Multi-criteria analysis of parameter impact in large-scale robotic 3D printing

Additive manufacturing is widely used for prototyping and producing functional parts. With the growing capabilities of industrial robots, robotic additive manufacturing is becoming an attractive alternative to conventional 3D printing. Robots enable the fabrication of large-scale, structurally complex, and non-planar components that exceed the limitations of traditional printing. However, the flexibility of robotic systems comes with increased complexity in process control – particularly in the selection of appropriate printing parameters, which is critical for ensuring the quality and stability of the printed parts. This paper addresses the need for a systematic approach to parameter selection in robotic 3D printing to ensure optimal process performance and part quality. First, control software to manage and execute the printing process was developed. Secondly, the impact of changes in the industrial robot TCP's velocity and orientation on the quality of manufactured parts was investigated. Furthermore, to optimize the selection of process parameters, the TOPSIS multi-criteria decision-making method was employed. The presented approach provides a methodology for parameter selection and optimization in robotic 3D printing.