Combining heuristics for tool-path optimisation in material extrusion additive manufacturing

Volpato, Neri; Galvão, Lauro César; Nunes, Luiz Fernando; Souza, Romulo Ianuch; Oguido, Karina

doi:10.1080/01605682.2019.1590135

Cited by 20 publications

(8 citation statements)

References 14 publications

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“…Instead of continuously switching the printing areas, the path planning algorithm was improved to complete the maximum number of layers that the nozzle could reach, and then moved to other areas to continue printing, so as to shorten the travelling paths and time. Volpato et al [12] compared two MEX path optimisation schemes to reduce the time spent on nozzle repositioning. One was based on greedy algorithm, while the other combined the 2-opt heuristics and the nearest insertion algorithms.…”

Section: Background and Motivationmentioning

confidence: 99%

Prediction-based multi-objective optimisation method for 3D Printing Resource Consumption

Yang,

Wang,

Dun

et al. 2024

Preprint

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A prediction-based multi-objective optimisation (PBMO) method is proposed for 3D printing (3DP) technology to predict and reduce resource requirements on-demand, including time, energy and material. In the authors’ previous research work, a hybrid code-based and data-driven modelling (HCDM) scheme has been proposed to forecast 3DP resource consumption. The predictive models are customised based on process parameters, material deposition paths and machine behaviours. Aiming at the appropriate process parameters that consume the least resources, this study further utilises the models as three objectives to be minimised. Meta-heuristic algorithm is adopted to construct the optimisation framework, in which the HCDM process is embedded in the fitness evaluation step. To validate the proposed method, the corresponding computing program is compiled using Non-dominated Sorting Genetic Algorithm II (NSGA-II) and demonstrated on two material extrusion (MEX) machines. Hypervolume is used as the Lebesgue measure to evaluate the superiorities of near-optimal solutions on the non-dominated Pareto front. In three-dimensional objective space, the solution set that occupies the maximum hypervolume will be recommended as the optimal-found solutions for 3DP. In addition to 3DP, the proposed optimisation method is applicable to mainstream computer numerical control (CNC) manufacturing technologies, and will guide process design to promote resource conservation for cleaner production.

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Section: Background and Motivationmentioning

confidence: 99%

Prediction-based multi-objective optimisation method for 3D Printing Resource Consumption

Yang,

Wang,

Dun

et al. 2024

Preprint

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show abstract

“…Continuous path infill strategies are developed to reduce the tool starting and stopping and reduce the printing time [163]. In this sense, the spiral infill was developed [145,228] (see Fig.…”

Section: Contourmentioning

confidence: 99%

A review of geometry representation and processing methods for cartesian and multiaxial robot-based additive manufacturing

Lettori

Raffaeli

Bilancia

et al. 2022

Int J Adv Manuf Technol

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Nowadays, robot-based additive manufacturing (RBAM) is emerging as a potential solution to increase manufacturing flexibility. Such technology allows to change the orientation of the material deposition unit during printing, making it possible to fabricate complex parts with optimized material distribution. In this context, the representation of parts geometries and their subsequent processing become aspects of primary importance. In particular, part orientation, multiaxial deposition, slicing, and infill strategies must be properly evaluated so as to obtain satisfactory outputs and avoid printing failures. Some advanced features can be found in commercial slicing software (e.g., adaptive slicing, advanced path strategies, and nonplanar slicing), although the procedure may result excessively constrained due to the limited number of available options. Several approaches and algorithms have been proposed for each phase and their combination must be determined accurately to achieve the best results. This paper reviews the state-of-the-art works addressing the primary methods for the representation of geometries and the subsequent geometry processing for RBAM. For each category, tools and software found in the literature and commercially available are discussed. Comparison tables are then reported to assist in the selection of the most appropriate approaches. The presented review can be helpful for designers, researchers and practitioners to identify possible future directions and open issues.

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“…The minimization of non-productive times in material extrusion additive manufacturing is investigated in [17,18], where vertices in a class encode the entry and exit points for closed contours and processing directions for open filling rasters within each layer. For solving the problem, heuristics and mixed-integer linear programming are combined in [17], whereas the performance of different heuristics is compared in [18].…”

Section: Survey Of Robotic Task Sequencing Problemsmentioning

confidence: 99%

ProSeqqo: A generic solver for process planning and sequencing in industrial robotics

Zahorán

Kovács²

2022

Robotics and Computer-Integrated Manufacturing

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Combining heuristics for tool-path optimisation in material extrusion additive manufacturing

Cited by 20 publications

References 14 publications

Prediction-based multi-objective optimisation method for 3D Printing Resource Consumption

Prediction-based multi-objective optimisation method for 3D Printing Resource Consumption

A review of geometry representation and processing methods for cartesian and multiaxial robot-based additive manufacturing

ProSeqqo: A generic solver for process planning and sequencing in industrial robotics

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