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Spinel Li4Ti5O12 (LTO) is a promising anode material for solid state thin film batteries (SSTB) due to its almost-zero volume change and promising Li-ion mobility. However, preparing LTO anodes for SSTB demands tedious vacuum-based processing steps that are not cost effective. In this context, the present study embarks on evaluating the versatile suspension plasma spraying (SPS) approach to fabricate LTO coatings without using any binder. The microstructure and stoichiometry of the fabricated LTO coatings developed through the SPS route reveals retention of ∼76 wt.% of the spinel LTO from the starting feedstock, with minor amounts of rutile and anatase TiO2. The SPS experiments yielded varying thickness build up rates of the LTO coatings depending on the processing parameters adopted. The electrochemical data of the produced LTO based electrode tested in a half-cell through galvanostatic cycling show reversible lithiation and delithiation at expected potential, thereby validating the promise of the SPS technique for potential fabrication of SSTB components once fully optimized.

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., CC BY 4.0

Nowadays, conventional welding technologies such as submerged arc welding (SAW) are still used in most heavy-steel industries. This type of traditional technology means that welding takes up a large part of the productive time. As a solution to this problem, there are welding methods, such as Laser-Arc Hybrid Welding (LAHW), that have the potential to reduce the cost of manufacturing large steel structures. This is possible due to the reduced number of weld passes required to join thicker steel sections, as large thicknesses can be welded in one or a few passes. A problem with LAHW is achieving satisfactory quality. For this reason, it is essential to study the starting conditions, e.g. edge joint preparation. The target of this research work is to find out the relationship between the penetration value of the weld bead obtained and the edge joint preparation. The evolution of the molten pool and the behavior of the molten material in the joint is discussed for the different edge joint preparation configurations. The effect of the roughness is that it affects the wetting of the molten material in the joint, which would affect the penetration result, together with the gap and air volume gap used in the joint. Cut-wire is also used in the research, in samples that presented a larger air volume gap. The behavior of the molten metal inside the joint in this case is also discussed. In addition, the quality of the weld beads has also been determined by making macrographs, microstructural analysis, X-ray, microhardness profiles, tensile test and Charpy test. Some pores and cracks have been found, although destructive tests show adequate behavior of the weld bead. It is possible to elucidate from the findings that as the roughness, gap and/or air volume gap of the edge joint increases, the penetration value obtained increases. Cut-wire samples obtained full penetration., Validerad;2024;Nivå 2;2024-09-06 (joosat);Full text License: CC BY-NC

Computational modeling of the melt pool dynamics in laser-based powder bed fusion metal additive manufacturing (PBF-LB/M) promises to shed light on fundamental mechanisms of defect generation. These processes are accompanied by rapid evaporation so that the evaporation-induced recoil pressure and cooling arise as major driving forces for fluid dynamics and temperature evolution. The magnitude of these interface fluxes depends exponentially on the melt pool surface temperature, which, therefore, has to be predicted with high accuracy. The present work utilizes a diffuse interface finite element model based on a continuum surface flux (CSF) description of interface fluxes to study dimensionally reduced thermal two-phase problems representative for PBF-LB/M in a finite element framework. It is demonstrated that the extreme temperature gradients combined with the high ratios of material properties between metal and ambient gas lead to significant errors in the interface temperatures and fluxes when classical CSF approaches, along with typical interface thicknesses and discretizations, are applied. It is expected that this finding is also relevant for other types of diffuse interface PBF-LB/M melt pool models. A novel parameter-scaled CSF approach is proposed, which is constructed to yield a smoother temperature field in the diffuse interface region, significantly increasing the solution accuracy. The interface thickness required to predict the temperature field with a given level of accuracy is less restrictive by at least one order of magnitude for the proposed parameter-scaled approach compared to classical CSF, drastically reducing computational costs. Finally, we showcase the general applicability of the parameter-scaled CSF to a 3D simulation of stationary laser melting of PBF-LB/M considering the fully coupled thermo-hydrodynamic multi-phase problem, including phase change.

In the battery pack assembly, it is essential to ensure that the cell-to-busbar joints can be produced with high quality and with minimal impact on the individual battery cells. This study examines the influence of process parameters on the joint quality for nickel-plated copper and steel plates, laser welded in an overlap configuration. Artificial neural network-based meta models, trained on numerical results from computational fluid dynamics simulations of the laser welding process, are used to predict and evaluate the joint quality. A set of optimized process parameters is identified, in order to simultaneously maximize the interface width for the joints, and minimize the formation of undercuts and in-process temperatures. In an meta model-based multi-objective optimization approach, the non-dominated sorting genetic algorithm II (NSGA-II) is used to efficiently search for trade-off solutions and the meta models are used for objective approximation. As a result, the objective evaluation time is decreased from around 9 h, when evaluated directly from numerical simulations, to only tenths of a second. From the Pareto-optimal front of trade-off solutions, three optimal solutions are selected for validation. The selected solutions are validated through laser welding experiments and numerical simulations, resulting in joints with large interface widths and low in-process temperatures without a full penetration., CC BY-NC-ND 4.0Available online 22 October 2024Corresponding author: andreas.andersson.lassila@his.seThis work was supported financially by Vinnova through the Produktion 2030 project QWELD (dnr: 2021-03693)., QWELD

Residual stress (RS) within titanium alloy structural components is the primary factor contributing to machining deformation. It comprises initial residual stress （IRS） and machined surface residual stress (MSRS), resulting from the interplay between IRS and high-level machining-induced residual stress MIRS). Machining deformation of components poses a significant challenge in the aerospace industry，and accurately assessing RS is crucial for precise prediction and control. However, current RS prediction methods struggle to account for various uncertainties in the component manufacturing process，leading to limited prediction accuracy. Furthermore, existing measurement methods can only gauge local RS in samples，which proves inefficient and unreliable for measuring RS fields in large components. Addressing these challenges, this paper introduces a method for simultaneously estimating IRS and MSRS within titanium alloy aircraft components using a Bayesian framework. This approach treats IRS and MSRS as unobservable fields modeled by Gaussian processes. It leverages observable deformation force data to estimate IRS and MSRS while incorporating prior correlations between MSRS fields. In this context，the prior correlation between MSRS fields is represented as a latent Gaussian process with a shared covariance function. The proposed method offers an effective means of estimating the RS field using deformation force data from a probabilistic perspective. It serves as a dependable foundation for optimizing subsequent deformation control strategies., CC BY-NC-ND 4.0© 2024 Nanjing University of Aeronautics an Astronautics. All rights reserved.Correspondence Address: C. Liu; College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China; email: liuchangqing@nuaa.edu.cn; CODEN: TNUAFThis work was supported by the National Key R&D Program of China (No.2022YFB3402600), the National Science Fund for Distinguished Young Scholars (No.51925505), and the General Program of the National Natural Science Foundation of China（No.52175467).

To advance quality assurance in the welding process, this study presents a deep learning (DL) model that enables the prediction of two critical welds’ key performance characteristics (KPCs): welding depth and average pore volume. In the proposed approach, a wide range of laser welding key input characteristics (KICs) is utilized, including welding beam geometries, welding feed rates, path repetitions for weld beam geometries, and bright light weld ratios for all paths, all of which were obtained from hairpin welding experiments. Two DL networks are employed with multiple hidden dense layers and linear activation functions to investigate the capabilities of deep neural networks in capturing the complex nonlinear relationships between the welding input and output variables (KPCs and KICs). Applying DL networks to the small numerical experimental hairpin welding dataset has shown promising results, achieving mean absolute error values of 0.1079 for predicting welding depth and 0.0641 for average pore volume. This, in turn, promises significant advantages in controlling welding outcomes, moving beyond the current trend of relying only on defect classification in weld monitoring to capture the correlation between the weld parameters and weld geometries., Author to whom correspondence should be addressed; electronic mail: amena.darwish@his.seAIP Publishing is a wholly owned not-for-profit subsidiary of the American Institute of Physics (AIP).Paper published as part of the special topic on Laser Manufacturing for Future Mobility

Paper C, D and E are to be submitted and not included in this digital thesis.

Laser metal fusion is widely used in production technology to manufacture parts, as in welding, cladding, and additive manufacturing. One development of interest to laser metal fusion is the recent advancements in deformable mirror technologies that allow them to withstand multi-kilowatt laser power. This enables the generation of various beam shapes and rapid switching between these within 10 milliseconds. This thesis investigates the application of deformable mirror-based beamshaping and computer vision techniques to improve laser beam welding and directed energy deposition using laser and wire. Additionally, methods including analysis of melt pool images, cross-cut micrographs, surface topology measurements has been used to evaluate and characterize the results. An industrially relevant challenge addressed is variation in the joint gap width during autogenous butt welding, which often results in defects such as incomplete groove filling and root concavities. Two near-elliptical beam shapes, with major axes aligned either along or transverse to the welding direction, were studied for gap bridging. Both beam shapes were capable of bridging gaps up to 0.6 mm wide during welding of 2.0 mm thick steel plates. It was shown that the beam shaping made it possible to meet higher quality levels in the ISO13919-1 standard compared to a ordinary circular static beam. The beam with the major axis along the welding direction performed even better in reducing defects compared to the one aligned transversely. When adaptive beam shaping was used for gap bridging in butt joints it resulted in an 80% reduction in workpiece distortion, demonstrating its effectiveness in accommodating varying process conditions. Additionally, computer vision algorithms, including adaptive Kalman filters and convolutional neural networks, proved successful in gap width estimation, classification, and tack weld detection under varying conditions during welding. In directed energy deposition using laser, Lasersmältning av metall är en produktionsteknik som används for att tillverka komponenter, till exempel genom svetsning, påläggssvetsning eller additiv tillverkning. En utveckling som är intressant för lasersmältning är de senaste framstegen inom formbar spegelteknik gör att denna typ av spegeloptik kan klara av en lasereffekt på flera kilowatt, samt frambringa olika strålformer (beam shapes) och snabbt växla mellan dessa inom 10 millisekunder. Denna avhandling undersöker ett system med en deformerbar spegel för laserstrålformning i kombination med datorseendeteknik (computer vision) för att effektivisera lasersvetsning och additiv tillverkning. Dessutom har metoder som analyserar bilder på smältan i processen, bilder på den resulterande mikrostrukturen i tvärsnitt samt topologimätningar använts för att utvärdera och karakterisera resultaten. En industriellt relevant utmaning som undersökts är variationen i fogspaltbredd under stumfogsvetsning utan tillsatstråd, vilket ofta resulterar i defekter såsom svetsdiken. Två elliptiska laserstrålformer, med huvudaxlar riktade antingen längs med eller tvärs mot svetsriktningen, studerades med avseende på förmågan att överbrygga fogspalten.Båda strålformerna kunde överbrygga en fogspalt på upp till 0,6 mm vidsvetsning av 2,0 mm tjocka stålplåtar. Det visade sig att strålformningen gjorde det möjligt att uppfylla högre kvalitetsnivåer enligt ISO13919-1-standarden jämfört med en vanlig cirkulär statisk laserstråle. Laserstrålen med huvudaxelnl ängs svetsriktningen presterade ännu bättre när det gällde att minska defekterj ämfört med den som var på tvären. Den adaptiva strålformningen som används för överbryggning av spalter i stumfogar resulterade i en 80-procentig minskning av arbetsstyckets deformation, vilket demonstrerar dess effektivitet när det gäller att hantera varierande processförhållanden. Dessutom visade algoritmer för datorseende bland annat med ett adaptivt Kalman-filter eller ett neuralt nätverk, vara framgångsr, Following papers are not included in the electronic thesis:Paper 3 and 4 are to be submitted.Paper 5 has no permission to be included in the electronic thesisPaper 6 is under review.

Arbetet undersöker förbättring inom produktionsteknik, med särskilt fokus på additiv tillverkning (AM) och tekniker såsom Powder Bed Fusion-Electron Beam(PBF-EB) och Powder Bed Fusion-Laser Beam (PBF-LB), för att förstå strukturegenskapsrelationer i komplexa mikrostrukturer hos nickelbaserade högpresterande superlegeringar. Det primära målet är att förstå och förutsäga de riktade elastiska egenskaperna och mikrostrukturella beteenden hos material som Inconel 718, Haynes 282 och Hastelloy X. Genom att använda 2D Electron Backscatter Diffraction (EBSD) data samt metoder för mikrostrukturkarakterisering i MTEX, och genom att generera representativa volymelement (RVE) och representativa areaelement (RAE) i NEPER, erhålls detaljerade 3D-representationer av mikrostrukturer. Forskningen använder både ideala och verkliga mikrostrukturer för att fördjupa kunskapen om riktad elasticitet hos polykristaller, samt spännings- och töjningsfördelningar inom heterogena och icke-homogena kornstrukturer. Beräkningsmässig homogenisering (CH), implementerad via ABAQUS, inkluderar Crystal Finite Element (CEFE) metoden, vilken är avgörande för att generera styvhetsmatriser och förutsäga riktade elastiska egenskaper. Genom att integrera dessa metoder möjliggörs en omfattande analys av isotropt och anisotropt beteende, särskilt inom ekviaxiella, kolumnära och kombinerade (ekviaxiella och kolumnära) kornstrukturer. Genom experimentell validering ger de viktigaste resultaten betydande insikter i hur olika mikrostrukturer påverkar mekaniska egenskaper, vilket förbättrar prediktiva möjligheter och noggrannhet i analysen av AMmaterialprestanda. Simuleringsresultaten betonar vikten av en noggrann representation av mikrostrukturen, med hänsyn till både kristallografisk textur och faktisk kornmorfologi. De bifogade publikationerna stöder dessa resultat och erbjuder detaljerade diskussioner om virtuell testning av mikrostrukturrepresentation. Arbetet visar sammantaget potentialen hos avancerade PBF, This work investigates advancements in Production Technology, specifically focusing on Additive Manufacturing (AM) techniques such as Powder Bed Fusion-Electron Beam (PBF-EB) and Powder Bed Fusion-Laser Beam (PBF-LB), to understand the structure-property relationships of complex microstructures in high-performance Ni-based superalloys. The primary objective is to comprehend and predict the directional elastic properties and microstructural behaviour of materials such as Inconel 718, Haynes 282, and Hastelloy X. Utilizing 2D Electron Backscatter Diffraction (EBSD) data, methods such as microstructure characterization in MTEX, Representative Volume Element (RVE) and Representative Area Element (RAE) generation in NEPER, detailed 3D microstructure representations are obtained. The research employs both idealand real microstructures to advance knowledge about directional elasticity of polycrystals, stress, and strain distributions within heterogeneous and nonhomogeneous grain structures. The Computational Homogenization (CH) approach, implemented via ABAQUS, includes the Crystal Elasticity Finite Element (CEFE) method, essential for generating stiffness matrices and predicting directional elastic properties. Integrated methodologies facilitate a comprehensive analysis of isotropic and anisotropic behaviour, particularly within equiaxed, columnar, and combined (equiaxed and columnar) grain structures. Through experimental validation, the key findings provide significant insights into the influence of different microstructures on mechanical properties, enhancing predictive capabilities and accuracy in AM material performance analysis. The simulation results emphasize the importance of accurate microstructure representation, considering both crystallographic texture and actual grain morphology. The appended publications support these findings, offering detailed discussions on virtual testing of ideal microstructure predictions and real microstructure representation. This w, Paper C is to be accepted and not included in this licentiate.

CC BY 4.0

CC-BY 4.0

In the underlying study, a method has been proposed to automatically extract finite element (FE) peak stresses of welded components to alleviate human errors and increase the calculation accuracy. The approach is based on the K-means and DBSCAN (density-based spatial clustering of applications with noise) methods as the unsupervised machine learning approaches. Data points, in this case, nodal coordinates and their corresponding stress magnitudes, are grouped within different clusters. The peak stress in each dense region (cluster) is then highlighted and reported automatically. Parametric and comparative studies have also been carried out in order to detect optimised parameters of the K-means and DBSCAN algorithms. The methodology will ultimately be used for more reliable stress analysis in fatigue assessment of welded structures.

Transition metal carbides are valued for high hardness, thermal and mechanical stability, but fall short in fracture toughness. Contrarily, their less hard transition metal nitride counterparts offer more favorable fracture characteristics. Here, we use magnetron-sputtering to synthesize nitrides and carbides-TiC/TaN, TiN/TaC-in a nanolaminate superlattice (SL) architecture and compare their properties (hardness, fracture toughness, thermal stability) with that of their layer materials, as well as of carbide SLs, TiC/TaC. Except for the monolithically grown TaN and TiC/TaN SLs with nominal bilayer periods above 14 nm, all other coatings are purely fccstructured and feature close-to-stoichiometric compositions, revealed by EBS-ERDA and XRF measurements. In-situ X-ray diffraction investigations indicate that the monolithically grown coatings have poor thermal stability compared to the SLs, which remain stable up until well over 1000-degrees C. While the TiC/TaC superlattices retain the highest hardness of all three systems, with 44.1 +/- 3.4 GPa at a bilayer period (Lambda) of 2 nm, the TiN/TaC system exhibits significantly higher fracture toughness values with up to 4.75 +/- 0.33 MPa root m for the Lambda = 14 nm coating. The TiC/TaN system exhibits neither hardness nor fracture toughness enhancement, as explained by the formation of a secondary hexagonal Ta2N phase.

Stoichiometric CrN and Cr:N with different nitrogen (N) content are of interest for hard coating applications. In the Cr-N material system, bcc-Cr rich coatings, containing a few percent of diluted N, provide tunability in microstructure and mechanical properties. Additionally, the incorporation of Nb into the CrNx coatings may further tailor the materials properties. In this work, bcc-CrNx and CrNbNx coatings were deposited by reactive magnetron sputtering, and their mechanical and microstructural characteristics were investigated as a function of N content. Depending on the N content, the phases observed by X-ray diffractometry (XRD) varied from metallic bcc-Cr, mixed bcc-Cr/h-Cr2N, to h-Cr2N/CrN. X-ray reflectivity (XRR), and scanning electron microscopy (SEM) measurements show that a dense and nearly columnar-free bcc-CrNx coatings was obtained at ~13–25 at.% of N, while CrNbNx coatings composed of dense, column-free, and featureless microstructure at a N content of ~10–20 at.%. The dense and nearly column-free microstructure composed of dispersion of Cr2N grains into the bcc-Cr matrix for both CrNx and CrNbNx coatings, as shown by high resolution transmission electron microscope analysis (HRTEM). Nanoindentation revealed a hardening of the coatings due to the grain refinement, solid solution strengthening, and variation in phase content.

Robotized laser beam welding is one important process in manufacturing, offering efficient welding while minimizing the heat input. Nonetheless, this method is sensitive to various deviations, including fixture problems, heat-induced distortions, and inaccuracies in tool handling. Such deviations can lead to significant defects like lack of fusion, particularly when welding square butt joints without gaps. Detecting these defects through visual inspection or non-destructive methods is challenging. To address this, real-time monitoring and automatic intervention are necessary. One effective sensor for monitoring laser beam welding is the photodiode, which captures optical emissions from the process. Research has demonstrated correlations between these emissions and process stability. Photodiodes are costeffective and easily integrated into welding tools, making them ideal for industrial applications. However, the challenge lies in analyzing the output signals and defining thresholds for identifying deviations from normal conditions. Thus, there's a need for an automated method to set threshold values based on measured data. Machine learning offers a solution, particularly through supervised, unsupervised, or semi-supervised methods. Supervised machine learning requires labeled data, involving time-consuming experiments with nominal and deviating cases, making it less feasible for industrial setups. This paper suggests using unsupervised learning for anomaly detection, relying solely on data from nominal welding cases for model training. In this approach, a model is trained using photodiode data from a single nominal weld case and subsequently tested on data collected during experiments involving laser beam offsets during welding. The results demonstrate the promise of this method for monitoring closed square butt-joint laser beam welding, even with limited training data from nominal cases., CC BY NC 4.0

Although widely adopted around the globe, emerging evidence suggests that digitalization investments often underperform. One potential reason is that firms lack organizational readiness to adopt these new technologies. Thus, in this paper, we evaluate both digitalization implementation and digital readiness in the Brazilian auto industry to ascertain how readiness potentially impacts the implementation of new digital technologies and processes. In reviewing the literature on digital transformation in the global automotive sector, a lack of studies was identified on the level of readiness and maturity of the automotive sector in relation to digitalization and innovation brought out by the implementation of Industry 4.0 technologies. To address this gap, a digitalization protocol was drawn up with the aim of verifying the maturity of companies and understanding the degree of readiness for digital transformation. Subsequently, the research was applied to thirteen companies in the automotive sector, including vehicle and engine manufacturers, as well as automotive parts and systems subcontractors in the automotive supply chain. The contribution of this paper identified that the use of digital technologies increases the quality and results of work, facilitates the achievement of objectives, and offers a competitive advantage. Further’ advantages come from improving customer experience, increasing innovation through data analysis, improving manufacturing processes, and bringing greater employee engagement. Finally, it is highlighted that this study is aligned with the ninth Sustainable Development Goal (SDG) proposed by the United Nations: Industry, Innovation, and Infrastructure, which seeks to promote inclusive and sustainable industrialization and foster innovation., Open Access

The topological characteristics of the down-skin surfaces for as-built components by laser powder bed fusion (LPBF) are particularly representative, while the study on the improvement of the surface quality of these surfaces remains largely unexplored. Herein, the laser polishing of LPBF-built components with different inclination angles was systematically investigated with an emphasis on the down-skin surfaces. Our result shows that the topography of the top surface is independent of the inclination angle, and the surface topography of the down-skin surface is dominated by additional angle-dependent surface characteristics. It also indicates that the surface roughness can be reduced sharply when increasing the laser power from 40 W to 60 W, and the reduction slows down when further increasing the laser power while decreasing the scanning speed leads to a progressive improvement of the surface morphology. Moreover, a second-order regression model was established to evaluate the influence of the initial surface morphology and polishing parameters on the polished surface roughness and to achieve surface roughness optimization. Therefore, our established methodology can be readily applied to surface morphology manipulation and process optimization for laser polishing of widely used metals and alloys fabricated by the additive manufacturing process.

High-density interconnect (HDI) technology for liquid metal (LM)-based stretchable printed circuit boards is crucial for expanding their applicability. HDI technology provides high-resolution multilayer circuits with a high density of components, as required for next generation of neuroprobes and ultrasonic and sensor arrays. This study presents a HDI technique utilizing laser engraved micro grooves in silicone with a protective lift-off mask of polyvinyl alcohol (PVA) and subsequent microscale LM particle spray deposition. This approach achieves high-resolution LM patterns and enables multilayer connectivity and high-density integration of components simultaneously, that is, realizing HDI technology. It is demonstrated using a stretchable 0201 LED display with a density of six leads per mm2 and a cochlear implant (CI) electrode array. The demonstrated manufacturing of the CI has the potential to enable fully automated printed circuit board manufacturing of such implants with increased precision and throughput. Implants in guinea pigs show that the CI is capable of activating the auditory neuron with electrical auditory brainstem response (eABR) and electrical compound action potential (eCAP) of high quality. Moreover, the U-shaped cross section of the LM interconnects provides a higher mechanical shock resistance of the circuit than that of normal rectangular cross sections.

Paper 3 is not included in the elecronic licentiate thesis.

Surface tension is an essential material property that defines many aspects of thermal processes involving liquids. Metal materials have highmelting temperatures, and surface tension could often be measured around melting temperature and is, therefore, known for many purematerials and simple material systems. However, high-energy input during laser, electron beam, or plasma processes is known to increase the material temperatures far above the melting point. To build theoretical models, simulate processes, and increase process understanding,surface tension values at those high temperatures would be beneficial to know. However, it can be difficult to create stable circumstancesand measure surface tension in those conditions. Therefore, it is suggested in this work to indirectly derive surface tension values from thepressure balance inside keyholes created during laser deep penetration processing. A variety of different keyhole shapes were created usingdynamic beam shaping by means of coherent beam combining. From the observed keyhole shapes using inline x-ray observations, temperature distributions on the keyhole walls were calculated using ray tracing. The temperature defines the local recoil pressure that counteractsthe surface tension pressure, which contains the surface tension value as the only unknown variable. At increasing temperatures above the boiling point, an increasing surface tension was observed., CC-BY 4.0The authors kindly acknowledge the funding of SMART—Surface tension of Metals Above vapoRization Temperature(Vetenskapsrådet—The Swedish Research Council, 2020-04250). Thework was partially funded by the Deutsche Forschungsgemeinschaft(DFG, German Research Foundation) under No. 503306266. The collaboration expenses were supported by the InnovationCampus FutureMobility funded by the Baden-Württemberg Ministry of Science,Research and the Arts.

During laser processing, complex effects can occur regarding the laser-material interactions. A high laser energy input leads to surface melting and even boiling. The resulting recoil pressure can create the so-called keyhole, a vapor channel existing during welding and called cut front during laser cutting. On the keyhole front wall, the induced recoil pressure pushes the melt downwards and can ejects melt drops. Usually, those melt ejections are seen as undesired spattering or necessary waste to enable the cutting. However, outflow characteristics can tell more about the complex process behavior. Therefore, this work aimed to relate melt ejection formation effects to keyhole behavior in order to get a better understanding of the complex laser-matter-interactions and fluid flows. Axial beam shaping was used to create different energy inputs into the keyhole front walls. Beam shaping was done with an optic that can superposition up to four laser beams in axial direction, leading to varying intensity distributions on the inclined keyhole front walls. Based on high-speed image analysis, it was seen that different outflow characteristics occur depending on the beam shapes. A high intensity on the front keyhole wall could be related to high temperatures on the keyhole wall. The outflow mechanism was shown to be able to move from corrugating to atomizing drop generation at increasing temperature due to temperature-dependent material properties. The main influencing factors are assumed to be the vapor speed and the keyhole/drop diameters that define the outflow mechanism., CC-BY 4.0The author acknowledge the funding of PoSAddive – Powder Sheet AdditiveManufacturing (EIT raw materials, No. 22021) and SMART - Surface tension of MetalsAbove vapoRization Temperature (Vetenskapsrådet, No. 2020-04250).

The level of ferritization in the high temperature heat-affected zone (HT-HAZ) affects the weldability of duplex stainless steels. The modern grades show different sensitivity and especially the nitrogen content has been proposed to control the grain growth and austenite formation. In this work, 3-, 4- and 5-mm thick UNS S32101, UNS S32304, UNS S32205 and UNS S32750 with a nitrogen range of 0.09–0.28 wt.-% were considered. Gas tungsten arc welding (GTAW) was conducted bead-on-plate with pure argon (Ar) and Ar + 2% N2 as shielding gas. Measurements of the HT-HAZ width and ferrite content were compared with values reported for welds and thermo-mechanical Gleeble® simulations in existing literature. The HT-HAZ width decreased with the material thickness and the nitrogen content in the base metal, while only the nitrogen alloying had a clear effect on the phase balance. Nitrogen additions to the shielding gas efficiently counteracted weld metal nitrogen loss and improved the austenite formation as compared to 100% Ar but had no clear effect on the HT-HAZ width nor ferrite content. A positive influence of the base material nitrogen content on the phase balance could be validated with thermodynamic simulations using Thermo-Calc and DICTRA, but the negative effect of high cooling rates was underestimated., CC-BY 4.0

Additive manufacturing (AM) methods like powder bed fusion–laser beam (PBF-LB) enablecomplex geometry production. However, understanding and predicting the microstructural properties of AM parts remain challenging due to the inherent non-homogeneity introduced during the manufacturing process. This study demonstrates a novel approach for 3D microstructure representation and virtual testing of non-homogeneous AM materials using 2d electron backscatter diffraction (EBSD) data. By employing the representative volume element (RVE) method, we reconstruct the 3D microstructure from 2D EBSD datasets, effectively capturing the grain morphological characteristicsof PBF-LB-produced Hastelloy X. Using validated RVE data, we artificially generate combinations of two grain textures to gain deeper insight into locally affected areas, particularly the stress distribution within the interfaces, as well as global material behavior, exploring non-homogeneity. Computational homogenization (CH) utilizing a crystal elasticity finite element (CEFE) method is used to virtually test and predict directional elastic properties, offering insights into relationships between microstructure evolution and property correlation. The experimentally validated results show a strong correlation, with only 0.5–3.5% correlation error for the selected grain tessellation method.This consistency and reliability of the methodology provide high confidence for additional virtual tests predicting the properties of non-homogeneous, artificially generated combined-grain structures., CC BY 4.0

Purpose This study addresses the critical imperative of quantifying building information modeling (bimalliance) benefits by augmenting existing methodologies, with a focus on monetization. Engaging industry practitioners, the research develops a comprehensive framework through an exhaustive literature review and a survey in the Swedish construction industry, incorporating insights from 128 respondents. Design/methodology/approach The framework, validated by industry experts, systematically assesses tangible BIM benefits against associated costs. It introduces a novel method in construction, addressing the lack of a unified approach. The resulting framework facilitates nuanced feasibility determinations by systematically evaluating BIM benefits against costs. Findings Despite its acknowledged limitations, the framework effectively captures a comprehensive range of costs and benefits, providing a more accurate and detailed estimation of BIM’s impact on project outcomes. Practical implications With practical implications, the framework enhances BIM understanding and application, contributing to effective project management throughout the construction supply chain lifecycle. Moreover, it aims to improve efficacy within the architecture, engineering, construction and operations industry. Originality/value The study empowers organizations and decision-makers with a bespoke tool for evaluating BIM feasibility, contributing to decision-making through a clarified numerical representation., CC BY 4.0

The weldability of stainless steels is largely controlled by the chemical composition, and alloys with ferritic or ferritic-austenitic solidification show the highest resistance to hot cracking. As the resulting phase balance also affects the final properties, it may be beneficial to both foresee and measure the weld metal ferrite content. The WRC ‘92 constitution diagram is currently the most accurate prediction tool available, but it does not take the cooling rate into consideration and the precision may be less accurate for stainless steels with high ferrite numbers (FNs). This study aims to assess the reliability of the WRC ‘92 diagram for weld metals with FN > 50. The chemical composition was altered through gas tungsten arc welding (GTAW) of UNS S32205 with ER347 filler wire that had been coated using physical vapor deposition (PVD) with either niobium (Nb), copper (Cu), nickel (Ni), manganese (Mn), carbon (C), or silicon (Si). The actual ferrite content was evaluated using image analysis, FeriteScope and X-ray diffraction (XRD). While predictions from the WRC ‘92 diagram were deemed acceptable for Ni, Si, and Mn, notable deviations were observed for Nb, Cu, and C. The FeriteScope exhibited a consistent trend with image analysis, albeit with slightly higher FN values, wider scatter, and the conversion factor from FN to vol% is open for discussion. The lowest accuracy and largest spread were obtained using non-contact XRD, rendering it unsuitable for ferrite measurements of welds. These findings underscore the need for improved prediction tools and appropriate measurement methods for assessing ferrite content in duplex weld metals.

Surface tension is an important characteristic of materials. In particular at high temperatures, surface tension values are often unknown. However, for metals, these values are highly relevant in order to enable efficient industrial processing or simulation of material behavior. Plasma, electron or laser beam processes can induce such high energy inputs, which increase the metal temperatures to, and even above, boiling temperatures, e.g., during deep penetration welding or remote cutting. Unfortunately, both theoretical and experimental methods experience challenges in deriving surface tension values at high temperatures. Material models of metals have limitations in explaining complex ion interactions, and experimentally measuring temperature and surface tension at high temperatures is a challenge for methods and equipment. Therefore, surface wave analysis was conducted in this work to derive surface tension values around the boiling temperature of steel and identify trends. In addition, a simple ion interaction calculation was used to simulate the impacting parameters that define the surface tension. Since both the experimental values and simulation results indicate an increasing trend in surface tension above the boiling temperature, it is concluded that the dominating attractive forces above this temperature should increase with increasing temperature and lead to increasing surface tension forces in the surface layers of liquid metal., CC BY 4.0

Hot isostatic pressing (HIP) is a near-net shape powder metallurgy (PM) technique, which has emerged as an efficient technique, offering precise control over the microstructure and properties of materials, particularly in high-performance alloys. This technology finds applications across a wide range of industries, such as aerospace, automotive, marine, oil and gas, medical, and tooling. This paper provides an overview of powder metallurgy and hot isostatic pressing, covering their principles, process parameters, and applications. Additionally, it conducts an analysis of PM-HIPed alloys, focusing on their microstructure and fatigue behavior to illustrate their potential in diverse engineering applications. Specifically, this paper focuses on nickel-based superalloys and martensitic tool steels. The diverse microstructural characteristics of these alloys provide valuable insights into the PM-HIP-induced fatigue defects and properties.

This study investigates melt flow dynamics in asymmetric T-joint laser welding, particularly with sheets inclined up to 45°. This complex scenario requires filler wire, accessible only from the flat sheet side. High-speed imaging at the top and root captures transient phenomena leading to weld imperfections. Research on stainless-steel involved the impact of first-order welding parameters on the weld quality. This included multi-spot laser welding with two beams. The analysis focused on melt pool dynamics under these challenging conditions. The asymmetric root side’s geometry necessitates proper melt flow to form a favorable root topology, avoiding defects like wavy roots and porosity. Key observations included intermittent keyhole openings, transient melt flow effects, and potential spatter ejection at the bottom. The findings offer a comprehensive understanding of 3D asymmetric melt flow, laying the analytical groundwork for enhancing the weld quality., Full text license: CC BY-NC-ND 4.0;Funder: VINNOVA (2022-01591); Swedish Energy Agency (P2022-00150)

High-power laser interaction with a metal material can induce melting and even evaporation. However, the origin and content of vapor emissions based on temperature, material alloy elements, and other external conditions are not fully understood yet. Therefore, in this study, the content of laser-induced vapor was systematically examined during directed energy deposition processes. Single tracks of aluminum bronze were deposited with both continuous and periodically modulated laser powers. The duration and laser power of the modulations were set to achieve the same total line energy input. With the aid of those laser power modulations, controlled emissions were temporarily excited and observed. Optical emissions were captured with a spectrometer and a high-speed camera and related to the melt pool temperature signals and surface dynamics. The intensity of the emissions as well as the impact on the local chemical composition depend on the modulation parameters. Tracks deposited with short, high-power peaks in the modulation pattern showed chemical compositions comparable to those tracks that were continuously welded, whereby the intensity of spectral emissions was significantly increased. It can be concluded that the intensity of the measured spectral emissions correlates with the measured melt pool temperature signal and the dynamic movement of the vapor plume., The authors acknowledge the following funding: SMART—Surface tension of Metals Above vapoRization Temperature (Vetenskapsrådet—The Swedish Research Council, No. 2020-04250). DEDICATE—Directed Energy Deposition for Industrial Competitiveness in Additive Manufacturing Technologies (Swedish Knowledge Foundation, KK-Stiftelsen, Stiftelsen for kunskaps-och kompetensutveckling, No. Dnr.20210094).

Additive manufacturing of AlSi10Mg has obtained increased attention due to its lightweight feature. However, handling of loose powder, efficient usage of feedstock, and powder recycling still remain major open challenges. Herein, a novel additive manufacturing method based on metal additive manufacturing using powder sheet (MAPS) is proposed, which leverages composite flexible films made of the feedstock of metal powder and a polymeric binder, aiming to extend the range of applicability of AlSi10Mg-based additive manufacturing technologies, for example, vehicle components. In situ high-speed imaging is used to explore the underlying manufacturing mechanisms of the proposed MAPS concept and investigate the laser–powder sheet interaction. In addition, a representative computational thermo-mechanical model was used to evaluate the substrate deformation due to the printing process, a critical aspect that must be minimized in order to transfer this technology to larger scale applications., A correction has been published.

Accurate temperature estimation is crucial in metal additive manufacturing ensuring component quality and process efficiency. This study introduces the use of Convolutional Neural Networks (CNNs), namely MobileNet and ResNet, to predict temperatures directly from melt pool images without the need for extensive preprocessing. Through comparative analysis, MobileNet demonstrated superior performance over ResNet, achieving a mean absolute error of 0.0562 and a correlation coefficient of 0.9900. These findings underscore the effectiveness of CNNs in real-time temperature prediction tasks within Laser-Directed Energy Deposition with wire (DED-LB/w), highlighting significant advancements and setting the stage for further technological enhancements., This research was supported by the project TANDEM (2021-03145) Vinnova under the SMART EUREKA cluster on advance manufacturing program.

This study investigates the high-temperature wear behavior of laser-cladded (LC) cobalt-based Stellite 6 alloy coatings and compares the wear resistance of the cladding layer to the grey cast iron (GCI) substrate material at three different elevated temperatures: 150 °C, 250 °C, and 350 °C. Wear mechanisms at elevated temperatures were analyzed using SEM-EDS and Raman Spectroscopy to understand the material removal processes and degradation for the discs and counterpart composite friction material pins, respectively. The results indicated a significant improvement in wear resistance for cobalt-based alloy cladding at high temperatures. Wear rates were reduced by 5.0 %, 43.0 %, and 16.0 % at 150 °C, 250 °C, and 350 °C, respectively. The LC - brake pin tribo-pair exhibited a continuous increase in friction coefficients (CoF) with an increase in testing temperatures. The wear mechanism for laser-cladded discs exhibited a combination of abrasive and adhesive wear, with abrasive wear prevailing at 150 °C and increased adhesive wear at 250 °C and 350 °C. However, at 350 °C, decomposition of phenolic resin and the adhesive wear mechanism, led to brake pin failure. For GCI discs oxidative wear was identified as the predominant wear mechanism. The improved knowledge of wear mechanisms on LC Stellite 6 against composite brake pins, is set to enhance surface modification of GCI for brake disc applications. © 2024 Elsevier Ltd and Techna Group S.r.l.

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.

CC-BY 4.0

A high-alloy (Cr-Mo-V) cold-work tool steel was manufactured by laser powder-bed fusion (PBF-LB) without preheating and by electron-beam powder-bed fusion (PBF-EB) with the build temperature set at 850 degrees C. The solidification rates, cooling, and thermal cycles that the material was subjected to during manufacturing were different in the laser powder-bed fusion than electron-beam powder-bed fusion, which resulted in very different microstructures and properties. During the solidification of the PBF-LB steel, a cellular-dendritic structure was formed. The primary cell size was 0.28-0.32 mu m, corresponding to a solidification rate of 2.0-2.5 x 106 degrees C/s. No coarse primary carbides were observed in the microstructure. Further rapid cooling resulted in the formation of a martensitic microstructure with high amounts of retained austenite. The high-retained austenite explained the low hardness of 597 +/- 38 HV. Upon solidification of the PBF-EB tool steel, dendrites with well-developed secondary arms and a carbide network in the interdendritic space were formed. Secondary dendrite arm spacing was in the range of 1.49-3.10 mu m, which corresponds to solidification rates of 0.5-3.8 x 104 degrees C/s. Cooling after manufacturing resulted in the formation of a bainite needle-like microstructure within the dendrites with a final hardness of 701 +/- 17 HV. These findings provide a background for the selection of a manufacturing method and the development of the post-treatment of a steel to obtain a desirable final microstructure, which ensures that the final tool's performance is up to specification.

Funding agencies: The Swedish Government Strategic Research Area in Materials Science on Functional Materials at Linköping University (Faculty Grant SFO-Mat-LiU 2009-00971), Siemens Industrial Turbomachinery AB (Finspång, Sweden) and Stiftelsen Axel Hultgrens Fond (Stockholm, Sweden)

Pre-deposition substrate etching by metal ion bombardment is an efficient and fast cleaning method that ensures improved chemical and topological substrate surface modification. Here, we study the effects of metal ion mass and kinetic energy on etching of industrially-relevant cemented carbide (WC) substrate as well as on adhesion at the Ti0.50Al0.50N/WC interface. Cr+ or W+ ion fluxes are generated by high-power impulse magnetron sputtering (HiPIMS), while their kinetic energy E-kin is tuned by applying negative substrate bias voltage synchronously with the metal ion-rich portion of the flux. The time evolution of ion fluxes at the substrate plane is studied with energy- and time-resolved ion mass spectrometry. The threshold substrate bias voltage required to initiate substrate etching is in the 900-1000 V range for both Cr+ and W+ fluxes. Moreover, we show that the adhesion strength of Ti0.50Al0.50N coatings correlates with E-kin. For E-kin < 900 eV, Cr or W interlayers are grown and no significant improvement in the adhesion strength is observed. Contrary, for E-kin > 900 eV, effective substrate etching with energetic metal ions significantly improves the adhesion strength: we demonstrate an increase of 76-79 % after etching with metal ions as compared to the untreated substrate., Funding Agencies|Swedish Energy Agency [51201-1, P2023-00784]; Aforsk Foundation [22-4]; Knut and Alice Wallenberg Foundation Scholar Grant [KAW2019.0290]; Olle Enqvist foundation [222-0053]; Carl Tryggers Stiftelse [CTS 20:150]; Swedish Research Council; Swedish National Infrastructure in Advanced Electron Microscopy [2021-00171, RIF21-0026]; Polish National Agency for Academic Exchange [BPN/BEK/2021/1/00366/U/00001]; Warsaw University of Technology within the Excellence Initiative: IDUB Mobility program [CPR-IDUB/21/Z09/2024]

Funding: This study was performed within the framework of the competence center FunMat-II that is financially supported by Vinnova (grant no 2016–05156). The use of PETRA III was enabled through the Röntgen-Ångström Cluster frame grant (grant no VR 2017–06701). The Swedish government strategic research area grant AFM (SFO Mat LiU, grant no 2009–00971) and the Swedish Foundation for Strategic Research (grant no APR20–0029) are acknowledged for financial support.

Additive manufacturing encompasses technologies that produce three-dimensional computer-aided design (CAD) models through a layer-by-layer production process. Compared to traditional manufacturing methods, additive manufacturing technologies offer significant advantages in producing intricate components with minimal energy consumption, reduced raw material waste, and shortened production timelines. AM methods based on shielded gas welding have recently piqued the interest of researchers due to their high efficiency and cost-effectiveness in manufacturing critical components. However, one of the most formidable challenges in additive manufacturing methods based on shielded gas welding lies in the irregularity of weld bead height at different points, compromising the precision of components produced using these techniques. In this current research, we aimed to achieve uniform weld heights along the welding path by considering the most influential parameters on weld bead geometry and conducting experimental tests. Input parameters of the process, including nozzle angle, welding speed, wire speed, and voltage, were considered. Simultaneously, image processing and wavelet transform were employed to assess the uniformity of weld bead height. These parameters were applied to produce intricate parts after identifying optimal parameters that yielded the smoothest weld lines. According to the results, the appropriate bead for manufacturing the part was extracted. The results show that the smoothest bead line is achieved in 27 V as the highest level of voltage, at a 90° nozzle position and the maximum wire feed rate. Parts manufactured using this method across different layers exhibited no distortions, and the repeatability of production substantiated the high reliability of this approach for component manufacturing. © 2024 by the authors.

Additive manufacturing (AM) using powder bed fusion is becoming a mature technology that offers great possibilities and design freedom for manufacturing of near net shape components. However, for many gas turbine and aerospace applications, machining is still required, which motivates further research on the machinability and work piece integrity of additive-manufactured superalloys. In this work, turning tests have been performed on components made with both Powder Bed Fusion for Laser Beam (PBF-LB) and Electron Beam (PBF-EB) in as-built and heat-treated conditions. The two AM processes and the respective heat-treatments have generated different microstructural features that have a great impact on both the tool wear and the work piece surface integrity. The results show that the PBF-EB components have relatively lower geometrical accuracy, a rough surface topography, a coarse microstructure with hard precipitates and low residual stresses after printing. Turning of the PBF-EB material results in high cutting tool wear, which induces moderate tensile surface stresses that are balanced by deep compressive stresses and a superficial deformed surface that is greater for the heat-treated material. In comparison, the PBF-LB components have a higher geometrical accuracy, a relatively smooth topography and a fine microstructure, but with high tensile stresses after printing. Machining of PBF-LB material resulted in higher tool wear for the heat-treated material, increase of 49%, and significantly higher tensile surface stresses followed by shallower compressive stresses below the surface compared to the PBF-EB materials, but with no superficially deformed surface. It is further observed an 87% higher tool wear for PBF-EB in as-built condition and 43% in the heat-treated condition compared to the PBF-LB material. These results show that the selection of cutting tools and cutting settings are critical, which requires the development of suitable machining parameters that are

Three FeCrAl alloys (APMT, EF100 and EF101) from Kanthal® and the reference Ni‐Cr Alloy 625 were used as weld cladding materials on tube shields in the evaporator tube bank of a waste‐fired combined heat and power plant. For each alloy type, the overlay welded tube shields were placed in both roof and floor positions within the evaporator for 6 months. The metal‐loss rate, the microstructure and hardness of the overlay welds before and after exposure and the corrosion products were analysed. The results showed higher metal‐loss rates in the welds placed in the roof position, confirming heterogeneities in the evaporator bank environment. Alloys were ranked from higher to lower erosion–corrosion resistance as follows: APMT≈Alloy 625 > EF101 > EF100. The analysis of the corrosion attacks showed a significant variation among the alloys, from a primarily homogeneous corrosion attack on APMT tointergranular corrosion in EF100 and pit formation in EF101., CC BY

In this study, the DED-LB/M process of AISI H11 tool steel powder blends modified by adding WC nanoparticles (WC-np) in concentrations of 1, 2.5 and 5 wt.-% was the object of scientific investigations. For this, 30-layer cuboid specimens were manufactured. The overall scientific aim was to examine how the WC-np interact with the steel melt and in the end, influence the processability, microstructure and mechanical properties of produced specimens. The examinations were carried out on both as-built and thermally post-processed specimens. An advanced microstructural analysis (SEM, EDS, EBSD and XRD) revealed that due to the high solubility of WC-np in the molten steel, most of the WC-np appear to have dissolved during the ongoing laser process. Furthermore, the WC-np favor a stronger distortion and finer grain size of martensite in the manufactured specimens. An increase in hardness from about 650 HV1 for the H11 specimen to 780 HV1 for the one manufactured using the powder blend containing 5 wt.-% of WC-np was observed in as-built conditions. In the same way, the compression yield strength enhanced from 1839 MPA to 2188 MPA. The hardness and strength increasing effect of WC-np remained unchanged even after heat treatments similar to those used in industry.

The development of new high temperature materials for coatings as well as structural components is an important topic to contribute to a higher efficiency and sustainability of e.g. gas turbine engines. One promising new class of high temperature materials are NiAl-based alloys. Within this study, the microstructure and microhardness of NiAl-Ta-Cr alloys with varying Cr and Ta content were investigated. Graded specimens were fabricated by laser-based directed energy deposition utilizing an in situ alloying approach by mixing elemental Ta and Cr as well as pre-alloyed NiAl powder. Thermodynamic calculations were performed to design the alloy compositions beforehand. Inductive preheating of the substrate was used to counter the challenge of cracking due to the high brittleness. The results show that the cracking decreases with increasing preheating temperature. However, even at 700 °C, the cracking cannot be fully eliminated. Scanning electron microscopy, X-ray diffraction and electron backscatter diffraction revealed the formation of the phases B2-NiAl, A2-Cr and C14-NiAlTa within NiAl-Ta and NiAl-Cr alloys. For NiAl-Ta-Cr compositions, deviations regarding the phase formation between calculation and experiment were observed. Maximum hardness values were achieved within the NiAl-Ta and NiAl-Ta-Cr systems for the eutectic compositions at 14 at.-% Ta with maximum values above 900 HV0.1., Validerad;2024;Nivå 2;2024-04-02 (joosat);Funder: German Research Foundation (Deutsche Forschungsgemeinschaft, DFG), (457729030);Full text license: CC BY-NC-ND

In machining, the heat generated during the process deforms the components and the final shape might not meet specified tolerances. There is therefore a need for a compensation strategy which requires knowledge of the workpiece temperature field and the associated thermal distortions. In this work, a methodology is presented for the determination of the heat load for indexable insert drilling of AISI 4140. Compared to previous research, this work has introduced a varying heat load. The heat load is extracted from thermo-mechanical finite element simulations for different nominal chip thicknesses and cutting speeds using the coupled Eulerian-Lagrangian formulation of an orthogonal turning process. The heat load is then transferred to a simplified 2D axisymmetric heat transfer model where the in-process temperature field in the workpiece is predicted. To verify the methodology, the predicted temperatures are compared to the experimentally measured temperatures for various feed rates. It is found that the model is capable of predicting the workpiece temperatures reasonably well. However, the methodology needs to be further explored to validate its applicability., CC BY 4.0 DEEDPublished: 02 March 2024The authors would like to acknowledge the Swedish Knowledge Foundation for funding of the CoSim project (Dnr:20160298). We also want to thank Powertrain Engineering Sweden AB and Automotive Components Floby AB for their support and collaboration during the project.Open access funding provided by University of Skövde. The research leading to these results received funding from the Swedish Knowledge Foundation under Grant Agreement No 20160298., CoSim

Static form errors due to in-process deflections is a major concern in flank milling of thin-walled parts. To increase both productivity and part geometric accuracy, there is a need to predict and control these form errors. In this work, a modelling framework for prediction of the cutting force-induced form errors, or thickness errors, during flank milling of a thin-walled workpiece is proposed. The modelled workpiece geometry is continuously updated to account for material removal and the reduced stiffness matrix is calculated for nodes in the engagement zone. The proposed modelling framework is able to predict the resulting thickness errors for a thin-walled plate which is cut on both sides. Several cutting strategies and cut patterns using constant z-level finishing are studied. The modelling framework is used to investigate the effect of different cut patterns, machining allowance, cutting tools and cutting parameters on the resulting thickness errors. The framework is experimentally validated for various cutting sequences and cutting parameters. The predicted thickness errors closely correspond to the experimental results. It is shown from numerical evaluations that the selection of an appropriate cut pattern is crucial in order to reduce the thickness error. Furthermore, it is shown that an increased machining allowance gives a decreased thickness error for thin-walled plates., CC BY 4.0 DEEDSchool of Engineering Science, University of Skövde, Kaplansgatan 11, SE‑541 34 Skövde, Sweden. *email: daniel.svensson@his.seOpen access funding provided by University of Skövde. This work was supported financially by the Swedish Knowledge Foundation through the project SIMPLE (dnr: 20180168).

Ultrasonic wire welding is considered a method of choice for creating reliable interconnects in electronics industry including aerospace, batteries and electric vehicles. In this paper, ultrasonic welding tests between EVR252 copper wire and substrate are carried out. Novel pattern morphologies are machined on substrates to explore its influence on mechanical properties of welded joint. Patterns are divided into three different categories e.g., original surface, vertical and horizontal shapes. Cracks, microstructure strength and tensile properties of welded joint are studied and its joining mechanism is analysed. Compared with the reference substrate (S1), the welded joint performance of the longitudinal patterns (S2, S3, S4) has been improved, among which the longitudinal pattern (S4) has the most significant improvement (+ 15%). Likewise, the performance of transverse pattern (S5) welded joints is relatively poor (− 16%). The microstructural analysis using SEM has revealed predominant joint strength on Cu wire surface while maintaining rock-like and compact properties of S4 substrate. Upper side of wire-harness compactness is frequently observed due to vertical direction of patterns on substrate and also increases the strength of welded joint. Values of failure load, failure displacement and failure energy absorption were increased by 7.9%, 72% and 35% for S2, 6.1%, 75% and 42% for S3 and 15%, 87% and 113% for S4 compared to S1. Failure modes of welded joints are mainly characterized into: 1-poor ductility or rupture (no deformation) failure in vertical 3-line pattern joints 2-cylindrical deep holes failure in vertical 3-line zigzag pattern joints and 3-bulging effect failure in horizontal 3-line zigzag pattern joints. Point and line scans EDS measurement were performed to investigate weaker and stable trends of different locations in welded joints. In S4 substrate, 17.9% carbon content at the position of welded joint was investigated, leading to content of less o

Purpose – Perceived benefits of building information modelling (BIM) have been discussed for some time, but cost–benefit benchmarking has been inconsistent. The purpose of this paper is to investigate BIM feasibility and evaluate investment worth to elucidate and develop the current understanding of BIM merit. The aim of the study is to propose a research agenda towards a more holistic perspective of BIM use incorporating quantifying investment return. Design/methodology/approach – An in-depth examination of research patterns has been conducted to identify challenges in the assessment of the investment value and return on investment (ROI) for BIM in the construction industry. A total of 75 research articles were considered for the final literature review. An evaluation of the literature is conducted using a combination of bibliometric analysis and systematic reviews. Findings – This study, which analysed 75 articles, unveils key findings in quantifying BIM benefits, primarily through ROI calculation. Two major research gaps are identified: the absence of a standardized BIM ROI method and insufficient exploration of intangible benefits. Research focus varies across phases, emphasizing design and construction integration and exploring post-construction phases. The study categorizes quantifiable factors, including productivity, changes and rework reduction, requests for information reduction, schedule efficiency, safety, environmental sustainability and operations and facility management. These findings offer vital insights for researchers and practitioners, enhancing understanding of ’BIM’s financial benefits and signalling areas for further exploration in construction. Originality/value – The ’study’s outcomes offer the latest insights for researchers and practitioners to create effective approaches for quantifying ’BIM’s financial benefits. Additionally, the proposed research agenda aims to improve the current limited understanding of BIM feasibility and investment, CC BY 4.0

In present study, a wall structure of SS309L was constructed through Gas metal arc welding based Wire-arc additive manufacturing process. The wall structure of SS309L underwent investigation for microstructure and mechanical properties at three positions along the horizontal deposition direction. Mechanical assessments, including microhardness testing, impact testing, tensile testing, and fractography, were conducted at three positions of walls. Microstructure study has shown a fine granular structure in addition to colony of columnar dendrites in bottom section, a columnar dendrites in middle section, and a mix of dendritic structure with even coarser structures in top section. The mean microhardness values were observed to be 159 ± 4.21 HV, 162 ± 3.89 HV, and 168 ± 5.34 HV for the top, middle, and bottom sections, respectively. Results of impact testing for the wall structure indicated greater strength compared to wrought SS309L. The tensile strength of the built structure showed average values of yield strength, ultimate tensile strength, and elongation to be 409.33 ± 7.66 MPa, 556.66 ± 6.33 MPa, and 39.66 ± 2.33 %, respectively. In comparison, wrought 309 L steel typically exhibits tensile strengths in the range of 360–480 MPa for yield strength, 530–650 MPa for ultimate tensile strength, and 35–45 % elongation. Thus, the obtained tensile strength results for the wall structure fall within the range of tensile strength observed in wrought 309 L steel. Fractography of the tensile and impact specimens, as obtained through Scanning Electron Microscopy, revealed the superior ductility of the fabricated component. This study contributes valuable insights into the manufacturing of wall structure and their analysis regarding mechanical characteristics., CC-BY 4.0