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Modeling and optimization of height-related geometrical parameters for thin wall structures manufactured by metal additive manufacturing

Tutkimustuotos: ArtikkeliTieteellinenvertaisarvioitu

9 Sitaatiot (Scopus)

Abstrakti

Cold metal transfer wire arc additive manufacturing (CMT-WAAM) has attracted attention in recent years due to its ability to print walls with higher dimensional accuracy than regular WAAM. To print near-net shape parts by CMT-WAAM, there is a need to define a set of height-related geometrical parameters (HGPs) that can capture, quantify, and compare the quality of the height of the produced parts. In the presenting study, a set of HGPs, namely, the average height error, maximum height variation, and average absolute slope are defined and assessed. Fifteen single-track multi-layer walls are printed to check the effect of process parameters on the defined HGPs. It is found that the stability and quality of the print cannot be guaranteed by checking the visual appearance of the single beads and at least five-to-ten-layer walls should be printed. It is also found that the travel speed and the wire feed speed have positive monotonic relationships with average absolute slope and maximum height variation, respectively. Correlations between process parameters and HGPs are modeled and optimized using multi-objective optimization, and a validation test is performed to check the validity of the developed models. Moreover, HGPs of walls printed using unidirectional and bidirectional path strategies are calculated and compared. Defined HGPs are able to quantify, capture, and compare the quality of height of a wall with only three parameters. The HGPs can be used in further studies to report and compare the quality of height of thin wall structures.

AlkuperäiskieliEnglanti
Sivut4663–4675
Sivumäärä13
JulkaisuInternational Journal of Advanced Manufacturing Technology
Vuosikerta129
Numero9-10
Varhainen verkossa julkaisun päivämäärä2023
DOI - pysyväislinkit
TilaJulkaistu - 2023
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Rahoitus

The authors gratefully acknowledge funding from the Natural Sciences and Engineering Research Council (NSERC) of Canada (grant numbers: RGPIN-2019–06601) and Business Finland under Project #: 4819/31/2021 with affiliation to the Eureka! SMART project (S0410) titled “TANDEM: Tools for Adaptive and Intelligent Control of Discrete Manufacturing Processes.”

RahoittajatRahoittajan numero
The Natural Sciences and Engineering Research Council of CanadaRGPIN-2019–06601
Business Finland4819/31/2021

    Julkaisufoorumi-taso

    • Jufo-taso 1

    !!ASJC Scopus subject areas

    • Control and Systems Engineering
    • Software
    • Mechanical Engineering
    • Computer Science Applications
    • Industrial and Manufacturing Engineering

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