Optimization Hole-Cutting Operations Sequence in CNC Machine Tools Using GA

Qudeiri, Jaber Abu; Almomani, Raid; Jamali, Mohamed Anouar; Yamamoto, Hidehiko

doi:10.1109/icsssm.2006.320513

Cited by 8 publications

(9 citation statements)

References 10 publications

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“…Furthermore, Lim et al (2012Lim et al ( , 2014 used cuckoo search (CS), which was inspired by the egg selection method of the cuckoo, for searching for the shortest CNC drilling path. Genetic algorithms (GAs), which are classical searching methods, have been developed for obtaining the optimal path (Al-Sahib and Abdulrazzaq, 2014;Mansour et al, 2013;Qudeiri et al, 2006Qudeiri et al, , 2013.…”

Section: Introductionmentioning

confidence: 99%

Path optimization of CNC PCB drilling using hybrid Taguchi genetic algorithm

Al-Janan

Liu

2016

Kybernetes

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Purpose – In this study, the hybrid Taguchi genetic algorithm (HTGA) was used to optimize the computer numerical control-printed circuit boards drilling path. The optimization was performed by searching for the shortest route for the drilling path. The number of feasible solutions is exponentially related to the number of hole positions. The paper aims to discuss these issues. Design/methodology/approach – Therefore, a traveling cutting tool problem (TCP), which is similar to the traveling salesman problem, was used to evaluate the drilling path; this evaluation is considered an NP-hard problem. In this paper, an improved genetic algorithm embedded in the Taguchi method and a neighbor search method are proposed for improving the solution quality. The classical TCP problems proposed by Lim et al. (2014) were used for validating the performance of the proposed algorithm. Findings – Results showed that the proposed algorithm outperforms a previous study in robustness and convergence speed. Originality/value – The HTGA has not been used for optimizing the drilling path. This study shows that the HTGA can be applied to complex problems.

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Section: Introductionmentioning

confidence: 99%

Path optimization of CNC PCB drilling using hybrid Taguchi genetic algorithm

Al-Janan

Liu

2016

Kybernetes

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“…However, there are some other researches that have studied the traveling time using various methods. [6][7][8][9] By minimizing cutting trajectory between objects, the travel time will be minimized correspondingly.…”

Section: Introductionmentioning

confidence: 99%

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

Kiani

Sharifi

Shakeri

2013

Proceedings of the Institution of Mechanical Engineers, Part B:

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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.

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“…The total production time to cut any part using CNC machine tools consists of a travel time [9,19], which is the time to move the CNC machine spindle between operations, switch time, which is the time to change the tool for the next operation, and the cutting time, which is the time that the tool moves with cutting speed in the air or on material. Our purpose is to minimize the CTTP based on P-ACO.…”

Section: Cnc Tool Path Generationmentioning

confidence: 99%

“…A number of commercial CAD/CAD packages that provide automatic NC programming have been developed and applied to various cutting processes. To cut any process using CNC machine tools, a tool path for the CTTP should be determined [9].…”

Section: Cnc Tool Path Generationmentioning

confidence: 99%

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Methodology to Optimize Manufacturing Time for a CNC Using a High Performance Implementation of ACO

Montiel

Medina-Rodríguez

Sepúlveda

et al. 2012

International Journal of Advanced Robotic Systems

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In this paper, an efficient methodology to generate optimal and/or quasi-optimal sequences of G commands to minimize the manufacturing time is presented. Our solution starts from original G codes provided by application CAD/CAM software. Here, first we tackled the problem of reducing the time of the travel path for drilling of an industrial robotic manufacturing machine. The methodology can be easily implemented for free distribution or commercial CAD/CAM software without achieving any modification to it. Several experiments that demonstrate how this proposal can help to outperform solutions provided by application software are presented, consistent improvements around 62% were obtained. Moreover, for optimizing the time along the travel path, we present a high performance implementation of Ant Colonies (ACO) known as Parallel ACO (P-ACO) that allows achieving the optimization task efficiently by speeding up the original ACO. A Graphical User Interface that integrates the whole process is shown.

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Optimization Hole-Cutting Operations Sequence in CNC Machine Tools Using GA

Cited by 8 publications

References 10 publications

Path optimization of CNC PCB drilling using hybrid Taguchi genetic algorithm

Path optimization of CNC PCB drilling using hybrid Taguchi genetic algorithm

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

Methodology to Optimize Manufacturing Time for a CNC Using a High Performance Implementation of ACO

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