Effects of different scanning patterns on nickel alloy-directed energy deposition based on thermal analysis

A novel and comprehensive evaluation index considering various processing parameters in additive manufacturing with four different scanning patterns was proposed. The relationship between the evaluation index and the performance of parts made by directed energy deposition was established and verifie...

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Bibliographic Details
Published inVirtual and physical prototyping Vol. 16; no. S1; pp. S98 - S115
Main Authors Zhang, Yang, Jing, Hongyang, Xu, Lianyong, Han, Yongdian, Zhao, Lei
Format Journal Article
LanguageEnglish
Published Taylor & Francis 08.09.2021
Taylor & Francis Group
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Summary:A novel and comprehensive evaluation index considering various processing parameters in additive manufacturing with four different scanning patterns was proposed. The relationship between the evaluation index and the performance of parts made by directed energy deposition was established and verified by experiments. The differences of thermal evolution between four scanning patterns were analysed. Comprehensive evaluation indices corresponding to different scanning patterns were calculated by integrating the contributions of various parameters, such as delamination, warping, porosity, heat accumulation, cooling rate, dendrite spacing, and deposition efficiency. The comprehensive evaluation indices off our scanning patterns were ranked in the following order (from lowest to highest): single-track zigzag, single-track, bi-direction, and spiral inward patterns. The performance of the single-track zigzag pattern was the best, and that of the spiral inward pattern was the worst. The single-track and bi-direction patterns showed intermediate performances under the same conditions. The closer the index is to zero, the better the performance. This index can be used for the quantitative evaluation of process quality and prediction of performance. It provides guidance for additive manufacturing process development and optimisation, reduces workload, and provides a new idea for quantitative performance evaluation and prediction of parts fabricated by additive manufacturing.
ISSN:1745-2759
1745-2767
DOI:10.1080/17452759.2021.1896173