A model of bead size based on the dynamic response of CMT-based wire and arc additive manufacturing process parameters. Issue 4 (17th May 2021)

• Record Type: Journal Article
• Authors: Fang, Xuewei; Ren, Chuanqi; Zhang, Lijuan; Wang, Changxing; Huang, Ke; Lu, Bingheng
• Is Part Of: Rapid prototyping journal. Volume 27:Issue 4(2021)
• Page Start: 741
• Page End: 753
• Publication Date: 2021-05-17
• Subjects: Prediction model -- Cold metal transfer -- Wire and arc additive manufacturing -- Bead morphology; Engineering design -- Periodicals; 620.004205
• DOI: 10.1108/RPJ-03-2020-0051
• Languages: English
• ISSNs: 1355-2546

Abstract

Abstract : Purpose: This paper aims at fabricating large metallic components with high deposition rates, low equipment costs through wire and wire and arc additive manufacturing (WAAM) method, in order to achieve the morphology and mechanical properties of manufacturing process, a bead morphology prediction model with high precision for ideal deposition of every pass was established. Design/methodology/approach: The dynamic response of the process parameters on the bead width and bead height of cold metal transfer (CMT)-based AM was analyzed. A laser profile scanner was used to continuously capture the morphology variation. A prediction model of the deposition bead morphology was established using response surface optimization. Moreover, the validity of the model was examined using 15 groups of quadratic regression analyzes. Findings: The relative errors of the predicted bead width and height were all less than 5% compared with the experimental measurements. The model was then preliminarily used with necessary modifications, such as further considering the interlayer process parameters, to guide the fabrication of complex three-dimensional components. Originality/value: The morphology prediction of WAAMed bead is a critical issue. Most research has focused on the formability and defects in CMT-based WAAM and little research on the effect of process parameters on the morphology of the deposited layer in CMT-based WAAM has been conducted. To test the sensitivities of the processing parameters to bead size, the dynamic response of key parameters was investigated. A regression model was established to guide the process parameter optimization for subsequent multi-layer or component deposition.