A hybrid of genetic algorithm and particle swarm optimization for reducing material waste in extrusion-basedadditive manufacturing

Feng, Ruiliang; Jiang, Jianjun; Sun, Zhichao; Thakur, Atul; Wei, Xiangzhi

doi:10.1108/rpj-11-2020-0292

Cited by 12 publications

(9 citation statements)

References 48 publications

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“…Finally, the total volume of two-level supports of the models is summarized in Table 4. Compared with the most recent two-level supports, our approach saves up to 26.34%, 10.72% and 8.93% than method of Jiang et al (2019b), method of Feng et al (2021b) and method III (Feng et al, 2021a), respectively. Figure 17 3D printing experimental results of the six example models, and the models with walls are cut such that their inside could be seen single path directions, this paper proposed a GA-based approach to generate hybrid paths to reduce the volume of Level 1 support.…”

Section: Comparisonmentioning

confidence: 91%

Section: Experiments and Comparisonmentioning

confidence: 92%

“…Note that the comparison between our method with Method VI (Feng et al , 2021a) indicates that the local strategy of geometric search can help the hybrid algorithm save up to 17.88% of materials. These models are available on the GitHub [1].…”

Section: Experiments and Comparisonmentioning

confidence: 96%

“…The 3D printing process parameters are set as follows: the nozzle temperature is 190°C, the fan speed is 250 RPM, the deposition speed is 20 mm/s and the layer thickness is 0.2 mm. Note that these parameters are set as the same as previous works (Feng et al, 2021b(Feng et al, , 2021aJiang et al, 2019b) for comparison purpose.…”

Section: Simulation and Experimentsmentioning

confidence: 99%

“…Zhou et al (2019) proposed a method based on the Lindenmayer system (Lsystem) and an octree data structure to generate tree-like supports. Feng et al (2021a) proposed a hybrid of GA and PSO in the lightweight design of the tree-like supports, where GA optimizes its topology and PSO optimizes when the tree topology is fixed. Wang et al (2022) enhanced the L-system with parametric rules and designed the tree branches as lattice structures to further reduce material consumption and improve In the two-level support structure [as shown in Figure 2(b)], the adjacent supporting points will be linked in a line and supported by a series of beams, which constitute the Level 1 support.…”

Section: Introductionmentioning

confidence: 99%

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Lightweight design of two-level supports for extrusion-based additive manufacturing based on metaheuristic algorithms

Feng

Jiang²,

Thakur³

et al. 2022

RPJ

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Purpose Two-level support with Level 1 consisting of a set of beams and Level 2 consisting of a tree-like structure is an efficient support structure for extrusion-based additive manufacturing (EBAM). However, the literature for finding a slim two-level support is rare. The purpose of this paper is to design a lightweight two-level support structure for EBAM. Design/methodology/approach To efficiently solve the problem, the lightweight design problem is split into two subproblems: finding a slim Level 1 support and a slim Level 2 support. To solve these two subproblems, this paper develops three efficient metaheuristic algorithms, i.e. genetic algorithm (GA), genetic programming (GP) and particle swarm optimization (PSO). They are problem-independent and are powerful in global search. For the first subproblem, considering the path direction is a critical factor influencing the layout of Level 1 support, this paper solves it by splitting the overhang region into a set of subregions, and determining the path direction (vertical or horizontal) in each subregion using GA. For the second subproblem, a hybrid of two metaheuristic algorithms is proposed: the GP manipulates the topologies of the tree support, while the PSO optimizes the position of nodes and the diameter of tree branches. In particular, each chromosome is encoded as a single virtual tree for GP to make it easy to manipulate Crossover and Mutation. Furthermore, a local strategy of geometric search is designed to help the hybrid algorithm reach a better result. Findings Simulation results show that the proposed method is preferred over the existing method: it saves the materials of the two-level support up to 26.34%, the materials of the Level 1 support up to 6.62% and the materials of the Level 2 support up to 37.93%. The proposed local strategy of geometric search can further improve the hybrid algorithm, saving up to 17.88% of Level 2 support materials. Research limitations/implications The proposed approach for sliming Level 1 support requires the overhanging region to be a rectilinear polygon and the path direction in a subregion to be vertical or horizontal. This limitation limits the further material savings of the Level 1 support. In future research, the proposed approach can be extended to handle an arbitrary overhang region, each with several choices of path directions. Practical implications The details of how to integrate the proposed algorithm into the open-source program CuraEngine 4.13.0 is presented. This is helpful for the designers and manufacturers to practice on their own 3D printers. Originality/value The path planning of the overhang is a critical factor influencing the distribution of supporting points and will thus influence the shape of the support structure. Different from existing approaches that use single path directions, the proposed method optimizes the volume of the support structure by planning hybrid paths of the overhangs.

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Section: Comparisonmentioning

confidence: 91%

Section: Experiments and Comparisonmentioning

confidence: 92%

Section: Experiments and Comparisonmentioning

confidence: 96%

Section: Simulation and Experimentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Lightweight design of two-level supports for extrusion-based additive manufacturing based on metaheuristic algorithms

Feng

Jiang²,

Thakur³

et al. 2022

RPJ

Self Cite

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Manufacturing constrained shape optimisation of variable width flat web formed channels

Gong

Ghabraie

Weiß

et al. 2023

Int J Adv Manuf Technol

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The trend in automotive manufacturing towards lower volumes and an increased number of car variants combined with the need for forming higher strength metals to reduce weight has led to the implementation of alternative and flexible manufacturing methods. These have new manufacturing constraints compared to conventional stamping that change the part shapes that can be formed. This requires new methods for part shape optimisation. This study proposes a novel parametrisation for shape design that allows: 1) implementation of a gradient-based optimisation approach; and 2) taking manufacturing constraints into account. Our novel parameterisation can describe most long automotive structural parts using only a small number of design variables. The parts are described using multiple series of straight and curved connected profiles. We have uniquely conducted a detailed sensitivity analysis on the profiles to determine analytical solutions for the first order derivatives of the design variables with respect to the surface area/mass of a generic part. The profiles are also used to determine the final manufacturing strains in a part based on ideal forming. These ideal manufacturing strains can be compared to manufacturing process strain limits to determine the potential manufacturability of the part. The proposed parametrisation is applied to optimise a variable width channel formed by flexible roll forming. The channel is optimised to maximise the stiffness while maintaining both mass and manufacturability. In detail, the effectiveness and the general applicability of the established parametrisation technique and shape optimisation platform are demonstrated using three case studies of a flexible roll formed automotive S-rail channel part subjected to compression and bending loads. Furthermore, the manufacturability of the optimised structure is demonstrated by a forming model of the flexible roll forming process, where the model has been previously validated against experimental data. These examples show that the presented parametrisation and the associated shape optimiser can be successfully applied to increase part stiffness while reducing weight and maintaining manufacturability. The range of problems analysed demonstrates the flexibility and capability of the newly developed optimisation platform.

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Mechanical property estimation for additive manufacturing parts with supports

Günaydın,

Gunpinar

2023

Int J Adv Manuf Technol

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A hybrid of genetic algorithm and particle swarm optimization for reducing material waste in extrusion-basedadditive manufacturing

Cited by 12 publications

References 48 publications

Lightweight design of two-level supports for extrusion-based additive manufacturing based on metaheuristic algorithms

Lightweight design of two-level supports for extrusion-based additive manufacturing based on metaheuristic algorithms

Manufacturing constrained shape optimisation of variable width flat web formed channels

Mechanical property estimation for additive manufacturing parts with supports

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