Abstract

The implementation of in-situ sensing solutions to monitor additive manufacturing processes has seen a significant surge in recent years, notably in processes where localised heating is used. These technologies, however, have not always yielded accurate information about final part quality, due to differences between the irregularities observed in-process and the anomalies present in the finished part. One way of investigating such differences is to establish correlations between in-process layer properties and the final condition of the part. In this work, we put forward a solution based on a bespoke fringe projection system designed to monitor layers within the build chamber of a PBF-LB machine. Through the computation of quantitative indicators on fringe projection data and the use of statistical control charts for their monitoring and analysis, we are able to predict local reductions in part density, detrimental to the quality of the final build, which are typically only visible after part manufacture. Principally, this article describes the developed fringe projection system utilised for data collection and the custom indicators used to examine layer topographical characteristics and which are correlated with local final densities. We design an experimental campaign to produce parts with different local densities and show how the proposed indicators, combined with statistical control charts, can predict in-process drops in density. The monitoring performance is validated via X-ray computed tomography (XCT) measurements performed on the as-built samples.

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