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Dimensional and Geometrical Quality Enhancement in Additively Manufactured Parts: Systematic Framework and A Case Study.
- Source :
-
Materials (1996-1944) . Dec2019, Vol. 12 Issue 23, p3937. 1p. 8 Diagrams, 9 Charts, 5 Graphs. - Publication Year :
- 2019
-
Abstract
- In order to compete with traditional manufacturing processes, Additive Manufacturing (AM) should be capable of producing medium to large batches at industrial-degree quality and competitive cost-per-unit. This paper proposes a systematic framework approach to the problem of fulfilling dimensional and geometric requirements for medium batch sizes of AM parts, which has been structured as a three-step optimization methodology. Firstly, specific work characteristics are analyzed so that information is arranged according to an Operation Space (factors that could have an influence upon quality) and a Verification Space (formed by quality indicators and requirements). Standard process configuration leads to characterization of the standard achievable quality. Secondly, controllable factors are analyzed to determine their relative influence upon quality indicators and the optimal process configuration. Thirdly, optimization of part dimensional and/or geometric definition at the design level is performed in order to improve part quality and meet quality requirements. To evaluate the usefulness of the proposed framework under quasi-industrial condition, a case study is presented here which is focused on the dimensional and geometric optimization of surgical-steel tibia resection guides manufactured by Laser-Power Bed Fusion (L-PBF). The results show that the proposed approach allows for part quality improvement to a degree that matches the initial requirements. [ABSTRACT FROM AUTHOR]
- Subjects :
- *MANUFACTURING processes
*JOB descriptions
*CASE studies
Subjects
Details
- Language :
- English
- ISSN :
- 19961944
- Volume :
- 12
- Issue :
- 23
- Database :
- Academic Search Index
- Journal :
- Materials (1996-1944)
- Publication Type :
- Academic Journal
- Accession number :
- 140236277
- Full Text :
- https://doi.org/10.3390/ma12233937