Comparison of methods to correlate input parameters with depth of penetration in LASER weldingShow others and affiliations
2019 (English)In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 101, no 5-8, p. 1157-1169Article in journal (Refereed) Published
Abstract [en]
Despite the industrial relevance of LASER welding, determination of sustainable parameterization is still a challenge. Trial and error, or even not totally justified methodologies, are frequently applied on LASER welding parametrization. This approach potentially leads to a decrease of the process tolerance and, consequently, increasing the likelihood of imperfections, which means extra operational time and raising of the final cost. The present paper addresses a comparative discussion about five factors experimentally determined and frequently used to predict depth of penetration in LASER welding. The experiments were performed with a 10-kW fiber LASER. In a first batch, power was varied while welding speed was fixed at 1 m/min. In a second batch, welding speed was varied and power was kept at 10 kW. The first demonstrated concern on using these popular factors is the definition and quantification of LASER energy. For evidencing this aspect, two samples were processed with the same welding energy of 120 kJ/m, yet resulting in completely different penetrations. Eventually, an empirical model based on power as a factor allowed a more reliable prediction of the depth of penetration.
Place, publisher, year, edition, pages
2019. Vol. 101, no 5-8, p. 1157-1169
Keywords [en]
Autogenous LASER welding, Conduction LASER welding, Keyhole welding, Heat input, Power density, Power factor
National Category
Manufacturing, Surface and Joining Technology
Research subject
ENGINEERING, Manufacturing and materials engineering; Production Technology
Identifiers
URN: urn:nbn:se:hv:diva-13147DOI: 10.1007/s00170-018-3018-2ISI: 000463240400004Scopus ID: 2-s2.0-85056474097OAI: oai:DiVA.org:hv-13147DiVA, id: diva2:1276356
Note
First Online: 14 November 2018
Funders: CNPq
2019-01-082019-01-082021-05-05Bibliographically approved