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Electromagnetism-like algorithms for optimized tool path planning in 5-axis flank machining
Affiliation:1. Department of Industrial Engineering and Engineering Management, National Tsing-Hua University, Hsinchu, Taiwan;2. State Key Lab of Digital Manufacturing Equipment & Technology, Huazhong University of Science & Technology, Wuhan, China;1. University of North Carolina at Charlotte, Charlotte, NC, USA;2. Los Alamos National Laboratory, Los Alamos, NM, USA;1. Department of Computer Science, Technion, Israel;2. King Abdullah University of Science and Technology, Saudi Arabia;3. Institute of Discrete Mathematics and Geometry, TU Wien, Austria;1. The University of British Columbia, Department of Mechanical Engineering, Manufacturing Automation Laboratory, 2054-6250 Applied Science Lane, Vancouver, BC V6T 1Z4, Canada;2. State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai 200240, PR China;1. School of Mechanical Engineering, University of Birmingham, Edgbaston B15 2TT, UK;2. School of Mechanical Engineering, University of Bath, Bath BA2 7AY, UK;1. School of Computer Science and Technology, Harbin Institute of Technology, West Wenhua Street 2, 264209 Weihai, China;2. BCAM — Basque Center for Applied Mathematics, Alameda de Mazarredo 14, 48009 Bilbao, Basque Country, Spain;3. ModuleWorks GmbH, Henricistr. 50, 52072 Aachen, Germany;4. Center for Geometry and Computational Design, Vienna University of Technology, Wiedner Hauptstr. 8-10/104, A-1040 Vienna, Austria
Abstract:
Optimization of tool path planning using metaheuristic algorithms such as ant colony systems (ACS) and particle swarm optimization (PSO) provides a feasible approach to reduce geometrical machining errors in 5-axis flank machining of ruled surfaces. The optimal solutions of these algorithms exhibit an unsatisfactory quality in a high-dimensional search space. In this study, various algorithms derived from the electromagnetism-like mechanism (EM) were applied. The test results of representative surfaces showed that all EM-based methods yield more effective optimal solutions than does PSO, despite a longer search time. A new EM-MSS (electromagnetism-like mechanism with move solution screening) algorithm produces the most favorable results by ensuring the continuous improvement of new searches. Incorporating an SPSA (simultaneous perturbation stochastic approximation) technique further improves the search results with effective initial solutions. This work enhances the practical values of tool path planning by providing a satisfactory machining quality.
Keywords:Electromagnetism-like mechanism algorithm  5-axis machining  Flank milling  Tool path planning
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