Innovative additively manufactured parts inspection via non-destructive methods based on thermography and Computed Tomography

Additively manufactured components are currently gaining a relevant place in many industrial sectors. However, the potential of additive manufacturing (AM) processes is still lacking significant research to achieve reliable broad industrial adoption in which repeatability and stability are restricting factors. Physical phenomena participating in the AM processes may generate defects between different layers, within the individual layers, and in the overall part such as internal defects. Thus, one of the main challenges in AM chain becomes the setup of methods to guarantee structural integrity and appropriateness of the component for the operating scenario. In this context, Non-Destructive Testing (NDT) represents a key technology for describing AM complexity, detecting and evaluating defects in the part without destroying its serviceability. Today, the most diffused solution is X-Ray computed tomography (CT), whose costs are only affordable for high-end components. A further difficulty is that CT represents a bottleneck in the lead-time, as it can take almost as long as the production itself. INTACT aims to increase the NDT investigation effectiveness towards a more rapid and economical solution, enhanced by combining other destructive and ND methods. INTACT integrates the rapidity and cost-effectiveness of thermography with the precision of detection of CT-scan for a full and fast description of AM complexity. Compared to conventional analyses, INTACT will define ad-hoc reference artefacts to characterise and compare the different NDT methods. The artefact will contain specific defects and features representative of AM. Owing to their totally non-destructive and non-invasive nature, the same components will be inspected by different NDTs. The aim is to highlight various demonstrations of parts characterisation through different data. Techniques with the ability to carry out high-throughput calculations based on artificial intelligence or inferential statistical analyses will be harnessed to develop proper data post-processing methods for thermogram analysis. The post-processed data from each system will be then compared to each other and with the predesigned nominal artefacts. These data will allow defining the operability of each system and, at the same time, verify its reliability. The data integration will allow to compensate for the limitations associated with each technology, enhance the defect detectability and component description of each other NDT techniques and define a reliable novel architecture to calibrate the thermography with the aim to be used as a stand-alone, fast and low-cost NDT method to characterise the AM part complexity fully. The use of this novel architecture will be tested using industrial components. Additionally, the novel approach will make available an unprecedented amount of well-structured data, which will serve as training set for a more robust ND diagnostic testing of metallic additively manufactured parts.