## 1 Introduction
Apart from the closed-loop control of the powder bed temperature monitoring, variable laser parameters, and the implementation of standard camera systems to detect major defects, such as part displacement, there are only scientific approaches for real-time and in situ process monitoring and no suitable solutions for industrial applications. The process flow by itself allows for remarkable possibilities in layer-by-layer monitoring for preventing defect transfer into final components and ensuring material properties and part quality [18]. The implementation of suitable online quality control is difficult to realize due to largely enclosed soft- and hardware solutions and the fact that almost no intrusion into parameters is possible during ongoing processes. In this paper, a new approach of curling defect detection and analysis of powder bed structure in PBF-LB/P is proposed by the simultaneous application of industrial grade laser profilometry and thermal imaging. Curling, as an in-process phenomenon where mainly only the first layers of the part are affected, is caused by stress due to temperature gradients, resulting in lifting of the part from the powder bed. According to [18], \"warpage\" is defined as a \"post-process\" process that results in deformation of the entire part. If non-tempered powder is introduced after the laser exposure, uneven shrinkage between the top and bottom of the part induces a curved profile close to the free edges of build parts, as can be seen in Figure 3. The effect can occur on the surface after coating, after the laser exposure (as depicted in Figure 4), in-build during processing, or even when the process is finished, and the components are cooling down to room temperature [17]. Figure 3: Curling defect after coating a new layer of powder. Visible lifting of part segments from the powder bed. Previous scientific and experimental approaches for process control and defect detection in PBF-LB have revealed a wide range of relevant concepts addressing both polymer and metal powder-based fusion. Beside similar powder bed defects concerning both processes, such as coating failures, curling, shrinkage, part shifting, and powder short feed, PBF of metals (PBF-LB/M) might lead to additional defects such as spatters, porosity, and cracks due to process parameters such as temperature, laser power, and material properties [17; 19; 20; 21; 22]. As part of the literature research, previous works have been delineated into different research fields as sensor-only concepts applying a variety of measuring methods such as thermography, profilometry, and fringe projection to analyze powder bed quality, and additionally machine/deep learning approaches to defect detection and prediction. To the best of our knowledge, the simultaneous application of laser profilometry and thermal imaging has not yet been discussed in powder bed fusion of polymers. Standalone laser profilometry solutions that have already been presented had limitations due to the mounting position within the installation space and the resulting detection range on the powder bed. The mounting position of both sensor concepts outside the installation space enables the sensing of the complete powder bed surface, providing real-time height data of curling failures and associated temperature fields at different stages of the ongoing manufacturing process. This new approach to monitoring the process in PBF-LB/P primarily focuses on revealing relationships between the spatial location of defects and the actual thermal distribution that leads to failures in these areas. This current work demonstrates a novel approach to real-time process monitoring and in situ defect detection in selective laser sintering of polymers by combining external laser profilometry to compile structural 3D data and thermal imaging to highlight the related thermal fields and temperature distributions.