To be a successful competitor among other technologies, metallic laser-directed energy depositionusing a laser beam would benefit from the support of intelligent automation making the processrobust, repeatable, and cost-efficient. This calls for technology leaps towards robust and accuratedetection and estimation of the conditions during processing and control schemes for robustperformance. This chapter discusses how developments in sensor technology and model-basedsignal processing can contribute to advancements in in-process monitoring of directed energydeposition using a laser beam and how developments in model-based feedforward- and feedbackcontrol can support automation. The focus is on how machine vision, optical emission spectroscopy,thermal sensing, and electrical process signals can support monitoring, control and better processunderstanding. These approaches are industrially relevant and have a high potential to support amore sustainable manufacturing. 

Robotized laser beam welding of closed-square-butt joints is sensitive to the positioning of the laser beam with respect to the joint since even a small offset may result in a detrimental lack of sidewall fusion. An evaluation of a system using a photodiode aligned coaxial to the processing laser beam confirms the ability to detect variations of the process conditions, such as when there is an evolution of an offset between the laser beam and the joint. Welding with different robot trajectories and with the processing laser operating in both continuous and pulsed mode provided data for this evaluation. The detection method uses wavelet analysis of the photodetector signal that carries information of the process condition revealed by the plasma plume optical emissions during welding. This experimental data have been evaluated offline. The results show the potential of this detection method that is clearly beneficial for the development of a system for welding joint tracking.

We report on an experimental study of the incubation effect during irradiation of stainless steel targets with bursts of femtosecond laser pulses at 1030 nm wavelength and 100 kHz repetition rate. The bursts were generated by splitting the pristine 650-fs laser pulses using an array of birefringent crystals which provided time separations between sub-pulses in the range from 1.5 ps to 24 ps. We measured the threshold fluence in Burst Mode, finding that it strongly depends on the bursts features. The comparison with Normal Pulse Mode revealed that the existing models introduced to explain the incubation effect during irradiation with trains of undivided pulses has to be adapted to describe incubation during Burst Mode processing. In fact, those models assume that the threshold fluence has a unique value for each number of impinging pulses in NPM, while in case of BM we observed different values of threshold fluence for fixed amount of sub-pulses but different pulse splitting. Therefore, the incubation factor coefficient depends on the burst features. It was found that incubation effect is higher in BM than NPM and that it increases with the number of sub-pulses and for shorter time delays within the burst. Two-Temperature-Model simulations in case of single pulses and bursts of up to 4 sub-pulses were performed to understand the experimental results. © Copyright SPIE.

Abstract: We report on an experimental investigation of the incubation effect during irradiation of stainless steel with bursts of ultrashort laser pulses. A series of birefringent crystals was used to split the pristine 650-fs pulses into bursts of up to 32 sub-pulses with time separations of 1.5 ps and 3 ps, respectively. The number of selected bursts was varied between 50 and 1600. The threshold fluence was measured in case of Burst Mode (BM) processing depending on the burst features, i.e. the number of sub-pulses and their separation time, and on the number of bursts. We found as many values of threshold fluence as the combinations of the number of bursts and of sub-pulses constituting the bursts set to give the same total number of impinging sub-pulses. However, existing incubation models developed for Normal Pulse Mode (NPM) return, for a given number of impinging pulses, a constant value of threshold fluence. Therefore, a dependence of the incubation coefficient with the burst features was hypothesized and experimentally investigated. Numerical solutions of the Two Temperature Model (TTM) in case of irradiation with single bursts of up to 4 sub-pulses have been performed to interpret the experimental results. © 2018 Optical Society of America.

Laser beam welding offers high productivity and relatively low heat input and is one key enabler for efficient manufacturing of sandwich constructions. However, the process is sensitive to how the laser beam is positioned with regards to the joint, and even a small deviation of the laser beam from the correct joint position (beam offset) can cause severe defects in the produced part. With tee joints, the joint is not visible from top side, therefore traditional seam tracking methods are not applicable since they rely on visual information of the joint. Hence, there is a need for a monitoring system that can give early detection of beam offsets and stop the process to avoid defects and reduce scrap. In this paper, a monitoring system using a spectrometer is suggested and the aim is to find correlations between the spectral emissions from the process and beam offsets. The spectrometer produces high dimensional data and it is not obvious how this is related to the beam offsets. A machine learning approach is therefore suggested to find these correlations. A multi-layer perceptron neural network (MLPNN), support vector machine (SVM), learning vector quantization (LVQ), logistic regression (LR), decision tree (DT) and random forest (RF) were evaluated as classifiers. Feature selection by using random forest and non-dominated sorting genetic algorithm II (NSGAII) was applied before feeding the data to the classifiers and the obtained results of the classifiers are compared subsequently. After testing different offsets, an accuracy of 94% was achieved for real-time detection of the laser beam deviations greater than 0.9 mm from the joint center-line.

This study investigates the combination of three sensors to improve in-process monitoring of the liquid bridge between the feedstock wire and melt pool in hot-wire Directed Energy Deposition using Laser Beam. The stability of the deposition process relies on the transfer of metal between the molten feedstock wire and melt pool. Therefore, monitoring the condition of the liquid bridge and the interaction between the feedstock wire and melt pool is crucial. By utilizing a laser-optics-integrated visible range optical spectrometer and electrical sensors measuring voltage and current, relevant process changes and indications of instabilities were detected. Combined information from the current sensor and the spectrometer provided a better understanding of the process and helped to identify deviations leading to unstable deposition modes.

In this work, a fast optical spectrometer was used to monitor the Directed Energy Deposition (DED) process, during the deposition of Alloy 718 samples with different laser power, thus different energy inputs into the material. Spectroscopic measurements revealed the presence of excited Cr I atoms in the plasma plume. The presence was more apparent for the samples characterized by higher energy input. The Cr depletion from these samples was confirmed by lower Cr content detected by Energy-Dispersive X-ray Spectroscopy (EDS) analysis. The samples were also characterized by higher oxidation and high-temperature corrosion rates in comparison to the samples produced with low energy input. These results prove the applicability of an optical emission spectroscopic system for monitoring DED to identify process conditions leading to compositional changes and variation in the quality of the built material.

Experimental explorations of a spectrometer system used for in-process monitoring of the laser blown powder directed energy deposition of Alloy 718 is presented. Additive manufacturing of metals using this laser process experiences repeated heating and cooling cycles which will influence the final microstructure and chemical composition at every given point in the built. The spectrometer system disclosed, under certain process conditions, spectral lines that indicate vaporisation of chromium. Post process scanning electron microscope energy dispersive spectroscopy analysis of the deposited beads confirmed a reduction of chromium. Since the chromium concentration in Alloy 718 is correlated to corrosion resistance, this result encourages to further investigations including corrosion tests.

This study investigates the influence of resistive pre-heating of the feedstock wire (here called hot-wire) on the stability of laser-directed energy deposition of Duplex stainless steel. Data acquired online during depositions as well as metallographic investigations revealed the process characteristic and its stability window. The online data, such as electrical signals in the pre-heating circuit and images captured from side-view of the process interaction zone gave insight on the metal transfer between the molten wire and the melt pool. The results show that the characteristics of the process, like laser-wire and wire-melt pool interaction, vary depending on the level of the wire pre-heating. In addition, application of two independent energy sources, laser beam and electrical power, allows fine-tuning of the heat input and increases penetration depth, with little influence on the height and width of the beads. This allows for better process stability as well as elimination of lack of fusion defects. Electrical signals measured in the hot-wire circuit indicate the process stability such that the resistive pre-heating can be used for in-process monitoring. The conclusion is that the resistive pre-heating gives additional means for controlling the stability and the heat input of the laser-directed energy deposition.

In autogenous laser butt welding the variability of the joint gap can cause problems in terms of weld seam quality. A suitable strategy to alleviate this is to dynamically shape the laser beam instead of a circular-shaped beam with typical Gaussian or top hat distributions. Currently available systems cannot reach sufficient performance due to both the real time control system for the shape variation and the limited laser power currently manageable. In the present work, the possibility of bridging the joint gap during welding using a deformable mirror to elongate the focused laser beam from circular to transversal elliptical shape was investigated. The effect of the beam shaping on the geometry of the weld pool and of the weld cross sections was analysed, for different values of the gap in comparison with a circular Gaussian beam. It was demonstrated that the adoption of a transversal elliptical laser beam makes the welding process more stable, especially for large gaps (i.e. larger than the circular beam radius). Thanks to the beam shaping, the extension of the fused zone (in terms of the cross section area, height and width) resulted to be less sensitive to the gap's dimension; in addition, the extension of the heat affected zone and the presence of undercuts were evidently reduced.

This study explores the possibility of tailoring the fusion zone in conduction mode laser welding using a deformable mirror for beam shaping of multi-kilowatt continuous wave laser sources. Three power density distributions were shaped and used in bead on plate welding of Ti64 plates in conduction mode at three travel speeds. The effect on melt pool free surface geometry, cross section, microstructure and hardness profiles was measured and studied. It is shown that the geometry of the melt pool can be modified using a deformable mirror. A narrower and longer melt pool or a wider, shorter and shallower one were indeed obtained forming Gaussian-elliptical power density distributions oriented along and transverse to the travel direction, respectively. The latter distribution could be a favourable option for laser beam additive manufacturing as it could improve process efficiency while reducing remelting of the previous layer. This system has also a promising potential for adaptive process control since it could change fundamentally the beam shape at a rate faster than 10 ms. 

This study explores the uncharted territory of beam shaping through a novel deformable mirror system in directed energy deposition laser wire, an emerging area in Additive Manufacturing. While beam shaping has shown substantial benefits in laser processes like welding and powder bed fusion, its potential in this specific domain remains unexploited. The research investigates the influence of three near-elliptical Gaussian beam shapes on melt pool and bead geometries during deposition with stainless-steel wire. The study reveals three distinct processing modes achievable at the same total power through beam shaping, with significant modifications observed in melt pool and bead structures. Reduced bead geometry variation and enhanced process stability were achieved with the beam shape with major axis along the wire feeding direction, and with highest average power density and intermediate peak power density. The findings underscore the potential of beam shaping to enhance robustness and increase energy utilization and productivity in this process.  

This paper presents an experimental study where a vision camera integrates coaxially into a laser beam welding tool to monitor beam deviations (beam offset) in laser stake welding of T-joints. The aim is to obtain an early detection of deviations from the joint centreline in this type of welding where the joint is not visible from the top side. A polynomial surface fitting method is applied to extract features that can describe the behaviour of the melt pool. A nonlinear autoregressive with exogenous inputs neural network model is trained to relate eight image features to the laser beam offset. The performance of the presented model is evaluated offline by different welding samples. The results show that the proposed method can be used to guide post weld inspection and has the potential for on-line adaptive control. © 2019 The Author(s). Published by Elsevier B.V.

Laser Beam Welding (LBW) requires precise control to ensure high-quality welds. Accurate classification of joint gap widths and detection of tack welds are crucial for optimizing the process and enhancing product reliability.

This study investigates the application of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to classify instant joint gap widths and detect the presence of tack welds during welding. The goal is to facilitate adaptive joint gap bridging in robotized and autogenous butt joint welding. Sequences of images resembling a time series were captured during welding of prepared workpieces with varying joint gap widths along the joint line.

The results demonstrate that CNNs significantly outperform RNNs, achieving over 99 percent classification accuracy in both validation and test datasets, and 96 percent accuracy under conditions of substantial noise. These findings underscore the potential of CNNs in enhancing the precision and adaptability of welding automation. However, challenges remain in generalizing the CNN model to diverse and noisy operational environments.

In robotized laser welding of technical zero gap closed square butt joints it is critical to position the laser beam correct with regardsto the joint. Welding with an offset from the joint may cause lack of sidewall fusion, a serious defect that is hard to detect and gives a weak weld . When using machined parts with gap and misalignment between the parts that is close to zero, existing joint tracking systems will probably fail to track the joint. A camera based system using LED illumination and matching optical filters is proposed in this paper to address this issue. A high dynamic range CMOS camera and the LED illumination is integrated into the laser tool. The camera captures images of the area in front of the melt pool where the joint is visible and an algorithm based on the Hough transform and a Kalman filter estimates the offset between the laser spot and the joint position. Welding experiments, using a 6 kW fiber laser, have been conducted to evaluate the performance of the system. Promising results are obtained that can be used in the further development of a closed loop controlled joint tracking system.

A vision and spectroscopic system for estimation of the joint gap width in autogenous laser beam butt welding is presented. Variations in joint gap width can introduce imperfections in the butt joint seam, which in turn influence fatigue life and structural integrity. The aim of the monitoring approach explored here is to acquire sufficiently robust process data to be used to guide post inspection activities and/or to enable feedback control for a decreased process variability. The dual-sensing approach includes a calibrated CMOS camera and a miniature spectrometer integrated with a laser beam tool. The camera system includes LED illumination and matching optical filters and captures images of the area in front of the melt pool in order to estimate the joint gap width from the information in the image. The intensity of different spectral lines acquired by the spectrometer has been investigated and the correlation between the intensity of representative lines and the joint gap width has been studied. Welding experiments have been conducted using a 6 kW fiber laser. Results from both systems are promising, the camera system is able to give good estimations of the joint gap width, and good correlations between the signal from the spectrometer and the joint gap width have been found. However, developments of the camera setup and vision algorithm can further improve the joint gap estimations and more experimental work is needed in order to evaluate the robustness of the systems.

Robotized laser beam welding of closed-square-butt joints is sensitive to how the focused laser beam is positioned in relation to the joint, and existing joint tracking systems tend to fail in detecting the joint when the gap and misalignment between the work pieces are close to zero. A camera-based system is presented based on a high dynamic range camera operating with LED illumination at a specific wavelength and a matching optical filter. An image processing algorithm based on the Hough transform extracts the joint position from the camera images, and the joint position is then estimated using a Kalman filter. The filter handles situations, when the joint is not detectable in the image, e.g., when tack welds cover the joint. Surface scratches, which can be misinterpreted as being the joint, are handled by a joint curve prediction model based on known information about the nominal path defined by the robot program. The performance of the proposed system has been evaluated off line with image data obtained during several welding experiments.

The automated laser beam butt welding process is sensitive to positioning the laser beam with respect to the joint because a small offset may result in detrimental lack of sidewall fusion. This problem is even more pronounced incase of narrow gap butt welding, where most of the commercial automatic joint tracing system fail to detect the exact position and size of the gap. In this work, adual vision and spectroscopic sensing approach is proposed to trace narrow gap butt joints during laser welding. The system consists of a camera with suitable illumination and matched optical filters and a fast miniature spectrometer. An image processing algorithm of the camera recordings has been developed in order to estimate the laser spot position relative the joint position. The spectral emissions from the laser induced plasma plume has been acquired by the spectrometer, and based on the measurements of the intensities of selected lines of the spectrum, the electron temperature signal has been calculated and correlated to variations of process conditions. The individual performances of these two systems have been experimentally investigated and evaluated offline by data from several welding experiments where artificial abrupt as well as gradual excursions of the laser beam out of the joint were produced. Results indicate thata combination of the information provided by the vision and spectroscopic systems is beneficial for development of a hybrid sensing system for joint tracing.

A computational fluid dynamics approach is used to analyse the influence of beam shaping in fusion welding on melt thermal flow. Three beam shapes are studied at several welding travel speeds: a reference Gaussian profile and its elliptic elongations along and transverse to the welding travel direction. It is found that these beam shapes change not only the intensity and direction of the melt thermocapillary flow but also the flow pattern. For instance, and contrary to the other profiles, the beam shape elongated along the welding travel direction generates melt front vortices that assist metal pre-heating. It can result in deeper penetration, larger melt volume, and lower amount of thermal energy diffused into the heat affected zone. The simple elongation of a beam profile has thus a non-linear effect on the melt flow and in turn on the seam geometry as well as the temperature gradients in the heat affected zone.

In this work the single-pulse laser irradiation of a hypereutectoid steel was investigated using a fiber laser source, in a range of process parameters enabling surface hardening and remelting. Effects of laser power, pulse energy and defocusing distance were investigated using a numerical/experimental approach. Laser surface treatments were conducted on uncoated samples without any gas shielding, changing both the laser power and the pulse energy, and exploring a wide range of defocusing distances. Numerical simulations were conducted using a finite element model calibrated by means of an optimization procedure based on a specific calculation algorithm and using a subset of experimental data producing surface melting. Using both simulations and experiments, the process operating windows of the discrete spot laser treatment were determined: it was found that, when varying the laser power between 250 W and 750 W, melt-free hardened zones are produced with a maximum extension between 0.7 mm and 1.0 mm; on the contrary, in case of more tightly beam focusing conditions, surface melting occurred with a size of the re-melted areas ranging between 1.0 mm and 1.4 mm. Results further showed that a small change (generally 2–3 mm) of the defocusing distance suddenly brings the material from melting to a non-hardening condition. © 2016 Elsevier Ltd

The single-pulse laser hardening of a hypereutectoid steel coated by a graphite layer was investigated using a numerical/experimental approach. Experimental tests were conducted on coated samples using a fibre laser source and without any gas shielding aiming to explore the effect of laser power, pulse energy and defocusing distance on the dimensions of the hardened region. The process operating window of the discrete spot laser hardening using the graphite layer was determined through a finite element model and compared with previous results obtained on uncoated samples. For the same laser power and interaction times, an enlargement of the hardened region was found when using the graphite coating, especially when operating at the lowest laser energy level. The process operating window remains similar in shape to the one of the uncoated steel but moves towards larger hardened diameters and much larger defocusing distances. Once the maximum temperature has been fixed, a linear relationship between the hardened diameter and the defocusing distance exists. No obvious surface oxidation occurs since the graphite coating acts as a protective layer. © 2019, Springer-Verlag London Ltd., part of Springer Nature.

Microfluidic optical stretchers are valuable optofluidic devices for studying single cell mechanical properties. These usually consist of a single microfluidic channel where cells, with dimensions ranging from 5 to 20 Όm are trapped and manipulated through optical forces induced by two counter-propagating laser beams. Recently, monolithic optical stretchers have been directly fabricated in fused silica by femtosecond laser micromachining (FLM). Such a technology allows writing in a single step in the substrate volume both the microfluidic channel and the optical waveguides with a high degree of precision and flexibility. However, this method is very slow and cannot be applied to cheaper materials like polymers. Therefore, novel technological platforms are needed to boost the production of such devices on a mass scale. In this work, we propose integration of FLM with micro-injection moulding (ΌIM) as a novel route towards the cost-effective and flexible manufacturing of polymeric Lab-on-a-Chip (LOC) devices. In particular, we have fabricated and assembled a polymethylmethacrylate (PMMA) microfluidic optical stretcher by exploiting firstly FLM to manufacture a metallic mould prototype with reconfigurable inserts. Afterwards, such mould was employed for the production, through ΌIM, of the two PMMA thin plates composing the device. The microchannel with reservoirs and lodgings for the optical fibers delivering the laser radiation for cell trapping were reproduced on one plate, while the other included access holes to the channel. The device was assembled by direct fs-laser welding, ensuring sealing of the channel and avoiding thermal deformation and/or contamination. © 2017 SPIE.