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COMPARISON OF THE SUCCESS OF META-HEURISTIC ALGORITHMS IN TOOL PATH PLANNING OF COMPUTER NUMERICAL CONTROL MACHINE

ÇAÅžKA Serkan, Kadir Gã–k and Arif Gã–k
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ÇAŞKA Serkan: Department of Mechanical Engineering, Hasan Ferdi Turgutlu Technology Faculty, Manisa Celal Bayar University, 45300 Manisa, Turkey
Kadir Gã–k: ��Department of Biomedical Engineering, Engineering and Architecture Faculty, İzmir Bakircay University, 35660 İzmir, Turkey
Arif Gã–k: ��Department of Industrial Design, Architecture Faculty, Kutahya Dumlupinar University, 43000 Kutahya, Turkey

Surface Review and Letters (SRL), 2022, vol. 29, issue 09, 1-9

Abstract: Carrying out an engineering process with the least cost and within the shortest time is the basic purpose in many fields of industry. In Computer Numerical Control (CNC) machining, performing a process by following a certain order reduces cost and time of the process. In the literature, there are research works involving varying methods that aim to minimize the length of the CNC machine tool path. In this study, the trajectory that the CNC machine tool follows while drilling holes on a plate was discussed within the Travelling Salesman Problem (TSP). Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Grey Wolf Optimizer (GWO) methods were used to solve TSP. The case that the shortest tool path was obtained was determined by changing population size parameter in GA, PSO, and GWO methods. The results were presented in tables.

Keywords: Computer numerical control machine; genetic algorithms; particle swarm optimization; grey wolf optimizer; travelling salesman problem (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0218625X22501268

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