Minimizing the Number of Transitions of 3D Printing Nozzles Using a Traveling-Salesman-Problem Optimization Model

Liu, Hao; Li, Rui; Liu, Zhoupeng; Xu, Shuhao

doi:10.1007/s12541-021-00512-2

Cited by 12 publications

(5 citation statements)

References 45 publications

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“…The hashed printing areas of the same robot are merged into the last combination with only the same robot task, resulting in an integrated printing combination. Taking an optimized path combination as an example ([13,22,1,20] [23,8,18]、 [24]、 [19]), 1-15 represents task region A, 16-24 represents task region B, 0 represents the rotation of the platform, and [13,22,1,20] represents a round of cooperative printing region. Due to the spatial constraint strategy of the global optimization algorithm, [2], [4], [10], [12], [9], [7], [5], [14], and [15] belonging to the same task are distributed in different cooperative combinations.…”

Section: Regional Integrationmentioning

confidence: 99%

“…Adding a breakpoint in the middle of a printing area will degrade the print quality. Therefore, the tool path for each printing area should be treated as an indivisible individual [18]. Regarding collision detection, Choi [10] proposed an envelope area method that determines whether a collision occurs by detecting the overlap of envelope areas, which simplifies the difficulty of collision detection.…”

Section: Introductionmentioning

confidence: 99%

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Research on dual-robot cooperative path planning for multi-material additive manufacturing

Li,

Wei

et al. 2024

Preprint

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To improve the efficiency of multi-material additive manufacturing and enhance the safety of multi-robot cooperative printing with uncertain execution delay, a dual-robot cooperative path planning method is proposed for the layer-by-layer printing mode. In the proposed algorithm, the description of the printing region is reconstructed by simply using the rectangular envelope region and two-dimensional directed line segment, and the adjacency list of the printing region is established to guide the optimization direction. Therefore, redundant information about the printing region is effectively removed, which is conducive to the optimization of the problem. A multi-round cooperation strategy with multiple synchronous starting points is proposed to accommodate uncertain execution delays by separating the space of the dual-robot printing area, so as to avoid the potential collision risk of dual-robot. To further optimize the printing efficiency, local strategies are used to reduce the makespan. Hence, a better printing order can be obtained, and states of cooperative and non-cooperative printing processes can be unified. In addition, the corresponding NC control strategy is designed for the industrial application of the cooperative strategy. The simulation result shows that this method can effectively reduce the makespan of dual-robot cooperative additive manufacturing, and accommodate the uncertain execution delay of the dual-robot.

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Section: Regional Integrationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on dual-robot cooperative path planning for multi-material additive manufacturing

Li,

Wei

et al. 2024

Preprint

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show abstract

“…For example, in the process of 3D printing, there is a need to minimize the transitions of the printhead from the endpoint of the path to the starting point, which reduces the deteriorating print quality. The endpoints of the line segments can be considered as "cities" in the transformation of the problem of minimizing the number of transitions to the traveling salesman problem [2].…”

Section: Introductionmentioning

confidence: 99%

Algorithm of ant colony optimization (ACO) for 3D variation traveling salesman problem

Riabko

Заїка

Kukharchuk

et al. 2022

J. Phys.: Conf. Ser.

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The article discusses the solution of the spatial traveling salesman problem (TSP 3D variation) using Ant Colony Optimization (ACO). The traveling salesman problem considers n bridges and a matrix of pairwise distances between them. It is necessary to find such an order of visiting cities so that the total distance traveled was minimal, each city was visited exactly once and the salesman returned to the city from which he began his route. In the TSP 3D variation problem, each “city” has 3 coordinates x, y, z. The analysis of the main methods of solving, in particular, the metaheuristic algorithms to which ACO belongs, is performed. At each iteration of these methods, a new solution of the problem is built, which is based not on one, but several solutions of the population. The ACO uses an idea that is based on collecting statistical information about the best solutions. The program code is implemented in MATLAB. During computational experiments, various network topologies were randomly generated, and the number of iterations at which the optimal cycle was achieved was recorded. The execution time of the code for the TSP 3D task is almost the same as the execution time of TSP 2D. The results can be used for spatial tasks of the salesman (TSP 3D-variation), which arise in the process of 3D printing, planning UAV trajectories (UAV) in mountain conditions or multi-story urban development, road planning in multi-story buildings.

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“…[26][27][28] Thus, their print speed is limited by stepwise material deposition due to the time of solidification and cooling of molten metals during the printing process. [29][30][31][32] This is because conventional arc-based metal 3D printing processes typically require solidified beads as supporting material to attach the molten metal droplet and to form a stable structure. In addition, an increasing heat input for a high deposition rate excessively increases the volume of molten metal during the printing process and causes it to flow downward owing to gravity (Figures S1-S3, Supporting Information).…”

Section: Introductionmentioning

confidence: 99%

High‐Throughput Metal 3D Printing Pen Enabled by a Continuous Molten Droplet Transfer

et al. 2022

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In metal additive manufacturing (AM), arc plasma is attracting attention as an alternative heat source to expensive lasers to enable the use of various metal wire materials with a high deposition efficiency. However, the stepwise material deposition and resulting limited number of degrees of freedom limit their potential for high-throughput and large-scale production for industrial applications. Herein, a high-throughput metal 3D printing pen (M3DPen) strategy is proposed based on an arc plasma heat source by harnessing the surface tension of the molten metal for enabling continuous material deposition without a downward flow by gravity. The proposed approach differs from conventional arc-based metal AM in that it controls the solidification and cooling time between interlayers of a point-by-point deposition path, thereby allowing for continuous metal 3D printing of freestanding and overhanging structures at once. The resulting mechanical properties and unique microstructures by continuous metal deposition that occur due to the difference in the thermal conditions of the molten metal under cooling are also investigated. This technology can be applied to a wide range of alloy systems and industrial manufacturing, thereby providing new possibilities for metal 3D printing.

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Minimizing the Number of Transitions of 3D Printing Nozzles Using a Traveling-Salesman-Problem Optimization Model

Cited by 12 publications

References 45 publications

Research on dual-robot cooperative path planning for multi-material additive manufacturing

Research on dual-robot cooperative path planning for multi-material additive manufacturing

Algorithm of ant colony optimization (ACO) for 3D variation traveling salesman problem

High‐Throughput Metal 3D Printing Pen Enabled by a Continuous Molten Droplet Transfer

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