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Additive manufacturing by laser metal deposition (LMD) requires continuous online monitoring to ensure quality of printed parts. Optical emission spectroscopy (OES) is proposed for the online detection of printing defects by monitoring minute variations in the temperature of a printed spot during laser scan. A two-lens optical system is attached to a moving laser head and focused on a molten pool created on a substrate during LMD. The light emitted by the pool is collected by an ultraviolet–visible (UV–vis) spectrometer and processed.
Two metrics are used to monitor variations in the surface temperature: the spectrally integrated emission intensity and correlation coefficient. The variations in the temperature are introduced by artificial defects, shallow grooves, and holes of various widths and diameters carved on a substrate surface. The metrics show sufficient sensitivity for revealing the surface defects, except for the smallest
holes with an under-millimeter diameter. Additionally, numeric simulations are carried out for the detection of emission in the UV–vis and near-infrared (NIR) spectral ranges at various surface temperatures. It is concluded that both the metrics perform better in the NIR range. In general, this work demonstrates that spectrally resolved OES suits well for monitoring surface defects during 3D metal
printing.
Laser metal deposition is a rapidly evolving method for additive manufacturing that combines high performance and simplified production routine. Quality of production depends on instrumental design and operational parameters that require constant control during the process. In this work, feasibility of using optical spectroscopy as a control method is studied via modeling and experimentally. A simplified thermal model is developed based on the time-dependent diffusion-conduction heat equation and geometrical light collection into detection optics. Intense light emitted by a laser-heated spot moving across a sample surface is collected and processed to yield the temperature and other temperature-related parameters. In a presence of surface defects the temperature field is distorted in a specific manner that depends on a shape and size of the defect. Optical signals produced by such the distorted temperature fields are simulated and verified experimentally using a 3D metal printer and a sample with artificially carved defects. Three quantities are tested as possible metrics for process monitoring: temperature, integral intensity, and correlation coefficient. The shapes of the simulated signals qualitatively agree with the experimental signals; this allows a cautious inference that optical spectroscopy is capable of detecting a defect and, possibly, predicting its character, e.g. inner or protruding.
A big problem with the chemistry literature is that it is not standardized with respect to precise operational parameters, and real time corrections are hard to make without expert knowledge. This lack of context means difficult reproducibility because many steps are ambiguous, and hence depend on tacit knowledge. Here we present the integration of online NMR into an automated chemical synthesis machine (CSM aka. “Chemputer” which is capable of small-molecule synthesis using a universal programming language) to allow automated analysis and adjustment of reactions on the fly. The system was validated and benchmarked by using Grignard reactions which were chosen due to their importance in synthesis. The system was monitored in real time using online-NMR, and spectra were measured continuously during the reactions. This shows that the synthesis being done in the Chemputer can be dynamically controlled in response to feedback optimizing the reaction conditions according to the user requirements.
Compact nuclear magnetic resonance (NMR) instruments make NMR spectroscopy and relaxometry accessible in industrial and harsh environments for reaction and process control. An increasing number of applications are reported. To build an interdisciplinary bridge between “process control” and “compact NMR”,we give a short overviewon current developments in the field of process Engineering such as modern process design, integrated processes, intensified processes along with requirements to process control, model based control, or soft sensing. Finally, robust field integration of NMR systems into processes environments, facing explosion protection or Integration into process control systems, are briefly discussed.
The design of sample flow cells, commonly used in on-line analytics and especially for medium resolution NMR spectroscopy (MR-NMR) in low magnetic fields, was experimentally and theoretically investigated by 1H NMR and numerical simulations. The flow pattern was characterised to gain information about the residence time distribution and mixing effects. Both 1H NMR imaging and spectroscopy were used to determine the characteristics of flow cells and their significance for on-line measurements such as reaction monitoring or hyphenated separation spectroscopy. The volume flow rates investigated were in the range from 0.1 to 10 ml/min, typically applied in the above mentioned applications. The special characteristics of flow cells for MR-NMR were revealed by various NMR experiments and compared with CFD simulations and to flow cells commonly used in high-field NMR. The influence of the design of the inlet and outlet on the flow pattern was investigated as well as the effect of the length of the cell. For practical use, a numerical estimation of the inflow length was given. In addition, it was shown how experiments on the polarisation build-up revealed insight into the flow characteristics in MR-NMR.