Methodology to Determine Melt Pool Anomalies in Powder Bed Fusion of Metals Using a Laser Beam by Means of Process Monitoring and Sensor Data Fusion

Additive manufacturing, in particular the powder bed fusion of metals using a laser beam, has a wide range of possible technical applications. Especially for safety-critical applications, a quality assurance of the components is indispensable. However, time-consuming and costly quality assurance measures, such as computer tomography, represent a barrier for further industrial spreading. For this reason, alternative methods for process anomaly detection using process monitoring systems have been developed. However, the defect detection quality of current methods is limited, as single monitoring systems only detect specific process anomalies. Therefore, a new methodology to evaluate the data of multiple monitoring systems is derived using sensor data fusion. Focus was placed on the causes and the appearance of defects in different monitoring systems (photodiodes, on- and off-axis high-speed cameras, and thermography). Based on this, indicators representing characteristics of the process were developed to reduce the data. Finally, deterministic models for the data fusion within a monitoring system and between the monitoring systems were developed. The result was a defect detection of up to 92% of the melt track defects. The methodology was thus able to determine process anomalies and to evaluate the suitability of a specific process monitoring system for the defect detection

Methodology to Determine Melt Pool Anomalies in Powder Bed Fusion of Metals Using a Laser Beam by Means of Process Monitoring and Sensor Data Fusion

Additive manufacturing, in particular the powder bed fusion of metals using a laser beam, has a wide range of possible technical applications. Especially for safety-critical applications, a quality assurance of the components is indispensable. However, time-consuming and costly quality assurance measures, such as computer tomography, represent a barrier for further industrial spreading. For this reason, alternative methods for process anomaly detection using process monitoring systems have been developed. However, the defect detection quality of current methods is limited, as single monitoring systems only detect specific process anomalies. Therefore, a new methodology to evaluate the data of multiple monitoring systems is derived using sensor data fusion. Focus was placed on the causes and the appearance of defects in different monitoring systems (photodiodes, on- and off-axis high-speed cameras, and thermography). Based on this, indicators representing characteristics of the process were developed to reduce the data. Finally, deterministic models for the data fusion within a monitoring system and between the monitoring systems were developed. The result was a defect detection of up to 92% of the melt track defects. The methodology was thus able to determine process anomalies and to evaluate the suitability of a specific process monitoring system for the defect detection

<i>Escherichia coli</i> Nissle 1917 Enhances Efficacy of Oral Attenuated Human Rotavirus Vaccine in a Gnotobiotic Piglet Model

Human rotavirus (HRV) infection is a major cause of viral gastroenteritis in young children worldwide. Current oral vaccines perform poorly in developing countries where efficacious vaccines are needed the most. Therefore, an alternative affordable strategy to enhance efficacy of the current RV vaccines is necessary. This study evaluated the effects of colonization of neonatal gnotobiotic (Gn) pigs with Escherichia coli Nissle (EcN) 1917 and Lacticaseibacillus rhamnosus GG (LGG) probiotics on immunogenicity and protective efficacy of oral attenuated (Att) HRV vaccine. EcN-colonized pigs had reduced virulent HRV (VirHRV) shedding and decreased diarrhea severity compared with the LGG-colonized group. They also had enhanced HRV-specific IgA antibody titers in serum and antibody secreting cell numbers in tissues pre/post VirHRV challenge, HRV-specific IgA antibody titers in intestinal contents, and B-cell subpopulations in tissues post VirHRV challenge. EcN colonization also enhanced T-cell immune response, promoted dendritic cells and NK cell function, reduced production of proinflammatory cytokines/Toll like receptor (TLR), and increased production of immunoregulatory cytokines/TLR expression in various tissues pre/post VirHRV challenge. Thus, EcN probiotic adjuvant with AttHRV vaccine enhances the immunogenicity and protective efficacy of AttHRV to a greater extent than LGG and it can be used as a safe and economical oral vaccine adjuvant