Electron beam additive manufacturing (EBAM) is an additive manufacturing (AM) technique increasingly used by many industrial sectors, including medical and aerospace industries. The application of this technology is still, however, challenged by many technical barriers. One of the major issues is the lack of process monitoring and control system to monitor process repeatability and component quality reproducibility. Various techniques, mainly involving infrared (IR) and optical cameras, have been employed in previous attempts to study the quality of the EBAM process. However, all attempts lack the flexibility to zoom-in and focus on multiple regions of the processing area. In this paper, a digital electronic imaging system prototype and a piece of macroscopic process quality analysis software are presented. The prototype aims to provide flexibility in magnifications and the selection of fields of view (FOV). The software aims to monitor the EBAM process on a layer-by-layer basis. Digital electronic images were generated by detecting both secondary electrons (SE) and backscattered electrons (BSE) originating from interactions between the machine electron beam and the processing area using specially designed hardware. Prototype capability experiments, software verification and demonstration were conducted at room temperature on the top layer of an EBAM test build. Digital images of different magnifications and FOVs were generated. The upper range of the magnification achieved in the experiments was 95 and the demonstration verified the potential ability of the software to be applied in process monitoring. It is believed that the prototype and software have significant potential to be used for in-process EBAM monitoring in many manufacturing sectors. This study is thought to be the necessary precursor for future work which will establish whether the concept is suited to working under in-process EBAM operating conditions.
Electron Beam Melting (EBM) is an increasingly used Additive Manufacturing (AM) technique employed by many industrial sectors, including the medical device and aerospace industries. In-process EBM monitoring for quality assurance purposes has been a popular research area. Electronic imaging has recently been investigated as one of the in-process EBM data collection methods, alongside thermal/ optical imaging techniques. Despite certain capabilities of an electronic imaging system have been investigated, experiments are yet to be carried out to benchmark one of the most important features of any imaging systems – spatial resolution. This article addresses this knowledge gap by: (1) proposing an indicator for the estimation of spatial resolution which includes the Backscattered Electrons (BSE) information depth, (2) estimating the achievable spatial resolution when electronic imaging is carried out inside an Arcam A1 EBM machine, and (3) presenting an experimental method to conduct edge resolution evaluation with the EBM machine. Analyses of experimental results indicated that the spatial resolution was of the order of 0.3mm-0.4mm when electronic imaging was carried out at room temperature. It is believed that by disseminating an analysis and experimental method to estimate and quantify spatial resolution, this study has contributed to the on-going quality assessment research in the field of in-process monitoring of the EBM process.
Electron Beam Melting (EBM) is an increasingly used Additive Manufacturing (AM) technique employed by many industrial sectors, including the medical device and aerospace industries. The application of this technology is, however, challenged by the lack of process monitoring and control system that underpins process repeatability and part quality reproducibility. An electronic imaging system prototype has been developed to serve as an EBM monitoring technique, the capabilities of which have been verified at room temperature and at 320+10°C. Nevertheless, in order to fully assess the applicability of this technique, the image quality needs to be investigated at a range of elevated temperatures to fully understand the influence of thermal noise due to heat. In this paper, electronic imaging pilot trials at elevated temperatures, ranging from room temperature to , were carried out. Image quality measure Q of the digital electron images was evaluated, and the influence of temperature was investigated. In this study, raw electronic images generated at higher temperatures had greater Q values, i.e. better global image quality. It has been demonstrated that, for temperatures between , the influence of temperature on electronic image quality was not adversely affecting the visual clarity of image features. It is envisaged that the prototype has significant potential to contribute to in-process EBM monitoring in many manufacturing sectors.
Electron Beam Melting (EBM) is an increasingly used Additive Manufacturing (AM) technique employed by many industrial sectors, including the medical device and aerospace industries. In EBM process monitoring, data analysis for processed layer quality evaluation is currently focused on the extraction of information from the raw data collected in-EBM process, i.e. thermal/ optical / electronic images, and the comparison between the collected data and the Computed Tomography (CT)/ microscopy images generated post-EBM process. This article postulates that a stack of bitmaps could be generated from the 3D model at a range of Z heights during file preparation of the EBM process, and serve as a reference image set. In-EBM process comparison between that and the workpiece images collected during the EBM process could then be used for quality assessment purposes. In addition, despite the extensive literature on 3D model slicing and contour generation for AM process preparation, no methods regarding image generation from cross sections of the 3D models have been disseminated in details. This article aims to address this by presenting a piece of 3D model-image generation software. The software is capable of generating binary 3D model reference images with user-defined Region-of-Interest (ROI) of the processing area, and Z heights of the model. It is envisaged that this 3D model-reference image generation ability opens up new opportunities in quality assessment for the in-process monitoring of the EBM process.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.