳。有鑒於此，本研究基於統計相關方法，針對直紋曲面的五軸側銑加工，發展進階式刀具路徑規劃方法，以提出有效的解決方案。目的為簡化搜尋空間提高計算效率，並改善最佳解的品質。分別完成「以類電磁演算法為基之路徑規劃」、「以抽樣技術為基之迭代式路徑規劃」、「多層次簡化解空間」與「基於公差分布之路徑規劃」等具體工作。根據代表性曲面產生的刀具路徑，進行模擬測試，驗證提出方法的效能。本研究兼具學理創新與應用價值，發揮基於全域最佳化之路徑規劃的優勢，不僅有效控制加工曲面的誤差，亦提供新穎的路徑規劃模式，提升複雜幾何的製造技術水準。

5-axis flank machining has received much attention in various industries since the late 90s. This advanced machining operation is particularly suitable in manufacturing complex components such as turbine blades, compressors, molds, and automobile as well as aerospace structure parts. With two rotational degrees of freedom in the cutter motion, 5-axis flank machining offers superior shaping capability and reduces part handling tasks compared to traditional 3-axis machining. However, tool path planning becomes complicated, as the cutter is likely to collide with objects in the machining environment. Past studies tried to use meta-heuristic methods to solve this problem, such as particle swarm optimization, genetic algorithm, and ant colony optimization, but the search process is lack of efficiency and the solution quality is sometimes not acceptable. Thus, this research develops advanced tool path planning methods based on statistical techniques and completes the following tasks: “Electromagnetism-Like Algorithms for Optimized Tool Path Planning,” “Iterative Optimization of Tool Path Planning by Integrating Sampling Techniques,” “Multilevel Simplification of Solution Space in 5-Axis Flank Machining,” and “ Tool Path Planning based on Distribution of Tolerances.” Simulation results of representative test surfaces validate the effectiveness of the proposed methods. This work provides a feasible approach to controlling machining errors, which enhances the practical values of 5-axis CNC machining technologies.

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