Glass-filled composites are used for overmolding of electrical components due to their good electrical isolation properties. Laser cutting is a preferred technology to remove excess mold material to achieve a low surface roughness and reduce tool wear. Hatching strategies improve the laser-cutting process of carbon fiber-reinforced polymers toward lower cutting times and a more homogeneous cut surface. The impact of hatching strategies on epoxy mold compounds has been so far unknown as the laser-cutting strategy was based on multiple single passes in previous studies. This work investigates the effects of hatching strategies such as perpendicular hatching, parallel hatching, and a single line, including the influence of material thickness and filler content regarding the cutting time, kerf taper angle, and heat-affected zone, using a 50 W short-pulsed fiber laser for different highly filled epoxy mold compounds. Results show that the use of a hatching strategy is required to cut workpieces at thicknesses of 4 mm or higher due to the sieving size of the filler. Perpendicular hatching needs to be chosen when the aim is a minimal cutting time. The kerf taper angle at the top of the cut is below 4° while hatching leads to a more pronounced kink of up to 25° occurring toward the bottom of the cut. Meanwhile, an increase in filler concentration leads to an increase in cutting time, because of higher thermal conduction, while no effect on the kerf taper angle or the heat-affected zone can be identified.

Laser welding of copper hairpins is required to produce a conductive connection in electric stators. Past manufacturing processes introduce misalignments that lead to poor weld connections with increased electrical resistance. In this work, we discuss correlations between the electrical resistance of the weld connection and possible misalignment types. Misalignments lead to a deformed surface topography of the weld. We correlate inline measurements of the weld topography by optical coherence tomography (OCT) with misalignment types and hence erroneous weld connections. We identify a connection between surface topographical weld features with the electrical resistance of the weld. As a result, a quantified separation of process results is possible with a surface topographical feature of the hairpins that allows for concluding the electrical resistance of the pin-pair connection. Correlation coefficient is identified as the most relevant feature indicating a linear trend in the height profile. Reference measurements with a symmetrical weld pearl show a correlation coefficient of around 0, whereas misalignments with a skewed surface topography show increased absolute correlation coefficient values up to 0.75. The identified correlation between the electrical resistance and different misalignment types can be depicted with the correlation coefficient for the given boundary conditions. Defective weld results with electrical resistances above 6 µΩ can be identified with feature values above 0.5, whereas reference welds with an electrical resistance below 5 µΩ can be identified with an absolute correlation coefficient below 0.2.

The high demand for electronic products increases the need for high-quality welds of copper. Laser welding can be applied but may result in undesired weld characteristics such as humping or spatter. Process control is needed to identify defective welds in the production line. Surface topographical features can be used to identify different weld characteristics by optical coherence tomography (OCT). The resulting surface topography of a weld can be influenced by process parameters like its material properties or the application of process gas. In this work, we investigate the influence of different pure copper materials and process gas on weld seam surface features for the classification of quality-relevant weld characteristics. First, the resulting changes in weld depth and metallographic cross sections are qualitatively and quantitively characterized for different pure copper materials under the consideration of weld categories such as melt ejection, deep penetration welding, humping, and heat conduction welding with and without the application of shielding gas. Afterward, a qualitative and quantitative analysis of weld surface features is performed for the beforementioned categories under consideration of the copper material and shielding gas. As a result, an influence on the achievable weld depth could be identified for pure copper with residual phosphor content. No significant changes in surface topographical features could be identified for different material properties of copper. The influence of shielding gas and pure copper material is found to be negligible on surface topographical characteristics for process control.

Optical coherence tomography (OCT) is an inline process monitoring technology for laser welding with various applications in the pre-, in-, and post-process. In-process monitoring with OCT focuses on the measurement of weld depth by the placement of a singular measurement beam into the keyhole. A laterally scanned measurement beam gives the opportunity to measure the keyhole and melt pool width. The processing region can be identified by separating higher signal intensities on the workpiece surface from lower signal intensities from the keyhole and the melt pool. In this work, we apply a scanned measurement beam for the identification of keyhole fluctuations. Different laser processing parameters are varied for laser welding of copper to evoke welds in the heat conduction regime, stable deep penetration welding, and unstable deep penetration welding. As keyhole instabilities can be related to the generation of spatter and other defects, we identified a feature for the classification of different weld statuses. In consequence, feedback can be given about possible defects which are originated in keyhole fluctuations (e.g., spatter).

The topographical information of a weld seam bears information about quality relevant characteristics such as humping or spatter. Optical coherence tomography (OCT) can be used for inline scanning the weld topography coaxially mounted at a laser scanning optic. Feature extraction from this topographical information is challenging due to finding mathematical representations for the identification of relevant features. Feature extraction based on scalable hypothesis tests (FRESH) allows for feature extraction by a combination of various time series characterization methods. FRESHs feature selection is supported with an automatically configured hypothesis test and hence allows for quick extraction of significant features from sensing data in laser welding processes. In this work, a proof-of-concept is demonstrated for weld result categorization from OCT data by feature extraction using the FRESH algorithm. Changes in weld topography are characterized in a vast variety of process parameters for weld categories such as spatter, deep penetration welding, humping and heat conduction welding. As a result, a quantified separation of weld categories is possible and shows the feasibility of the FRESH algorithm for future quality assessments with different sensing technologies in laser welding.

Inline monitoring technologies gain increasing importance in industrial laser welding applications. Multiple sensing technologies can be implemented for classification of welding defects. Feature extraction from sensing data is a time-consuming process due to various algorithm possibilities for the identification of relevant features. Feature extraction based on scalable hypothesis tests (FRESH) allows for feature extraction with a combination of various time series characterization methods. FRESHs feature selection promises a quick extraction of relevant features from sensing data with an automatically configured hypothesis test. In the example of classification of spatter events, we show that FRESH can be used for the extraction of relevant features with photodiode sensing data in laser welding of copper.

The coaxial integration of optical coherence tomography (OCT) enables the determination of surface topography and measurement of object features along the optical path within laser machining. The measurement of surface information from the processed workpiece allows for the identification of features from the joint configuration and the subsequent control of the welding process by seam tracking. State-of-the-art seam tracking approaches are based on monochromatic cameras or laser triangulation. Typically, these approaches apply line segmentations for the identification of the joint position. The interferometric measurement method of OCT gives rise to the identification of new features for image processing in seam tracking. In this work, we identify specific noise components and features based on the theoretical background of OCT for image processing in seam tracking applications. Two different features are derived for the detection of arbitrary joint configurations with corresponding systematic image processing approaches. In the first step, we show the applicability of line detection methods for feature detection of arbitrary joint configurations. The necessary evaluation algorithm for case sensitivity and limitations (e.g., chamfer) in detecting different joint geometries are discussed. In the second step, we show an approach in feature extraction with feature detectors (e.g., ORB, SURF) for a new image feature. Here, significant image space from (multiple) reflections at the joint position is used for joint detection. The detectability is discussed depending on the joint configuration. The results show good suitability of both features for seam tracking applications.

In-process monitoring of weld penetration depth is possible with optical coherence tomography (OCT). The weld depth can be identified with OCT by statistical signal processing of the raw OCT signal and keyhole mapping. This approach is only applicable to stable welding processes and requires a time-consuming keyhole mapping to identify the optimal placement of a singular OCT measuring beam. In this work, we use an OCT measurement line for the identification of the weld depth. This approach shows the advantage that the calibration effort can be reduced as the measurement line requires only calibration in one dimension. As current literature focuses on weld depth measurement with a singular measurement point in the keyhole, no optimal algorithm exists for weld depth measurement with an OCT measurement line. We developed seven different weld depth processing pipelines and tested these algorithms under different weld conditions, such as stable deep penetration welding, unstable deep penetration welding, and heat conduction welding. We analyzed the accuracy of the weld depth processing algorithms by comparing the measured weld depth with metallographic weld depths. The intensity accumulation approach is identified as the most accurate algorithm for successful weld depth measurement with a scanning OCT measurement line.

Femtosecond laser direct writing is widely used to create waveguide circuits for optical processing in applications including communications, astrophotonics, simulation and quantum information processing. The properties of these waveguide circuits can be sensitive to the fabrication conditions, meaning that noticeable variability can be present in nominally identical manufactured components. One potential solution to this problem is the use of device trimming, whereby additional laser fabrication is applied to optimise the optical properties of a device based upon measurement feedback. We show how this approach can be used in the manufacture of directional couplers by overwriting the laser-written structure to alter the coupling ratios.