A Relaxation Scheme for TSP-Based 3D Printing Path Optimizer

Ganganath

et al. 2019

IEEE Trans. Ind. Inf.

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Layered additive manufacturing, also known as 3D printing, has revolutionized transitional manufacturing processes. Fabrication of 3D models with complex structures is now feasible with 3D printing technologies. By performing careful tool-path optimization, the printing process can be speeded up, while the visual quality of printed objects can be improved simultaneously. The optimization process can be perceived as an undirected rural postman problem (URPP) with multiple constraints. In this paper, a tool-path optimizer is proposed, which further optimizes solutions generated from a slicer software to alleviate visual artifacts in 3D printing and shortens print time. The proposed optimizer is based on a modified ant colony optimization (ACO), which exploits unique properties in 3D printing. Experiment results verify that the proposed optimizer can deliver significant improvements in computational time, print time, and visual quality of printed objects over optimizers based on conventional URPP and ACO solvers.

Section: Literature Reviewmentioning

confidence: 99%

An ACO-Based Tool-Path Optimizer for 3-D Printing Applications

Ganganath

et al. 2019

IEEE Trans. Ind. Inf.

Self Cite

“…In this work, we adopt the nozzle motion model in [8] for calculating t d (v i , v j ) in (1). Such model considers the acceleration and deceleration of the nozzle and thus allows its velocity to be varied while traversing an edge.…”

Section: ) Motion Modelmentioning

confidence: 99%

“…The filling density was set to be 10% of the total volume. The print plans were further optimized using the relaxation scheme proposed in [8]. Nevertheless, for comparison purposes, the path optimization module in each set of simulations is replaced with different combinations of Frederickson's algorithm, 2-opt, and the proposed refinement process.…”

Section: A Simulation Settingsmentioning

confidence: 99%

“…In [7], Hertz et al showed that improved RPP solutions can be obtained, with reasonable processing durations, by applying 2-opt algorithm to solutions generated by Frederickson's algorithm mentioned above. Recently, Fok et al formulated the nozzle motion planning problem as TSP and proposed a relaxation scheme for shortening the processing time without causing significant impact to the model build time [8].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A refinement process for nozzle path planning in 3D printing

2017 IEEE International Symposium on Circuits and Systems (ISCAS)

Tse

2017

Self Cite

Abstract-A refinement process for nozzle path planning in 3D printing is presented in this paper. The nozzle path planning problem is formulated as an undirected rural postman problem (URPP). Based on the unique characteristics of URPP in 3D printing applications, a new refinement process is proposed to shorten the processing time of a conventional URPP solver. Performances of the proposed refinement process is evaluated using computer simulations. Simulation results show that when comparing with other URPP solvers, solvers with the proposed process have shorter processing time and can provide solutions with shorter transition length.

“…In order to minimize the amount of materials used to form the supporting structures, they proposed an algorithm which can select an appropriate orientation according to the model to be built. In [5], Fok et al proposed a print plan optimizer based on a deterministic method by which sub-optimum solutions were obtained with a reasonable computational cost. Recently, they formulated the nozzle path planning problem in 3D printing applications into a URPP [6].…”

Section: Introductionmentioning

confidence: 99%

Accelerating 3D Printing Process Using an Extended Ant Colony Optimization Algorithm

2018 IEEE International Symposium on Circuits and Systems (ISCAS)

Ganganath

et al. 2018

Self Cite

Ant colony optimization (ACO) algorithms have been widely adopted in solving combinatorial problems, like the traveling salesman problem (TSP). Nevertheless, with a proper transformation to TSP, ACO is capable of solving undirected rural postman problems (URPP) as well. In fact, nozzle path planning problems in 3D printing can be represented as URPP. Therefore, in this work, ACO is utilized as a URPP solver to accelerate the printing process in fused deposition modeling applications. Furthermore, mechanisms which exploit unique properties in 3D models are proposed to further extend the ACO in the above optimization process. These mechanisms are capable of accelerating ACO by adaptively adjusting its number of iterations on-the-fly. Simulation results using real-life 3D models show that the proposed extensions can accelerate ACO without affecting the quality of its solutions significantly. Index Terms-Ant colony optimization, Additive manufacturing, 3D printing, Undirected rural postman problem This is the Pre-Published Version.