Optimization of cutting trajectory to improve manufacturing time in computer numerical control machine using ant colony algorithm

This article presents a novel method to construct an autonomous, intelligent computer-aided design/computer-aided manufacturing programming system for the cutting device controller (e.g. a computer numerical control laser cutting machine tool) based on ant colony algorithm. The computer numerical control cutting device should be able to optimize trajectory autonomously between cutting objects. In order to find the best sequence of operations that achieves the shortest trajectory, ant colony is proposed. The shortest cutting trajectory can be formulated as a special case of traveling salesman problem. The integration of ant colony algorithm and traveling salesman problem can be included in commercial computer-aided design/computer-aided manufacturing packages to optimize the cutting trajectory.

[1]  Shyi-Ming Chen,et al.  Solving the traveling salesman problem based on the genetic simulated annealing ant colony system with particle swarm optimization techniques , 2011, Expert Syst. Appl..

[2]  Thomas Stützle,et al.  Estimation-based ant colony optimization and local search for the probabilistic traveling salesman problem , 2009, Swarm Intelligence.

[3]  Yuan-bin Mo The Advantage of Intelligent Algorithms for TSP , 2010 .

[4]  Juan José Salazar González,et al.  The multi‐commodity pickup‐and‐delivery traveling salesman problem , 2014, Networks.

[5]  Marco César Goldbarg,et al.  Particle Swarm for the Traveling Salesman Problem , 2006, EvoCOP.

[6]  Alfonsas Misevičius,et al.  USING ITERATED TABU SEARCH FOR THE TRAVELING SALESMAN PROBLEM , 2015 .

[7]  Z-H Xiong,et al.  Curvilinear tool path generation for pocket machining , 2011 .

[8]  Mauro Birattari,et al.  On the Invariance of Ant Colony Optimization for the Traveling Salesman Problem , 2006 .

[9]  Bruce L. Golden,et al.  The hierarchical traveling salesman problem , 2013, Optim. Lett..

[10]  Carlos Relvas,et al.  Optimization of computer numerical control set-up parameters to manufacture rapid prototypes , 2004 .

[11]  J.E.A. Qudeiri,et al.  Optimization Hole-Cutting Operations Sequence in CNC Machine Tools Using GA , 2006, 2006 International Conference on Service Systems and Service Management.

[12]  João Paulo Davim,et al.  Application of radial basis function neural networks in optimization of hard turning of AISI D2 cold-worked tool steel with a ceramic tool , 2007 .

[13]  J. Balic,et al.  Evolutionary programming of a CNC cutting machine , 2003 .

[14]  Asoke Kumar Bhunia,et al.  Genetic algorithm for asymmetric traveling salesman problem with imprecise travel times , 2011, J. Comput. Appl. Math..

[15]  Miran Brezocnik,et al.  Evolutionary programming of CNC machines , 2005 .

[16]  Xin-She Yang,et al.  Discrete cuckoo search algorithm for the travelling salesman problem , 2014, Neural Computing and Applications.

[17]  Wen Z Ding,et al.  Effect of trajectory-controlled algorithm on the mechatronical performance of high-speed machining , 2013 .

[18]  Zehui Shao,et al.  An Effective Simulated Annealing Algorithm for Solving the Traveling Salesman Problem , 2009 .

[19]  David M Ochoa,et al.  A method for generating trochoidal tool paths for 2½D pocket milling process planning with multiple tools , 2013 .

[20]  Ming Luo,et al.  Material removal process optimization for milling of flexible workpiece considering machining stability , 2011 .

[21]  Evgueni V. Bordatchev,et al.  Process planning for corner machining based on a looping tool path strategy , 2011 .

[22]  Kenji Shimada,et al.  The travelling salesman problem with neighbourhoods: MINLP solution , 2013, Optim. Methods Softw..

[23]  Xuerong Feng,et al.  An overall-regional competitive self-organizing map neural network for the Euclidean traveling salesman problem , 2012, Neurocomputing.

[24]  Fulya Altiparmak,et al.  New integer linear programming formulation for the traveling salesman problem with time windows: minimizing tour duration with waiting times , 2013 .