Trajectory Planning for Conformal 3D Printing Using Non-Planar Layers

Shembekar, Aniruddha V.; Yoon, Yeo Jung; Kanyuck, Alec; Gupta, Satyandra K.

doi:10.1115/detc2018-85975

Cited by 29 publications

(13 citation statements)

References 19 publications

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“…The allowed two robotic arms working together could save fabrication time. Shembekar et al [ 69 ] proposed a collision-free path planning strategy for a 6DOF material extrusion AM system, which could save both material usage and build time. A group-based path planning strategy for a multi-robotic material extrusion AM system was developed by Cai and Choi [ 70 ].…”

Section: Path Planning Strategiesmentioning

confidence: 99%

Path Planning Strategies to Optimize Accuracy, Quality, Build Time and Material Use in Additive Manufacturing: A Review

Jiang

2020

Micromachines

207

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Additive manufacturing (AM) is the process of joining materials layer by layer to fabricate products based on 3D models. Due to the layer-by-layer nature of AM, parts with complex geometries, integrated assemblies, customized geometry or multifunctional designs can now be manufactured more easily than traditional subtractive manufacturing. Path planning in AM is an important step in the process of manufacturing products. The final fabricated qualities, properties, etc., will be different when using different path strategies, even using the same AM machine and process parameters. Currently, increasing research studies have been published on path planning strategies with different aims. Due to the rapid development of path planning in AM and various newly proposed strategies, there is a lack of comprehensive reviews on this topic. Therefore, this paper gives a comprehensive understanding of the current status and challenges of AM path planning. This paper reviews and discusses path planning strategies in three categories: improving printed qualities, saving materials/time and achieving objective printed properties. The main findings of this review include: new path planning strategies can be developed by combining some of the strategies in literature with better performance; a path planning platform can be developed to help select the most suitable path planning strategy with required properties; research on path planning considering energy consumption can be carried out in the future; a benchmark model for testing the performance of path planning strategies can be designed; the trade-off among different fabricated properties can be considered as a factor in future path planning design processes; and lastly, machine learning can be a powerful tool to further improve path planning strategies in the future.

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Section: Path Planning Strategiesmentioning

confidence: 99%

Path Planning Strategies to Optimize Accuracy, Quality, Build Time and Material Use in Additive Manufacturing: A Review

Jiang

2020

Micromachines

207

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“…Thus, part strength can also be increased in specific directions. The path generation on a defined curvature layer has been widely studied by including the kinematics motion on the robots and acceleration and deceleration of the deposition motion [ 38 , 43 , 44 , 45 ]. These deposition path generation and robot trajectories computation strategies consider the behavior of robotics additive motion to prevent any collision between the freeform surface and the deposition nozzle.…”

Section: Literature Reviewmentioning

confidence: 99%

Autonomous Robotic Feature-Based Freeform Fabrication Approach

Xiao

2021

Materials

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Robotic additive manufacturing (AM) has gained much attention for its continuous material deposition capability with continuously changeable building orientations, reducing support structure volume and post-processing complexity. However, the current robotic additive process heavily relies on manual geometric reasoning that identifies additive features, related building orientations, tool approach direction, trajectory generation, and sequencing all features in a non-collision manner. In addition, multi-directional material accumulation cannot ensure the nozzle always stays above the building geometry. Thus, the collision between these two becomes a significant issue that needs to be solved. Hence, the common use of a robotic additive is hindered by the lack of fully autonomous tools based on the abovementioned issues. We present a systematic approach to the robotic AM process that can automate the abovementioned planning procedures in the aspect of collision-free. Typically, input models to robotic AM have diverse information contents and data formats, hindering the feature recognition, extraction, and relations to the robotic motion. Our proposed method integrates the collision-avoidance condition to the model decomposition step. Therefore, the decomposed volumes can be associated with additional constraints, such as accessibility, connectivity, and trajectory planning. This generates an entire workspace for the robotic additive building platform, rotatability, and additive features to determine the entire sequence and avoid potential collisions. This approach classifies the uniqueness of autonomous manufacturing on the robotic AM system to build large and complex metal components that are non-achievable through traditional one-directional AM in a computationally effective manner. This approach also paves the path in constructing an in situ monitoring and closed-loop control on robotic AM to control and enhance the build quality of the robotic metal AM process.

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“…The process is based on performing AM along the curved surface [21]. [15] presents the setup using a robot for AM, which assures more flexibility and is more scalable, despite the great accuracy and lower investment-cost of CNC machines. While conformed layer AM reduces fabrication time and increases the part quality, it is only limited to specific AM techniques and sizes.…”

Section: Previous Robotic Am Systemsmentioning

confidence: 99%

Robotic Additive Printing of Cylindrical Auxetic Structures

Biasetto

Boschetti

Minto

2020

Mechanisms and Machine Science

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Additive manufacturing technologies represent an interesting solution to aid companies to offer a wide range of customized products. Furthermore, they allow printing complex lattice and auxetic structures. The use of robot manipulators for 3D printing allows overcoming several limitations of traditional additive manufacturing systems, i.e. low surface quality (stair-casing effects) and undesirable anisotropic properties, so as to print complex geometries on curved surfaces. This work presents an experimental setup designed to print cylindrical auxetic structures composed of a 3D printer and a robotic arm. The system produces the part without any assembly and avoiding staircase effects. Furthermore, using the robot for moving the printing based simplified the control system and allows for simpler printing devices.

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Trajectory Planning for Conformal 3D Printing Using Non-Planar Layers

Cited by 29 publications

References 19 publications

Path Planning Strategies to Optimize Accuracy, Quality, Build Time and Material Use in Additive Manufacturing: A Review

Path Planning Strategies to Optimize Accuracy, Quality, Build Time and Material Use in Additive Manufacturing: A Review

Autonomous Robotic Feature-Based Freeform Fabrication Approach

Robotic Additive Printing of Cylindrical Auxetic Structures

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