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Publicación DOI 10.1007/s00170-022-08966-yA machine learning approach for the prediction of melting efficiency in wire arc additive manufacturing2022-05 ;Barrionuevo, German O. ;Sequeira-Almeida, Pedro M.; ;Ramos-Grez, Jorge A.Williams, Stewart W.Wire arc additive manufacturing (WAAM) appears as one of the most promising technologies due to its capacity to process all types of materials used in welding, its high production rate, and capacity to process large geometries of particular interest in the aeronautical industry. Since this technology is still under investigation, it is important to determine the efficiency of the process; in this sense, the melting efficiency stands out not only as a parameter of interest in energy terms but also as a measure of the stability of the process. For calculating melting efficiency, it is necessary to use tailored colorimeters or apply models requiring specific dimensions that involve destructive testing. For this reason, in the development of this work, the melting efficiency is evaluated through machine learning algorithms. Processing parameters such as wire diameter, wire feed speed, travel speed, and net power are used to determine melting efficiency. In addition, a simplified analytical model was developed to compare the results. The average melting efficiency analytically calculated was 44.56 +/- 5.48%, while the predicted value reaches a comparable value of 44.32 +/- 4.79% obtained with the Gaussian process regressor, which shows the highest accuracy. Moreover, the known relationship with travel speed was verified. - Some of the metrics are blocked by yourconsent settings
Publicación DOI 10.1007/s00170-022-08966-yA machine learning approach for the prediction of melting efficiency in wire arc additive manufacturing2022-05 ;Barrionuevo, German O. ;Sequeira-Almeida, Pedro M.; ;Ramos-Grez, Jorge A.Williams, Stewart W.Wire arc additive manufacturing (WAAM) appears as one of the most promising technologies due to its capacity to process all types of materials used in welding, its high production rate, and capacity to process large geometries of particular interest in the aeronautical industry. Since this technology is still under investigation, it is important to determine the efficiency of the process; in this sense, the melting efficiency stands out not only as a parameter of interest in energy terms but also as a measure of the stability of the process. For calculating melting efficiency, it is necessary to use tailored colorimeters or apply models requiring specific dimensions that involve destructive testing. For this reason, in the development of this work, the melting efficiency is evaluated through machine learning algorithms. Processing parameters such as wire diameter, wire feed speed, travel speed, and net power are used to determine melting efficiency. In addition, a simplified analytical model was developed to compare the results. The average melting efficiency analytically calculated was 44.56 +/- 5.48%, while the predicted value reaches a comparable value of 44.32 +/- 4.79% obtained with the Gaussian process regressor, which shows the highest accuracy. Moreover, the known relationship with travel speed was verified.Scopus© Citations 41 3 - Some of the metrics are blocked by yourconsent settings
Publicación DOI 10.1016/j.jmatprotec.2018.08.043
Metal transfer modes in plasma Wire plus Arc additive manufacture2019-02; ;Colegrove, Paul A.Williams, Stewart W.The stability of Plasma transferred arc Wire + Arc Additive Manufacture is critically dependent on the transfer mode of the wire into the melt pool which can either be in permanent contact (TM1), intermittent (TM2) or fleeting (TM3) and it's governed by the position of the wire. Analysis of the voltage waveforms in conjunction with video imaging was used to understand the preferred mode for process control and how these transfer modes are affected by convex and concave melt pools shapes. The study indicated that stable transfer can be more easily achieved with the convex weld pool, because it minimises the extent of the undesirable TM3 where droplet transfer occurs in an erratic fashion. Furthermore, even though the operational range of TM2 is limited, a control algorithm could be more easily developed for this transfer mode. Finally, video imaging showed how the melt pool oscillation interacts with droplet detachment under some operational conditions. - Some of the metrics are blocked by yourconsent settings
Publicación DOI 10.1016/j.jmatprotec.2018.08.043
Metal transfer modes in plasma Wire plus Arc additive manufacture2019-02; ;Colegrove, Paul A.Williams, Stewart W.The stability of Plasma transferred arc Wire + Arc Additive Manufacture is critically dependent on the transfer mode of the wire into the melt pool which can either be in permanent contact (TM1), intermittent (TM2) or fleeting (TM3) and it's governed by the position of the wire. Analysis of the voltage waveforms in conjunction with video imaging was used to understand the preferred mode for process control and how these transfer modes are affected by convex and concave melt pools shapes. The study indicated that stable transfer can be more easily achieved with the convex weld pool, because it minimises the extent of the undesirable TM3 where droplet transfer occurs in an erratic fashion. Furthermore, even though the operational range of TM2 is limited, a control algorithm could be more easily developed for this transfer mode. Finally, video imaging showed how the melt pool oscillation interacts with droplet detachment under some operational conditions.Scopus© Citations 66 1