Optimizing the mean and variance of bead geometry in the wire plus arc additive manufacturing using a desirability function method
- Authors
- Cho, Jin-Soo; Lee, Dong-Hee; Seo, Gi-Jeong; Kim, Duck-Bong; Shin, Seung-Jun
- Issue Date
- Jun-2022
- Publisher
- SPRINGER LONDON LTD
- Keywords
- Wire plus arc additive manufacturing process; TZM; Bead geometry; Desirability function method; Response surface methodology
- Citation
- INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, v.120, no.11-12, pp.7771 - 7783
- Indexed
- SCIE
SCOPUS
- Journal Title
- INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Volume
- 120
- Number
- 11-12
- Start Page
- 7771
- End Page
- 7783
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/170116
- DOI
- 10.1007/s00170-022-09237-6
- ISSN
- 0268-3768
- Abstract
- Wire + arc additive manufacturing is an arc welding process that uses non-consumable tungsten electrodes to produce the weld. The material used in this study is a titanium, carbon, zirconium, and molybdenum alloy that is physically and chemically stable and has good performance for use as a welding and high-temperature heating element. In this study, welding experiments are designed based on a central composite design, and single-layer wire + arc additive manufacturing is performed using the titanium, carbon, zirconium, and molybdenum alloy. Consequently, 17 beads are obtained and the height, width, left and right toe angles, which represent the geometry of the beads are measured. Based on the measured geometry, response surface models for mean and standard deviation of the four geometries are fitted. Mean absolute percentage error of the four response surface models is 16.6% on average which implies that the models are reasonably well fitted. Based on the response surface models, the optimal settings for the Wire + arc additive manufacturing parameters are obtained by using a desirability function method. At the optimal setting, the desirability function value shows 0.85 on average which is close to ideal value of 1.00. This result indicates that valid optimal settings for the process parameters can be obtained via the proposed method.
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