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

Montiel, Oscar; Medina-Rodríguez, Nataly; Sepúlveda, Roberto; Melín, Patricia

doi:10.5772/50527

Cited by 14 publications

(8 citation statements)

References 33 publications

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“…In M1, the cost of the tour started at 1100mm and ended at 4117mm after a total of 108 iterations. In M2, the cost of the tour started at 7750mm and ended at 4900mm.The optimized cost of the tour for the omega plate problem is 4117mm and the optimal sequence by using proposed hybrid algorithm is [1,2,3,4,5,6,7,8,13,18,17,14,15,16,25,24,23,22,21,20,19,12,11,10,9, and 1], which has been obtained through memeplex 2 (M2).…”

Section: B Formulation Of Problem and Results Obtainedmentioning

confidence: 99%

“…The results achieved are compared with the results of MasterCAM and it is found that drilling time achieved by ACO is less than the time taken by MasterCAM in all case studies. ACO metaheuristic was also applied in [3] for optimization of circular pattern drilling problems. ACO results are compared with the results of MasterCAM and the improvement in the results achieved by ACO is around 62.27%.…”

Section: Methodsmentioning

confidence: 99%

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Application of Hybrid Sfla and Aco Algorithm to Omega Plate for Drilling Process Planning and Cost Management

Mehmood¹,

Umer²,

Asgher³

2022

AFST

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Tool traveling and tool switching time constitute almost seventy percent (70%) of the total time consumed in drilling process. This fact that 70% of the total time is nonproductive and does not add any value to the job, grabs attention of the researchers and the industrialist for optimization. A literature on drilling process revealed that very few studies have been done on hybridization of metaheuristics for optimization of tool travel time. This research gap is the motivation of the present study. In this study, two metaheuristic approaches – the shuffled frog leaping algorithm (SFLA) and ant colony optimization (ACO) were hybridized. With respect to hybridization of SFLA and ACO, this study signifies its originality and novelty in which main objective is to minimize the tool travel time. The literature review also revealed that the shortest path generated through commercially available software is not optimal all the time. This aspect emphasizes the application of metaheuristic algorithms on the real-world industrial problems. In this study, the proposed hybrid algorithm was applied to drilling of omega plate which is used in automobile manufacturing industry. The results of the proposed hybrid algorithm were compared with those of manual drilling path and software generated path. The results obtained through proposed hybrid algorithm were improved by 11.1% when compared to results of manual drilling path. The results of proposed algorithm were also better than results of commercial software Creo 6.0 and Siemens NX by 5.9% each. This showed that hybrid algorithm outperformed the commercially available software. This not only validates the efficacy of proposed hybrid algorithm, but also indicates the significance of the metaheuristic algorithm applications in industrial optimization problems.

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Section: B Formulation Of Problem and Results Obtainedmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Application of Hybrid Sfla and Aco Algorithm to Omega Plate for Drilling Process Planning and Cost Management

Mehmood¹,

Umer²,

Asgher³

2022

AFST

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“…A detailed literature review on HDPOP is presented by Dewil et al [9] and Abidin et al [10], in which various heuristic approaches proposed to solve HDPOP are listed. Considering both single and multi-tool hole drilling path optimization problems, well-known simulated annealing algorithm [12], tabu search algorithm [13] ant colony optimization algorithm [11,14,15], particle swarm optimization algorithm [16][17][18], genetic algorithm [19][20][21][22][23] are proposed. In addition to these algorithms, various recent algorithms are also implemented to HDPOP, such as biogeography based optimization [24], charged system search algorithm [25], hybrid cuckoo search-genetic algorithm [26], shuffled frog leaping algorithm [18], optimal foraging algorithm [27], etc.…”

Section: Introductionmentioning

confidence: 99%

Application of precedence constrained travelling salesman problem model for tool path optimization in CNC milling machines

Küçükoğlu

Gündüz

Balkancioglu³

et al. 2019

Int. J. Optim. Control, Theor. Appl. (IJOCTA)

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In this study, a tool path optimization problem in Computer Numerical Control (CNC) milling machines is considered to increase the operational efficiency rates of a company. In this context, tool path optimization problem of the company is formulated based on the precedence constrained travelling salesman problem (PCTSP), where the general form of the TSP model is extended by taking the precedence of the tool operations into account. The objective of the model is to minimize total idle and unnecessary times of the tools for internal operations. To solve the considered problem, a recent optimization algorithm, called Satin Bowerbird Optimizer (SBO), is used. Since the SBO is first introduced for the global optimization problems, the original version of the SBO is modified for the PCTSP with discretization and local search procedures. In computational studies, first, the performance of the proposed algorithm is tested on a well-known PCTSP benchmark problems by comparing the proposed algorithm against two recently proposed meta-heuristic approaches. Results of the comparisons show that the proposed algorithm outperforms the other two competitive algorithms by finding better results. Then, the proposed algorithm is carried out to optimize the hole drilling processes of three different products produced by the company. For this case, with up to 4.05% improvement on the operational times was provided for the real-life problem of the company. As a consequence, it should be noted that the proposed solution approach for the tool path optimization is capable of providing considerable time reductions on the CNC internal operations for the company.

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“…Many types of techniques, including a hybrid GA (Gupta et al, 2011), parallel ant colony (Montiel-Ross et al, 2012), and hybrid ant colony together with a GA (Abbas et al, 2014), have been used in previous studies. Research on path optimization has been inspired by not only biological phenomena but also physical phenomena.…”

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

Cited by 14 publications

References 33 publications

Application of Hybrid Sfla and Aco Algorithm to Omega Plate for Drilling Process Planning and Cost Management

Application of Hybrid Sfla and Aco Algorithm to Omega Plate for Drilling Process Planning and Cost Management

Application of precedence constrained travelling salesman problem model for tool path optimization in CNC milling machines

Path optimization of CNC PCB drilling using hybrid Taguchi genetic algorithm

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