Page 59 - MSAM-2-1
P. 59
Materials Science in Additive Manufacturing Data imputation strategies of PBF Ti64
Wiley and Sons Inc., New York. multiple imputation: an overview and case study. Emerging
Themes Epidemiol, 14: 8.
https://doi.org/10.1002/9780470316696
https://doi.org/10.1186/s12982-017-0062-6
31. 6.4. Imputation of Missing Values-scikit-learn 0.23.2
Documentation. Available from: https://scikit-learn.org/ 38. Metelkova J, Kinds Y, Kempen K, et al., 2018, On the
stable/modules/impute.html#multiple-vs-singleimputation influence of laser defocusing in Selective Laser melting of
[Last accessed on 2020 Oct 05]. 316L. Addit Manuf, 23: 161–169.
32. Shah AD, Bartlett JW, Carpenter J, et al., 2014, Comparison https://doi.org/10.1016/j.addma.2018.08.006
of random forest and parametric imputation models for 39. Slobodzian GE. White Paper-apples to Apples: Which Camera
imputing missing data using MICE: A CALIBER study. Am Technologies Work Best for Beam Profiling Applications,
J Epidemiol, 179: 764–774.
Part 2: Baseline Methods and Mode Effects. Available from:
https://doi.org/10.1093/aje/kwt312 https://www.ophiropt.com/laser--measurement/knowledge-
center/article/8065 [Last accessed on 2020 Oct 12].
33. Spinelli I, Scardapane S, Uncini A, 2020, Missing data
imputation with adversarially-trained graph convolutional 40. Kuruvilla M, Srivatsan TS, Petraroli M, et al., 2008,
networks. Neural Netw, 129: 249–260. An investigation of microstructure, hardness, tensile
behaviour of a titanium alloy: Role of orientation. Sadhana,
https://doi.org/10.1016/j.neunet.2020.06.005
33: 235–250.
34. Kohonen T, 1982, Self-organized formation of topologically https://doi.org/10.1007/s12046-008-0017-2
correct feature maps. Biol Cybern, 43: 59–69.
41. Jiang PF, Zhang CH, Zhang S, et al., 2021, Additive
https://doi.org/10.1007/BF00337288
manufacturing of novel ferritic stainless steel by selective
35. Moosavi V, Packmann S, Vallés I, 2014, SOMPY: A Python laser melting: Role of laser scanning speed on the
Library for Self Organizing Map (SOM). Available from: formability, microstructure and properties. Opt Laser
https://www.github.com/sevamoo/sompy [Last accessed on Technol, 140: 107055.
2020 Oct 05].
https://doi.org/10.1016/j.optlastec.2021.107055
36. Qian J, Nguyen NP, Oya Y, et al., 2019, Introducing self- 42. Wang Z, Xiao Z, Tse Y, et al., 2019, Optimization of
organized maps (SOM) as a visualization tool for materials processing parameters and establishment of a relationship
research and education. Results Mater, 4: 100020.
between microstructure and mechanical properties of SLM
https://doi.org/10.1016/j.rinma.2019.100020 titanium alloy. Opt Laser Technol, 112: 159–167.
37. Nguyen CD, Carlin JB, Lee KJ, 2017, Model checking in https://doi.org/10.1016/j.optlastec.2018.11.014
Volume 2 Issue 1 (2023) 18 https://doi.org/10.36922/msam.50

