bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the influence of the initial surface integrity on the result of burnished high torque splined shafts
Authors: DAMM P.
Published: April 2024

Abstract. The increasing demand for low surface roughness and long service life in highly loaded components, such as extruder shafts, requires high strength, functional reliability and long-term durability. Extruder shafts are applied in plastics technology and in the food industry for processing plastic melts, mixing and compounding. Screw and kneading elements are required for this purpose. The screw and kneading elements are pushed form-fittingly onto a splined shaft. The torque is transmitted by the splined shaft. [1] Main causes of wear and damage of extruder shafts are corrosion and mechanical load. High surface qualities, increased residual compressive stresses and increased surface hardness are possibilities to increase the durability of the splined shafts. These desired properties can be achieved by applying the ball burnishing technology. [2] By utilizing cold working processes, such as ball burnishing, it is possible to enhance the surface and subsurface properties to increase the lifespan of rotary components intended for transmitting high rotational torques. Due to the importance of considering the roughness of the initial surface, this study aimed to generate various roughness and surface profiles through the turning process to investigate their influence on the burnishing process results. For this purpose, shaft sections made of AISI H11 steel were pre-machined with different cutting inserts in order to set different surface roughnesses. Subsequently, a statistical experimental design was created by using the Taguchi method by varying feed rate, pressure and speed. As a main result, roughness and residual stresses on the surface were measured and compared with the initial conditions.
Digital image processing algorithm for industrial on-site roughness evaluation in Ti-alloy machining
Authors: RIBEIRO CARVALHO Sílvia Daniela
Published: April 2024

Abstract. The surface texture is normally observed after the machining process, but nowadays it is important to use on-site analysis to improve the process automatically via smart processing. This study introduces a contactless roughness inspection method employing digital image processing on Ti6Al4V samples in turning using three different feed. Texture analysis with grey-level co-occurrence matrix (GLCM) extracted features that were correlated with the arithmetic average roughness (Ra), leading to the establishment of predictive models. The study encompassed diverse image testing, incorporating variations in resolution and brightness distributions. It was found that the pixel pair spacing (PPS) in GLCM analysis was influenced by the image resolution and feed rate. The predictive models developed with high-quality images, i.e., higher resolution and better brightness distribution, yielded similar results to those created using lower-quality images.
Artificial Intelligence techniques and Internet of things sensors for tool condition monitoring in milling: A review
Authors: FERRISI Stefania
Published: April 2024

Abstract. Milling is a machining process that involves removing material from a workpiece using a rotating cutting tool. During the milling process, the cutter is affected by a progressive degradation due to the grinding of the workpiece which results in a decline in product quality and a sharp increase in energy consumption and production costs. For these reasons, Tool Condition Monitoring has emerged as the essential approach in the machining industry. The application of Artificial Intelligence (AI) systems that incorporate the use of various Internet of Things sensors (IoT) to support the tool condition monitoring in the milling process has recently been a subject of great interest to researchers. It helps to achieve goals required in the modern manufacturing industries in terms of sustainability, cost reduction, and quality improvement. This review article focuses on the application of IoT sensors for recording acoustic emissions, to conduct tool condition monitoring of the milling cutting tools based on AI techniques. The discussion includes an analysis of the principal sensory systems and their main advantages and disadvantages for the milling process. Moreover, trends and problems of applied AI techniques for tool condition monitoring are highlighted.
Surface characteristics comparison between additively manufactured Ti6Al4V and wrought Ti6Al4V turned samples
Authors: Saffioti M.S.
Published: April 2024

Abstract. This paper aims to contribute increasing the knowledge surrounding Ti6Al4V by making a comprehensive comparative analysis of surface characteristics between additively manufactured and conventionally wrought Ti6Al4V turned samples. The tests were carried out by varying the process parameters such as cutting speed and lubricant conditions (dry and cryogenic), and by keeping fixed the feed rate and the depth of cut. The comparison of these two manufacturing methods allows to explore how the different surface properties, such as roughness, microstructure and hardness, can change.
Impact of heat treatment cycles on work hardening characteristics in selective laser melted Ti6Al4V ELI alloy
Authors: SUKRE Mahendra
Published: April 2024

Abstract. The present study investigates the influence of heat treatment cycles on the work hardening behaviour of a selective laser-melted (SLM) Ti6Al4V ELI alloy. To modify the microstructure and assess its impact on work hardening behaviour, the SLM Ti6Al4V ELI alloy is subjected to a series of heat treatment cycles, including solution treatment, quenching, and ageing. The microstructural evolution is characterized using scanning electron microscopy (SEM) and X-ray diffraction (XRD). Tensile tests are conducted to investigate the work hardening behaviour, including yield strength, ultimate tensile strength, and strain hardening. The findings show that heat treatment cycles have a significant impact on the microstructure and work hardening behavior of the SLM Ti6Al4V ELI alloy. Solution treatment and quenching produce a refined α' martensitic structure by homogenizing the microstructure and dissolving the secondary phases. Subsequent ageing treatments induce the precipitation of secondary phases, such as α and β phases, within the α' martensite matrix.
The effect of cryogenic assistance on the machinability of Ti54M and energetic approach
Authors: EL HATIMI Imane
Published: April 2024

Abstract. Titanium alloys are increasingly being used in various applications due to their excellent mechanical properties and corrosion resistance. However, their machinability can be challenging due to their high strength and low thermal conductivity. Cryogenic assistance is a promising technique that can be used to improve the machinability of titanium alloys by reducing the cutting forces and improving the tool life. This study investigates the effect of cryogenic assistance on the machining of Ti54M, a high-strength titanium alloy. The results show that cryogenic assistance can significantly reduce the cutting forces and improve the tool life. However, the benefits of cryogenic assistance are limited at high cutting speeds. The study also provides insights into the mechanisms by which cryogenic assistance improves machinability.
A new view on the solution of rate-independent crystal plasticity finite element models
Authors: NIJHUIS Björn
Published: April 2024

Abstract. The crystal plasticity finite element method (CP-FEM) readily enables microstructure-based material modelling by relating macroscopic plastic deformation to dislocation slip on crystal slip systems. Rate-independent CP models provide physically accurate solutions by allowing slip only if the resolved shear stress on a slip system equals the critical resolved shear stress. However, computing the amount of slip for such models remains challenging. This work proposes a novel stable and efficient stress-update algorithm based on fixed-point iterations. These iterations trace the hypersurfaces that describe the slip state for which individual slip system’s yield functions are zero, until all slip system hypersurfaces intersect. This simultaneously provides the set of active slip systems and the slip on these systems, avoiding the need for an iterative active set search algorithm without inducing spurious slip on systems on which the shear stress is below the critical resolved shear stress.
Fatigue life analysis of hot forming dies produced by the L-PBF and WA-DED additive technologies
Authors: ALIMOV Artem
Published: April 2024

Abstract. Additive manufacturing (AM) technologies are widely used for the production of individual complex precise parts and small-scale production. AM has been used in many applications for the manufacturing of sheet metal forming dies. The production of hot bulk forming dies by additive manufacturing technology has not been extensively studied in the literature. Traditional hot working steels exhibit many problems during the AM process, such as crack formation due to complex thermal processing cycles. Maraging/precipitation-hardened (PH) steels may be a good alternative because of their ability to undergo additive manufacturing. One of the main causes of hot forming die failures is thermomechanical fatigue. The fatigue performance of 17-4PH was investigated primarily during high-cycle fatigue (HCF) and low-cycle fatigue (LCF) modes without heat treatment as well as with H1100 heat treatment. The LCF of dies with the heat treatment designation H900, which is most appropriate for die production, has not been intensively investigated. In this work, the mechanical properties and fatigue life of 17-4PH precipitation-hardened steel produced by laser powder bed fusion (L-PBF) and wire arc direct energy deposition (WA-DED) additive technologies were experimentally investigated, and numerical models for high-temperature low cycle fatigue life were developed for 17-4PH steel. Based on the FEM simulation in the commercial program QForm UK, the fatigue life of the produced dies was predicted.
Modelling ductile fracture in an Al alloy with crystal plasticity models
Authors: KHADYKO Mikhail
Published: April 2024

Abstract. Crystal plasticity models enhanced with coupled or uncoupled damage and fracture criteria give an opportunity to account for the role of microstructure in ductile fracture, most directly representing the local variations of stress and strain fields inside and between the grains, voids and particles. Some computationally efficient crystal plasticity, damage and fracture models have recently been developed and applied to some cases of polycrystalline fracture. Such models allow to investigate in a direct way the effects of, e.g., shear bands, larger voids, particles, free surfaces and load direction on the development of damage and fracture. The cast and homogenized Al1.2Mn alloy investigated previously is used here as a basis for simulations. The alloy has an equiaxed grain structure with no texture and contains a population of larger particles and a population of dispersoids. The grain structure and the large particles are modelled directly in the finite element model, while the effect of dispersoids is represented by the damage and fracture part of the single crystal plasticity model. The study investigates the effect of different model parameters and features on the global and local behaviour of the material during localization and fracture, in light of available experimental data.
High strain rate investigation on the mechanical anisotropy induced by SLM technology on a 3D printed steel
Authors: MANCINI E.
Published: April 2024

Abstract. Selective Laser Melting (SLM) technology is an additive manufacturing (AM) technique that involves selective or localized melting of metallic powder bed by a high-intensity laser beam source. This technology is responsible for an induced anisotropy in the printed components: in fact, depending on the orientation of the part within the powder bed, different mechanical properties are usually obtained. It is also known that mechanical properties may depend on the rate of load application. This work studies the mechanical anisotropy induced by SLM technology on a 16MnCr5 case hardening steel subjected to high strain rate loading. A direct Split Hopkinson Bar was employed for testing. The Cowper-Symonds model was used to describe the material behavior at high strain rates for samples loaded in the building and in the normal to building directions.
Comparative study of artificial neural network and physics-informed neural network application in sheet metal forming
Authors: MUNZONE Francesco
Published: April 2024

Abstract. Accurate prediction of the resultant geometry in sheet metal forming simulation is necessary to achieve zero-defect production. To quantify the effect of process parameters on the final geometry, numerical methods are used to simulate the process outputs for a given set of process variables. Finite element methods are employed in process optimization and design exploration. However, these computationally expensive models are unhelpful for process control applications. Surrogate models allowing fast prediction of resultant geometry or stress distribution can be plausible solutions. In the current study, we propose a sequential surrogate model to fit the stress field as a function of the process variable and the initial spatial coordinates. The framework is composed of two surrogate models. First, an artificial neural network (ANN) evaluates the displacement and the strain. Then, a second surrogate is employed to fit the stress using input strain and displacement. Here, ANN and physics-informed neural networks (PINN) are compared concerning prediction accuracy for the second surrogate model. The PINN is enhanced with the equilibrium equations. The developed method is demonstrated using a v-bending process. The results show that both surrogate models return good approximations, with ANN showing slightly better results.
Novel approach for data-driven modelling of multi-stage straightening and bending processes
Authors: PETERS Henning
Published: April 2024

Abstract. In multi-stage bending and straightening operations cross-stage and quantity-dependent effects crucially affect the quality of the end product. Using punch-bending units in combination with a mechatronic straightening device can improve the accuracy and repeatability of product features remarkably well. In this work a concept for an innovative hybrid model of a roll straightener in a multi-stage straightening and multi-stage bending process is proposed. This model combines data-driven elements with expert knowledge and aims to minimise residual errors of the roll straightener to reliably decrease the risk of disadvantageous cross-stage and quantity-dependent effects on a subsequent punch-bending process.
Fast prediction of the material displacement in open die forging using neural networks
Authors: JAGTAP Nikhil Vijay
Published: April 2024

Abstract. This paper presents a data-driven approach to predict the material displacement in open die forging using neural networks. Training data for different process parameters and workpiece geometries is generated using finite element simulations. A neural network architecture is designed that takes the process parameters and the coordinates of a point in the geometry as inputs and outputs the displacement of that point after the deformation. This is systematically implemented for open die forging, using relevant process information. The neural network model is trained and tested on various FEA-simulations for different process parameters and shows good accuracy and generalization. The model is also able to simulate multiple strokes of a single pass in a fast and efficient way. It is demonstrated how the neural network model can enable building a digital material shadow of open die forging processes. The advantages and limitations of the approach are then further discussed.
Enhancing metal-forming predictions with VR-infused digital twin models
Authors: URIBE David
Published: April 2024

Abstract. This article presents a two-step method to enhance metal-forming predictions by integrating Virtual Reality (VR) into Digital Twin models, focusing on single-blow cold copper upsetting operations. The process begins with developing a real-time predictive surrogate model that considers actual process parameters, acting as a crucial link between conventional numerical simulations and immediate decision-making. Subsequently, the surrogate model is integrated into a realistic VR environment, aligned with the experimental forging setup. The study underscores the need and potential advantages of real-time digital twins in the forging field, emphasizing the bridging capability between numerical simulations and instant decision-making through predictive modeling and immersive virtual environments.
Effectiveness of machining equipment user guides: A comparative study of augmented reality and traditional media
Authors: GHOBRIAL Mina
Published: April 2024

Abstract. In the rapidly evolving landscape of manufacturing and material forming, innovative strategies are imperative for maintaining a competitive edge. Augmented Reality (AR) has emerged as a groundbreaking technology, offering new dimensions in how information is displayed and interacted with. It holds particular promise in the panel of instructional guides for complex machinery, potentially enhance traditional methods of knowledge transfer and operator training. Material forming, a key discipline within mechanical engineering, requires high-precision and skill, making it an ideal candidate for the integration of advanced instructional technologies like AR. This study aims to explore the efficiency of three distinct types of user manuals—video, paper, and augmented reality (AR)—on performance and acceptability in a material forming workshop environment. The focus will be on how AR can be specifically applied to improve task execution and understanding in material forming operations. Participants are mechanical engineering students specializing in material forming. They will engage in a series of standardized tasks related to machining processes. Performance will be gauged by metrics like task completion time and error rates, while task load will be assessed via the NASA Task Load Index (NASA-TLX) [1]. Acceptability of each manual type will be evaluated using the System Usability Scale (SUS) [2]. By comparing these various instructional formats, this research seeks to shed light on the most effective mediums for enhancing both operator performance and experience.
Experimental derivation of process input parameters for electrochemical precision machining of a powder metallurgical tool steel
Authors: PETERMANN Richard
Published: April 2024

Abstract. Powder metallurgical steels are used for tools because of their properties, such as toughness, wear resistance and hardness. During the machining of the tool, the material is hardened. Consequently, the subsequent finishing of the tool is a challenge, as conventional manufacturing processes reach their limit of machinability due to the hardness. An alternative manufacturing technology is electrochemical precision machining (PECM). The PECM process, which is based on anodic metal dissolution, can be applied to machine metallic materials without force, cracks or burrs, regardless of their hardness [1]. Due to the process principle, the mechanical properties of the workpiece are not changed. As a result, the PECM process is suitable for finish machining of tools and finishing of tools. A significant challenge for PECM is the material-specific removal functions [2]. In this paper, the material removal functions of the hardened powder metallurgical steel S390 [3] are analyzed using experimental tests and the achievable surface quality is shown. Subsequently, process input parameters for electrochemical precision machining of S390 are derived.
Simulation-based analysis of electrical current induction in a device for electrochemical precision machining of Nd Fe B permanent magnets
Authors: THIELECKE A.
Published: April 2024

Abstract. Sintered permanent magnets, consisting of the neodymium-iron-boron (Nd-Fe-B) alloy, are installed as rotor magnets in small and precision electric drives due to their high magnetic forces in small volumes. When permanent magnets are brought into their final shape by electrical discharge machining (EDM), the thermal influence of this manufacturing process has negative effects on the magnetic properties of the workpieces. In consequence, re-magnetization of the workpieces is necessary after the finishing process. As an alternative manufacturing technology, electrochemical precision machining with an oscillating electrode and pulsed direct current (PECM) has the potential to eliminate this subsequent processing step. Based on Faraday's law of induction, an electrical induction current is expected to be generated by the cathode oscillation during the manufacturing process. In this study, the effect of the magnetic field of the workpiece on the process current and on the ablation-effective local electrical current density of the PECM process is analyzed based on multiphysics simulation.
Manufacturing of a shape memory polymer composite actuator with embedded heater
Authors: IORIO L.
Published: April 2024

Abstract. A new architecture of shape memory polymer composite (SMPC) sandwich actuator was developed. High-performance carbon fibre reinforced (CFR) prepreg was used for the external skins, whereas the shape memory functionalities were given by embedding square tablets of epoxy foams in the centre of the actuator. The epoxy foams were obtained by a solid-state process without using a foaming agent. Thermal activation of the smart actuator was induced through a flexible heater embedded during the lamination sequence. Finally, thin layers of the same shape memory (SM) resin used for the foams were deposited at the interface with the constituents. A SMPC actuator in the form of a 2-ply laminate with an embedded heater and with shape memory polymer (SMP) interlayer was also manufactured for comparison. The actuators were manufactured by a single-step hot press moulding process. Optical observations were carried out to evaluate the soundness of the adopted lab-scale manufacturing procedure, whereas shape memory, constrained-recovery and free recovery tests were performed to investigate the shape memory capabilities and the recovery loads of the novel smart device. Comparable actuation loads (1.5N on average) were found for the two SMPC actuators while shape fixity and shape recovery ratios higher than 81% and 99% respectively were measured for the sandwich actuator.
Nano-texturing orientation effect on the piercing behavior of five stacked amorphous electrical steel sheets
Authors: SHIRATORI Tomomi
Published: April 2024

Abstract. Higher efficiency motor becomes an expecting keyword in the sustainable society. The iron core in these motors is fabricated by piercing the amorphous electrical steel sheet with sufficient dimensional accuracy and without defects. However, this material has 2.2 GPa in the tensile strength, no ductility, and over 900 HV in hardness. Furthermore, tool life was limited to be short. In recent years, some new tooling technologies for piercing amorphous electrical steel sheets have been developed to reduce the induced damages into punched sheets．Especially, when using nano-textured tool, the process affected width was more reduced than using the none-textured tools. In the present study, nano-texturing orientation effect on the piercing behavior is investigated and its mechanism is discussed.
Improving room temperature formability of twin-roll cast Mg-Al-Zn-Sn alloy by repeated bending
Authors: TOZUKA Hotaka
Published: April 2024

Abstract. A twin-roll cast Mg-9mass%Al-1 mass%Zn-2mass%Sn alloy was used for the purpose of fabricating for wrought magnesium alloy which can be bent in the room temperature. An appropriate solution annealing time was found in order to reduce beta phase precipitation, which may cause cracking without coarsening of crystal grain size while for improving cold formability of twin-roll cast Mg-9mass%Al-1 mass%Zn-2 mass%Sn alloy. After solution heat treatment of the twin-roll casting of the material, repeated bending by three rolls of the solution heat treated strip was performed in order to examine of bendability of the materials. It has been clarified that repeatedly bending and reverse bending after solution heat treatment were effective for improving formability of the Mg-9mass%Al-1 mass%Zn-2 mass% Sn alloy at room temperature.
The influence of signal type and distance to the sound source on sound transmission through small 3D printed polymer panels
Authors: HRIȚUC A.
Published: April 2024

Abstract. The sound insulation of some spaces is possible using panels made of polymer materials manufactured by 3D printing. It is expected that the intensity of the sound signal after passing through a small wall made of polymeric material will be affected by the type of sound signal and the distance at which the sound is received. In the case of previous experimental research, the influence exerted by some parameters of the 3D printing process on the sound insulation capacity of walls made of polymeric materials was largely considered. In the case of the present paper, experimental research was carried out aiming to identify empirical mathematical models capable of highlighting the influence of the sound type and distance on the intensity of the sound signal after passing through the panel. The experimental tests were carried out on equipment designed to investigate different factors' influence on the sound signal's impact when passing through small panels. An empirical mathematical model was identified through the mathematical processing of the experimental results. The empirical mathematical model highlights the influence exerted by the shape of the electrical signal used to generate the sounds and, respectively, the distance between the sound source and the sensor of a sound level meter on the energy absorbed by the small panel from a polymeric material.
Optimization of the temperature profile of PET preform via a 3D modelling of the Infrared Heating and ventilation
Authors: LUO Yun-Mei
Published: April 2024

Abstract. Thermal effect has important influence during the stretch blow moulding (SBM) process of PET bottle. Setting the heating condition in an industrial context is a complex task. A 3D simplified modelling of the heating stage during this process is proposed. In this numerical approach, the radiation source is simulated by using a model for intensity of the incident radiation and the Beer Lambert’s law. On the other hand, the ventilation effect under industrial condition is taken into account by a modelling of the forced convection around a cylinder. The IR flux and ventilation effects are implemented as thermal boundary conditions in COMSOL for a 3D computation of the thermal problem for the preform only. Based on this simplified approach to achieve quickly the numerical simulation of the preform heating, an optimization procedure is proposed to adjust the settings of the infrared lamps by comparing our simulation results to the target temperature profile. This optimization tool provides quickly a first set of parameters to help industrial to obtain the desired temperature profile.
Recycling of thermoplastic materials: Development of a self-adaptive process to the recycled materials
Authors: FARAH Elena
Published: April 2024

Abstract. Over the last few decades, thermoplastic polymers have become increasingly popular and widely used materials in our lives. However, these mass consumptions remain difficult to reuse. Although mechanical recycling is being seriously proposed as an alternative solution [1], until now many obstacles prevent its application to polymers. Undetermined initial properties and aging conditions of post-consumer waste, which are, in fact, extremely variable, result in an ignorance of the aged material rheological properties before their reprocessing. As a consequence, the adjustment of extrusion parameters becomes very difficult and can vary over time and between supply batches. In this context, the project RECYPLAST-DEMO was proposed aiming at developing a prototype able to characterize, in real-time [2], the rheological properties of extruded waste materials and self-adjust the operating parameters of the machine, with the help of artificial intelligence, to maintain products of required quality. Our work concerns inline rheological characterization of materials using an instrumented die numerically tested with the software POLYFLOW® for the viscosity range of a PP, designed and experimentally validated in a later step of the project. The goal is to obtain the rheological behavior of the material from pressure difference measurements along the length of the developed die and assess data compared to rheological characterization measurements performed in laboratory on virgin material and aged ones. This paper highlights the effect of the processing temperature and the residence time on the aging of the polymer. Moreover, the numerical work of the developed extrusion die is presented and explained.
Rheological behavior of nanofillers enclosed multilayer systems under elongational flows: From microlayers to nanolayers
Authors: LI Jixiang
Published: April 2024

Abstract. The present work dedicated in the elongational behavior of multilayer polymer nanocomposites. CNTs were enclosed in a polypropylene with linear chain structure (PPC) and then co-extruded with another polypropylene (PPH) with long chain branching (LCB). By forced assembly, multilayer films with layer thickness from micro to nano were fabricated and the elongational rheology test was then conducted with the extension vertical to the film extrusion direction. Due to the LCB inside PPH, all multilayer films showed obvious strain hardening behavior despite linear PPC is a strain softening polymer. When the layer numbers were fewer, namely, the layer thickness was higher than the length of the CNTs, the strain hardening behavior of nanocomposite films was close to the multilayer system with neat polymers. With the layer numbers increasing, the layer thickness became lower than the length of the CNTs and the strain hardening behavior of nanocomposite films increased dramatically compared to the multilayer system with neat polymers. The reason for this kind behavior was because of the better orientation of CNTs via layer confinement when layer numbers increased, which thus making the strain hardening more significant.
Monitoring the temperature during thermoplastic composites assembling with fibre Bragg gratings: Validation using a rheometer
Authors: KORYCKI Adrian
Published: April 2024

Abstract. For many years, thermoplastic composites have been conquering the technological market in commercial applications in civil and military structures, with particular emphasis on aircraft. One of their most attractive advantages is the potential to be repaired and welded in a short time. However, due to the lack of knowledge on the impact of process parameters (time, pressure, temperature) bonding thermoplastic composites remains a challenge. The combined action of force and temperature leads to intimate contact between the substrates, which is the prerequisite for macromolecular interdiffusion and welding. A polymer film named Energy Director (ED) can be set up at the interface between substrates to enable the process and to ensure the strength of the joint. This leads to the need for a temperature measurement technique to better understand the physics responsible for the best bonding parameters. The use of Fibre Bragg Grating (FBG) seems to be suitable for obtaining real-time temperature data during the joining. The present work is challenging this technique by means of a rheometer as a device for results validation. The considered bonded materials are carbon fibre-reinforced polyetheretherketone (CF/PEEK) and polyetherimide (PEI). The integration of PEI film on top of the CF/PEEK composite parts is studied. The FBG sensors respond to both temperature and longitudinal strain. Then two kinds of measurements are examined under the rheometer: the first response of the fibre as a function of temperature in static mode during processing and the second one as a function of torque loading. Wavelength shifts and spectral form changes induced by the contraction of the composite during cooling were observed. The use of a rheometer is suitable for the simulation of CF/PEEK composites joining processes such as welding. FBG method has a higher potential for temperature measurement than incorporated thermocouples (TC) as studied during ultrasonic (US) welding [1]. Its advantage is the possibility to allow several measurement points along the optical fibre. The ultimate goal is to provide temperature mapping in the welding zone. The results from both techniques: optical fibre sensors and thermocouples were compared.
A melt flow index-based approach for the viscosity curves determination
Authors: OUBELLAOUCH Keltoum
Published: April 2024

Abstract. To optimize the polymers processing technologies, a rheological characterization of the polymer is essential to predict its behavior at specific temperatures and under varying shear rates. Simulating this process requires providing the simulation software with viscosity curves for the polymer to be processed, ensuring a reliable simulation. However, traditional rheological characterization utilizing a capillary rheometer is known for its high cost, time-intensive nature, and the need for skilled operators. In this study, a more cost-effective approach is proposed, using the Melt Flow Indexer (MFI) to obtain the experimental viscosity curves. These undergo an innovative numerical procedure based on simulating the MFI tests, reducing the numerical-experimental error in terms of pressure applied to the molten polymer. This methodology is applied to characterize three different thermoplastic polymers: polypropylene, 30% glass-reinforced polypropylene and 30% glass-reinforced polyamide. The viscosity curves obtained through this methodology are then compared to those obtained using the capillary rheometer, serving as a reference to assess the accuracy of the proposed approach.
Prediction of the microstructure morphology after the WAAM process based on the FEM simulation results
Authors: SZYNDLER J.
Published: April 2024

Abstract. To improve understanding of the material behavior of additive-produced components, this paper focuses on the development of a numerical model that reproduces a Wire Arc Additive Manufacturing (WAAM) process, with particular attention given to the evolution of the microstructure. In this study, a finite element model in Simufact Welding software is developed, that replicates a real wire arc welding process of building a multilayer straight wall. Microscopy analysis of the weld wall cut in the middle of its length gave information about the expected microstructure morphology at different levels of the build wall. The whole experimental setup is reproduced in the software Simufact Welding. Simulation results in the form of temperature-time and temperature gradient-time history are then used as superimposed thermal conditions to simulate the microstructure evolution at different areas of the welded part by using MICRESS software.
Property grading by friction induced and continuous solid-state recycling of aluminium scrap
Authors: Borgert T.
Published: April 2024

Abstract. Saving energy and reducing emissions in all sectors is essential if the ambitious climate targets of various European countries are to be met. One way of achieving this is to recycle metallic materials, which require a lot of energy to produce, in a way that minimizes the use of energy and resources. The friction-induced solid-state recycling process enables the energy-efficient recycling of what is in theory an endless aluminium semi-finished product through the continuous rotation of the wheel used. The past investigations proved the energy-efficient recycling of new aluminium scrap (powder, foil, chips) to a full semi-finished product with good properties. The continuous character of the process along with the likewise continuous feeding of the material to be recycled enables both mixing and successive processing of different aluminium alloys. For this purpose, the processed four different aluminium alloys are selectively mixed and processed simultaneously, as well as different alloys are processed one after the other to achieve a gradation of properties along the length of the semi-finished product. The recycled semi-finished product is examined regarding die filling, hardness, tensile strength as well as microstructure. The central result of the investigations is the fact that the friction-induced recycling process has different possibilities for grading the properties and microstructure in a wide range.
Innovative control system for straightening machines using sensor information from downstream processes
Authors: BATHELT L.
Published: April 2024

Abstract. Increasing the sustainability and resource efficiency of forming processes is one of today's major goals. High-strength wire materials are usually available as strip material and are subjected to a downstream forming process such as punch-bending to produce parts for the electronics industry, for example. During the manufacturing process of the semi-finished product, residual stresses and plastic deformations are introduced into the wire by rolling and drawing processes. Straightening machines are used in the production lines to compensate for these. To increase the sustainability of these production lines, the straightening process is an essential step. Before the continuous manufacturing process starts, the straightening process must be set up and the optimal roller positions must be found. Once the process is set up, the roller position settings are usually not changed. Due to missing measurement systems for the straightening quality, it is not possible to dynamically adjust the positions of the straightening rollers to variations in the material properties. This leads to deviations in the dimensional accuracy of the components to be produced and thus to an increase in the rejection rate in the manufacturing processes. To reduce the rejection rate, a novel control system for a continuous feedback control of a straightening process is presented in this paper. This leads to a reduction of the rejection rate and unnecessary preforming operations in wire straightening process. The result is an increasing sustainability and efficiency of these production process.
Remanufacturing process chain for end-of-life aluminium car body parts: Technical and economic analysis
Authors: FARIOLI D.
Published: April 2024

Abstract. This paper investigates the potential for remanufacturing aluminium sheets from end-of-life vehicles (ELVs), specifically focusing on car hoods. The study explores various pre-flattening procedures and reshaping techniques, with warm flattening showing promise despite challenges such as paint degradation. A Design of Experiment (DoE) was used to assess the impact of various factors on the flattening process, and Finite Element (FE) simulations were used to validate the experimental findings. An economic feasibility analysis was also conducted, which revealed that while technically feasible, the economic viability of this remanufacturing process is currently challenging due to the high costs compared to purchasing new sheets. However, with the increasing use of aluminium in automotive body panels and potential market shifts, these remanufacturing initiatives could become economically viable in the future, contributing to sustainability goals in the automotive sector.
Sustainability and economic assessment of an innovative automated filament winding process
Authors: BIANCHI I.
Published: April 2024

Abstract. The present paper aims at studying the environmental and economic impacts of an innovative Filament Winding (FW) process used to realize a tubular shape structural component in Carbon Fiber Reinforced Polymer (CFRP). To this purpose, the Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) methodologies were applied using a “from cradle to grave” approach. Specifically, a towbar used for aircraft pushback was considered as case study. All phases of the life cycle of the analyzed component were included (from the raw materials extraction to the disposal phase). The comparison between the CFRP towbar investigated and a traditional one in aluminum alloy was performed. The LCC analysis was conducted by considering all costs associated with the automated filament winding process, from the initial investment costs. For all the considered impact categories, the CFRP towbar showed the lowest environmental impacts, mainly due to both the reduced weight and service life fuel consumption. The cost and carbon footprint of the innovative component were associated with raw materials use.
Monitoring of the friction stir welding process: A preliminary study
Authors: Silvestri A.T.
Published: April 2024

Abstract. Friction stir welding (FSW) has received great response in both academia and industry. Extensive research has been carried out to investigate the feasibility of the FSW process for different alloys and configurations. However, the growing demand for sustainable and cost-effective manufacturing, coupled with the pursuit of high-quality products, has led to the need for continuous monitoring of the manufacturing process and machine health. Therefore, the development of robust monitoring methods to assess the condition of the welding during the process becomes crucial for sustaining high production efficiency and ensuring quality standards. In this context, this study aims to provide methods for properly monitoring each phase characterizing the FSW process. Power consumption, vibrations, and temperatures were measured and evaluated in dissimilar friction stir lap welding of aluminum alloys.
Liquid nitrogen jet impingement cooling of ultra-high strength steel in hot stamping process
Authors: CAO Dongsheng
Published: April 2024

Abstract. In the hot stamping process, elevated sheet temperatures and uneven die cooling contribute to insufficient thickness uniformity in the formed parts, leading to reduced forming efficiency and inducing severe thermo-mechanical fatigue in the die. To address these issues, a novel in-die liquid nitrogen (LN2) jet impingement cooling method is introduced to achieve a low and uniform initial holding temperature. The high-temperature steel sheet is initially cooled to slightly above the martensitic transition temperature through the application of an LN2 jet during the forming stage, followed by pressure-holding quenching. This method demonstrates remarkable outcomes, including a notable 74.19% reduction in holding time and a substantial 24.72% decrease in the maximum thinning rate. Furthermore, the maximum temperature difference between the upper and lower dies sees significant reductions of 34.57% and 25.84%, respectively.
Effect of infill percentage and pattern on compressive behavior of FDM-printed GF-CF PA6 composites
Authors: ANDREOZZI M.
Published: April 2024

Abstract. The present paper aims to assess the effect of different infill percentages and patterns on the compressive mechanical properties of specimens in Polyamide PA6 reinforced with 20% glass fibers (GF) and 10% carbon fibers (CF) printed using the Fused Deposition Modeling (FDM) technology. According to the ASTM D695-15 standard, cylindrical specimens were designed and processed through slicing software, configuring infill percentages and patterns. Three different typologies of infill pattern and two infill percentages were considered: a 100% grid infill, a 50% grid infill, a 100% concentric infill and a 50% honeycomb infill were printed. Then, compression tests were performed at room temperature to evaluate the properties of the different specimens. The comparison between the stress-strain compression curves has shown that the infill percentages and patterns significantly affect the mechanical compression properties of 3D printed components.
Microstructure mastering and fatigue behavior of duplex stainless steel obtained with laser powder bed fusion
Authors: PIRAS Maxime
Published: April 2024

Abstract. Microstructure and mechanical behavior of duplex stainless steels (DSS) are well known when elaborated with conventional processes. Nowadays, many studies aimed to characterize this material for additive manufacturing (AM) processes like laser powder bed fusion (LPBF) [1], [2]. The as-built LPBF microstructure of this alloy is totally ferritic [1]. Heat treatments are therefore necessary to recover the duplex microstructure. These heat treatments need to be optimized. The effects of annealing heat treatments on the microstructure and mechanical behavior of DSS are now known [2], but the consequences on its fatigue strength need to be explored. In this study, firstly, the duplex microstructure will be controlled by heat treatments to obtain austenitic phase with different grain morphology. Then, the influence of microstructure on tensile high cycle fatigue behavior will be investigated. As a result, a microstructure with coarser austenite grains has no effect on fatigue behavior compared to the fully ferritic As-built material whereas the finer microstructure allows an improvement. Even if there is austenite phase improving the material ductility, fatigue damage initiation is always due to pore defects.
Artificial intelligence approaches for enhanced coating performance
Authors: PERNA A.S.
Published: April 2024

Abstract. Cold spray (CS) is an innovative manufacturing technology designed to produce metallic layers on diverse materials. This process involves propelling metallic particles at supersonic speeds using pressurized gas, causing them to impact the target surface and achieve adhesion through mechanical interlocking between the powders and the substrate. Integrating Artificial Intelligence (AI) techniques can enhance the understanding and quality of this additive manufacturing process. This work focuses on predicting the characteristics of particle deformation upon collision by exploring multiple Machine Learning (ML) and Deep Learning (DL) techniques with the aim of identifying the most suitable approach. The used dataset is mixed data, composed of experimental data and FEM data, generated by Finite Element models (FEM). The input parameters for the model are categorized into three macro-categories: process, powder, and substrate. The research aims to forecast particle behavior through this multidimensional approach and contribute valuable insights for optimizing the cold spray manufacturing process by applying DL methodologies.
Multiscale Analysis of 316L stainless steel microstructures for WAAM manufacturing tool prediction
Authors: KROMER Robin
Published: April 2024

Abstract. This study proposes a new approach on a multiscale analysis of 316L stainless steel microstructures to enhance the predictability and homogeneity of microstructure for the Wire Arc Additive Manufacturing (WAAM) process. Despite the promise in the fabrication of large-scale metallic components, achieving consistent microstructure and mechanical properties remains a challenge with WAAM. This research investigates the solidification behaviors, grain morphology, and mechanical characteristics of 316L stainless steel, aiming to develop a predictive framework for WAAM process optimization. By employing a systematic approach to the fabrication and subsequent analysis of 316L stainless steel walls, the study reveals critical insights into thermal gradients, solidification rates, and their impacts on microstructural features. The findings are anticipated to inform improved fabrication strategies, leading to enhanced mechanical properties and reliability in WAAM-manufactured components based on mereotopology philosophical framework. A spatio-temporal of the different tracks could be defined based on trajectory analysis.