bluuebunny/crossref_metadata_2025 huggingface dataset:
Immigration and Unemployment Nexus
Authors: Karapınar Kocağ Esra
Published: July 2022

Youth unemployment is a rising concern for many countries across the world. The gap between youth and adult is even wider in Sub-Saharan Africa than the world average. There might be several reasons to explain, yet this chapter focuses on one controversial potential reason: immigration. This continent has experienced considerable migration flows and one could expect that immigration worsens labour market conditions for native youth. Uganda as one of the Sub-Saharan countries is investigated to see if immigrants have a significant impact on unemployment probability of young Ugandans using cross-sectional census data for the years of 1991, 2002, and 2014. Data set was drawn from IPUMS-International. Findings indicate that regional share of immigrants does not have a significant large effect on unemployment probability of youth in Uganda. A further investigation showed that higher share of immigrants in a given region lowers the probability of being not in the labour force across specifications. This means immigrants do not push native youth out of the labour force in the Uganda case.
Waste Management Analysis for Energy Generation
Authors: Pereira Marcio Batista , Quelhas Osvaldo Gonçalves , Neto Julio Vieira
Published: July 2022

Currently, sustainable means of production and consumption are insufficient to meet the Sustainable Development Goals, requiring high awareness from managers of organizations and consumers. The production of urban solid waste, climate change, the emission of greenhouse gases, as well as energy demands are complex problems that require solutions from various branches of knowledge, including in the post-COVID-19 era. Considering the challenges of urban solid waste management and energy recovery technology, it is important to reflect on the level of understanding of municipal managers, in addition to observing the economic, social, and environmental impacts of the pandemic. Through a structured literature review, the study highlights multiple perspectives that can understand and seek alternatives for socio-environmental liabilities.
Green Innovation
Authors: Marco-Lajara Bartolomé , Zaragoza-Saez Patrocinio , Martínez-Falcó Javier
Published: July 2022

Green innovation (GI) represents the voluntary commitment of companies to develop new environmentally friendly products and/or processes. This type of innovation represents a new business paradigm in which social, environmental, and societal issues are taken into consideration in a balanced way, satisfying the different types of demands of the organizations' stakeholders. GI is therefore a long-term commitment to balancing the economic needs of the organization and the environmental and social demands of customers. Given the relevance of the topic, this chapter aims to answer the following research questions: What are the characteristics that make up the concept of GI? Has there been any terminological evolution? and Under what theoretical approaches has the concept been addressed? Through a narrative review of the literature, the research addresses these research questions in order to bring clarity to the field of study, thus serving as a reference study for both neophyte and experienced researchers in the field.
Dealing With Pandemic Grief in Organizations
Authors: Tomas Cynthia Maria Montaudon , Amsler Anna , Pinto-López Ingrid N.
Published: July 2022

This chapter analyzes grief in organizations as a result of the COVID-19 pandemic and how it has become a challenge that human resources professionals need to include in their future strategies. The chapter provides a literature review surrounding the concepts of grief and loss, especially pandemic-related grief and grief in the workplace. Additionally, it includes the most relevant scales used to evaluate grief and bereavement related to different types of loss. Best practices are included to present a general overview of how grief and loss can be dealt with in a way in which the positive emotions can be used to outcast lasting negative emotions. A modified version of the pandemic grief scale was applied in a private business school in Mexico to analyze the impact of grief in the workplace during the health crisis.
From Crisis to Resilience
Authors: Singh Anurag
Published: July 2022

Today's companies must be vigilant and flexible in the face of unanticipated occurrences, such as external crises, that heighten employee uncertainty and represent direct challenges to the organization's performance and sustainability. However, as a result of the current COVID-19 pandemic, companies are suddenly forced to traverse the unexpected and hence develop novel solutions to issues occurring across a wide range of operational domains. Several of these concerns are addressed in this chapter, with a particular emphasis on the transformation of human resource management (HRM) during COVID-19, as government and firms help their workers in adjusting to their significantly altered work environment.
Efficient Pairing-Free Identity-Based Signcryption Scheme for Cloud-Assisted IoT
Authors: Kiran Medikonda Asha , Pasupuleti Syam Kumar , Eswari R.
Published: July 2022

The Internet of Things (IoT) has become a part of our everyday life. Due to limited storage and computational capabilities, data collected by IoT devices outsource to cloud servers. Although cloud servers provide many benefits, confidentiality and authenticity are the major issues. Signcryption is a cryptographic technique to address the above issues. Several identity-based signcryption schemes are proposed; however, these schemes create heavy computation and communication overhead because of bilinear pairings. This paper proposes an Efficient Pairing-Free Identity-based Signcryption (EPFIBSC) scheme based on Elliptic Curve Cryptography (ECC), which reduces computation and communication overhead. The EPFIBSC scheme's security is proven under Elliptic Curve Discrete Logarithm Problem (ECDLP). The scheme also meets the security requirements such as confidentiality, authenticity, and unforgeability. In performance analysis, the authors compare the scheme with some of the existing schemes; the comparison shows that this scheme is more efficient in computation and communication costs.
Smart and Secure Dyeing Industrial Water Pollution Monitoring Using IoT
Authors: Gathir Selvan B.  , Allirani S.
Published: July 2022

Textile industries are responsible for one of the major environmental pollution because they release undesirable dye effluents. Therefore, environmental legislation commonly obligates textile factories to treat these effluents before discharge into the water bodies. The main aim of our project is to control the parameters causing pollution and to reduce the effect of these parameters without affecting the natural or industrial environment. The industrial waste is continuously sensed from a pH sensor. If anyone parameter exceeds its standard level, this information will send to the pollution control board through the IoT module. Another important step is these parameters can be monitor through the internet by using a web page (cloud). These systems find the amount of pH present in the industrial waste during Treatment. Thus our project will monitor and control pollution efficiently and the data can be transferred through cloud communication. Cayenne is a GUI to the user and IoT is used for outside world interaction for information transfer.
A Case for Ethical and Administrative Considerations on Grade Inflation
Authors: Hammond Helen G. , Almy Gary R.
Published: July 2022

The inflation of grades weakens the integrity of academics in colleges and universities. In addition to weakened academic integrity, it involves re-ranking and impacts earnings. The practice of grade inflation also provides a mismatch in the labor market resulting in students who are highly skilled being harmed. Academic administrators, college leadership, and faculty can partner to develop policy, training, and best practices that diminish or completely abate the inflation of grades. The purpose of this case study is to examine the issue of grade inflation in higher education using a three-part evaluation that will include a review of the case and case analysis followed by a recommended case solution.
Design and Implementation of IoT Platform Education System Based on Open Source Hardware
Authors: Choi Sun-O , Kim Jongbae
Published: July 2022

The IoT is the very critical core to 4th industrial revolution that will lead to hyper-connectivity, hyper-intelligence and hyper-reality. Recently, the importance of software, electronics, mechanical, and convergence education has emerged, and thanks to this, research and development for IoT platform educational equipment is in progress. However, in the educational field, practical devices for IoT education, namely, various sensors, breadboards, Arduino, and Raspberry Pi are purchased and used respectively. This problem is due to the lack of integrated IoT platform educational equipment. In this study, an integrated IoT platform education system based on open source hardware was the operation and performance are verified by using IoT platform system where various sensor and device module are equipped and controlled. The IoT in this article has strong points in openness, compatibility, high availability, economy and space utilization, which is to expected to improve the efficiency an educational field.
Student Expectations on Service Quality as a Determinant of Service Planning and Marketing for Higher Education Institutions in Tanzania
Authors: Suru Majiyd Hamis
Published: July 2022

This paper examines the university students' expectations of higher education institution (HEI) service quality (SQ) as a determinant of service planning and marketing of institutions. The paper embraces three models of customer-provider relationships to examine the possibility of satisfying students' expectations on SQ to market HEIs to prospective students. These models encompass the relationship marketing (RM) model, Tinto's students integration theory, and Parasuraman et al.'s conceptual model of service quality (SERVQUAL). The study used students' demographic characteristics to examine their expectations about SQ in HEIs and the likelihood to attract other students to do the same for marketing strategy. Multiple linear regressions were used to assess the influence of demographic characteristics on students' expectations about SQ. Students' years of study and the degree programs had statistical significance on SQ. The overall service quality (OSQ) was a determinant of students' likelihood to entice colleagues to the same programme.
Friction Stir Welding of Thin Sheets of the AA2024-T3 Alloy with a Ceramic Tool: RSM and ANOVA Study
Authors: Mysliwiec Piotr , Śliwa Romana Ewa
Published: July 2022

In this study a new ceramics tools with different groove distributions were designed and manufactured in order to enrich technological storage of joining thin-wall structures and obtain sound joint with high quality of alclad AA2024-T3 alloy of 0.5 mm in thickness. Four types of tools were tested, without grooves, with 1, 2 and 6 grooves. The tools are made of two materials. The straight shank is made from tungsten carbide and tool body made from ceramics strengthened with whiskers. The influence of technological parameters on the strength of FSW joints was tested by the RSM (Response Surface Methodology) and ANOVA (analysis of variance) method. The least durable weld is produced by a tool without grooves. The 1 and 2-flute tool produces a good quality weld over a wide range of tool speeds. It has been shown that the grooves on the tool shoulder significantly affect the quality of the obtained FSW joint.
A New Solution for Viscosity Identification in a Polymer Production Line via Convection Analysis
Authors: Lin Qiao , Allanic Nadine , Girault Manuel , Deterre Rémi , Mousseau Pierre
Published: July 2022

To overcome the inlet temperature uncertainties during an in-line thermo-rheological characterization and to further apply a differential convection method for an injection molding process, a concept of device designing is proposed in this work. An analytical and numerical investigation proves that the proposed concept can provide information on the viscosity of the material via thermal measurements, despite a poorly known inlet temperature.
Increasing the Forming Limits in Hole Flanging of Dual-Phase (DP) 1000 Steel Using Punch Rotation
Authors: Besong Lemopi Isidore , Buhl Johannes , Härtel Sebastian , Bambach Markus
Published: July 2022

Dual-phase (DP) steels are widely used in sheet metal stamping. However, they are typically characterized by low hole expansion ratios. Since hole flanging is very often applied to sheet metal parts, solutions for improving hole flangeability are needed. In this study, high-speed punch rotation is applied in hole flanging of DP 1000 to generate frictional heat and increase formability. The flanges were formed using a punch rotating at 8000 rev/min and varying axial feeds. A maximum hole expansion ratio (HER) of 3.6 is obtained in the tests compared to ~1.58 in conventional hole flanging. The high formability is explained by the high temperature recorded in the process. The effects of temperature and strain rate on the formability of DP 1000 are examined by tensile tests conducted at different conditions. The tensile tests show an increase in formability at high temperatures. Optical microscopy at the flange edge reveals a change in the microstructure of the steel from the characteristic dual phase to a martensitic structure with elongated grains.
Optimization of Machining Process for Improved Sustainability
Authors: Rotella Giovanna , Franchi Rodolfo , Del Prete Antonio
Published: July 2022

Optimization procedures can be considered useful for machining applications. Most commonly, the optimization method is applied to search a trade-off between costs and profits, and it allows searching for the optimum cutting parameters to maximize the useful tool-life, minimize the time of production, etc. The selection of the optimal machining conditions which could maximize the process sustainability performance and the fatigue life of the machined product is the objective of the work presented. The numerical model developed is useful to have integrated results as input for the optimization algorithm in order to drastically reduce the number of experimental tests needed. In the present work, the optimization of the performance measures is carried out using a self-written Genetic Algorithm code implemented using the MATLAB software.
Cutting Force in Drilling with Flat Bottom Drill
Authors: Tamura Shoichi , Matsumura Takashi
Published: July 2022

Flat bottom drills at a point angle of 180 deg. have recently been applied to not only drilling on inclined surfaces but also flat bottom holes in terms of the dimensional accuracy and the process efficiency. Controlling the cutting force, the tool damage, and the surface finish, the corner shape is a critical parameter in the design of the flat bottom drill. The paper discusses the effect of the corner radius on the cutting forces and the surface finish in drilling with flat bottom drills. The typical differences in the cutting force are confirmed during the edge engagement. Then, the cutting force is simulated with a chip flow model, in which the chip flow angle is determined to minimize the cutting energy. The cylinder surface finishes and the burr formations are associated with the chip flow direction and the uncut chip thickness at the end of the lip.
3D Modeling of Polymer Selective Laser Sintering Process: Laser-Polymer Interaction Modeling
Authors: Zhang Lan , Boutaous M'hamed , Xin Shi He
Published: July 2022

During selective laser sintering (SLS) process, the laser transmission in the polymer powder bed and solid polymer is different. The laser interaction with the powder bed splits into absorption, reflection and scattering three parts. The photon scattering between the polymer particles leads laser repeated absorption by particles, changes the photon’s traveling directions, and further influences the temperature distribution at the scanning laser area. New distribution and attenuation coefficients need to be introduced for correcting the results. For better simulating the photons travel ways, we introduce the modified Monte-Carlo method and Mie-Scattering theory to predict laser distribution in the polymer powder bed, by considering the scattering phenomenon. This paper analyses how the initial porosity influences the maximum temperature, laser attenuation rate and porosity change rate. The results show that lower porosity promoting the laser scattering phenomenon, decreasing the maximum temperature and the powder porosity change rate.
Effect of Finite Element Mesh Size and Time-Increment on Predicting Part-Scale Temperature for Powder Bed Fusion Process
Authors: Ullah Rizwan , Lian Jun He , Wu Jiao Jiao , Niemi Esko
Published: July 2022

Simulating powder bed fusion processes (PBF) can reveal temperature evolution in transient mode. Accurate temperature prediction using finite element (FE) method demands both mesh and timeincrements to be very small; thus, requiring a high computational cost. To avoid this, in part-scale simulation, coarse meshes representing multiple powder layers added at once, are usually used which results in fast solving of FE models. Powder layers and time increments are lumped in such a configuration, which results in a deviation of the temperature history. This research proposes a methodology to predict the nodal temperature (NT) due to the combined effect of space and time lumping for part-scale FE thermal simulation for PBF processes. It shows its effects in predicting both the local temperature history and the average far-field temperature.
Optimization of Laser Metal Deposition Process for 2205 Duplex Stainless Steel
Authors: Arbo Siri Marthe , Saai Afaf , Sørli Sture Henning , Dybdahl Cato , Onsøien Morten , Nedreberg Mette
Published: July 2022

This work aims to optimize the process parameters for laser based DED manufacturing of a water jet impeller with critical requirements to material and mechanical properties. The concerned material is 2205 duplex stainless steel with balanced ferrite-austenite microstructure. The optimization approach of the processing parameters relies on the assessment of their effect on microstructure and mechanical properties versus the requirements set by the maritime industry. The work aims to achieve an as-built microstructure with the required ferrite-austenite balance and mechanical properties, without the need for post-processing heat treatment. The work particularly focuses on the influence of the deposition speed of the DED process. The results show that duplex stainless steel with a 50-50 ferrite-austenite balance can be achieved directly from the DED process. A high deposition speed produced fine-grained microstructure resulting in a high tensile strength and toughness, well above the set requirements. However, it reduced the ductility, represented by tensile elongation due to the formation of welding defects. Reducing the deposition speed by 20% eliminated the welding defects but resulted in the formation of a distinct microstructure with coarse grains, elongated in the deposited layer. This microstructure improved the tensile elongation, but strongly reduced the toughness, represented by Charpy V impact energy values. The coarse grains in the deposited layer facilitated a fast fracture propagation initiated by the placement of the Charpy V notch. However, the presented results demonstrate the great potential for manufacturing duplex stainless steels by DED, where a suitable microstructure for optimal mechanical performance can be obtained by narrowing the optimization windows on the process parameters.
Fabrication of Anti-Icing Surface Structures on Aluminum Alloy for Aerospace Applications
Authors: Cholkar Abhijit , McCann Ronan , Kinahan David , Brabazon Dermot
Published: July 2022

Icing, the phenomenon of the formation and accumulation of ice or frost on a surface due to the solidification of water droplets at low temperature can be undesirable in many applications. Surface icing can lead to increased energy consumption in aerospace and automotive applications due to increased aerodynamic drag. Ice formation can also present a mechanical and electrical safety hazard, and as such significant work has been done to produce surfaces with anti-icing properties through surface modification to decrease ice formation and adhesion to surfaces. One route toward the generation of anti-icing surfaces is through laser surface processing. Laser micro/nanostructuring of surfaces has advanced greatly in recent years due to advancements in laser source technology and reduction in capital costs for ultrafast femtosecond pulsed machining lasers. Laser material processing offers a rapid, scalable, and non-contact method for fabricating large area anti-icing surfaces. In this work, the production of anti-icing surfaces using femtosecond laser micro-and nanostructuring on aluminum alloy 7075 surfaces was examined. With an aim to optimize the anti-icing properties of the substrates, laser parameters such as pulse energy, repetition rate and beam scanning speed were varied to produce highly defined microstructures on the aluminum surface.Various functional properties such as hydrophobicity and surface roughness are examined.
Formability Assessment of Variable Geometries Using Machine Learning - Analysis of the Influence of the Database
Authors: Zimmerling Clemens , Fengler Benedikt , Kärger Luise
Published: July 2022

Surrogate modelling has proven to be an effective strategy for time-efficient analysis and optimisation of expensive functions such as manufacturing process simulations. However, most surrogate approaches generate problem-specific “one-off” models, which cannot be reused in other, even similar scenarios. Hence, variations of the problem, e.g. minor geometry changes, instantly invalidate the surrogate. Image-based machine learning (ML) techniques have been proposed as an option to train a surrogate for variable geometries. However, it is currently unclear how to construct a sufficiently diverse set of generic training geometries and what effect different databases have. This work investigates the effect of different databases on the prediction accuracy of an ML-assessment of component manufacturability. The considered use-case is textile forming (draping) of a woven fabric. Sampling plans generate different numbers of training geometries, which are in turn evaluated in draping simulations. An image-based ML-algorithm is trained on these process samples and evaluated on a set of validation geometries. Results show that the diversity of the training geometries has a greater impact on the prediction accuracy than the number of samples. The results also hint that a comparably low number of geometry samples suffices to give meaningful results. With these findings, ML-techniques are considered a promising and time-efficient tool for manufacturability assessment at early stages of part and process design.
Setting Residual Stresses in Tensile Stress-Superposed Incremental Sheet Forming
Authors: Maaß Fabian , Hahn Marlon , Tekkaya A. Erman
Published: July 2022

Incremental sheet metal sheet forming (ISF) is a flexible forming process to manufacture sheet metal parts. ISF processes allow a control of residual stresses depending on the process parameters and the acting forming mechanisms. These forming-induced residual stresses highly influence the product properties. This paper presents numerical and experimental results demonstrating the influence of biaxial tensile stress-superposed incremental forming (TSSIF) on the residual stress of truncated cones. An adjustable clamping frame is used to apply defined tensile stresses over the sheet plane in biaxial direction during forming. Residual stresses are evaluated by means of x-ray diffraction on both sides of the cone wall. Tensile stress-superposition shifts the residual stress amplitudes to the tensile residual stress region, depending on the amount of initial tensile stress. TSSIF can be used to improve the product properties of compressive stress-imposed components.
Multistage Deep-Drawing with Alternating Blank Draw-in for Springback Reduction in Transfer and Progressive Dies
Authors: Briesenick David , Liewald Mathias
Published: July 2022

Cold formed sheet metal parts made of advanced high-strength steels (AHSS) offer a high potential for a lightweight, durable and economic design. However, manufacturing dedicated, high-strength parts with cold forming technologies such as conventional deep-drawing often results in unacceptable shape deviations due to elastic springback after unloading the part from the forming tools. Therefore, various springback compensation methods have been established to ensure dimensional quality of such sheet metal parts. At the Institute for Metal Forming Technology (IFU Stuttgart), deep-drawing with alternating blank draw-in was developed in this context as a new approach to reduce springback and enhance cold forming of AHSS sheet metal parts. Presented work provides numerical sensitivity analysis as well as experimental studies about this new forming method. The asymmetric and alternating blank draw-in, which is changed within a multistage forming process sequence, results in an alternated bending over tool radii and leads to a beneficial stress superposition in the part wall area with reduced springback phenomena. Compared to conventional deep-drawn sheet metal components, springback of a benchmark part geometry could thus be reduced over 75 % by a three-stage forming process with an optimized blank draw-in kinematic.
A Two-Temperature Model Based on Fin-Approximation for Transient Longitudinal Heat Transfer in Unidirectional Composite
Authors: Dusserre Gilles
Published: July 2022

The reliability of a two-temperature model is assessed in the case of longitudinal heat transfer in unidirectional composites. One interest is that it makes it possible to apply separate boundary conditions or source terms on the fibre and the matrix (emissivity for example), without necessitating an explicit description of the fibre and matrix domains. For the sake of simplicity, the model under study is based on a fin-approximation in both fibre and matrix, which implies a high interfacial thermal resistance. The range of validity of this assumption is investigated by comparing the model to an axisymmetric one-temperature model, using non-dimension variables and Dirichlet boundary conditions. It turns out that this range of validity is strongly dependent on the parameters.
Influence of the Grain Boundary Curvature Model on Cellular Automata Static Recrystallization Simulations
Authors: Niewczas Szymon , Sitko Mateusz , Madej Łukasz
Published: July 2022

Determination of the influence of grain boundary curvature model type on the cellular automata (CA) static recrystallization (SRX) simulation predictions is the primary goal of the research. The developed CA model is a full-field approach that captures local heterogeneities in grain morphology, crystallographic orientation, and distribution of stored deformation energy. The main driving force of the model is the value of the stored energy; however, the curvature of the grain boundary may also play a role during the recrystallization. Therefore, different variants of grain boundary curvature calculations within the discrete computational domain during recrystallization and additionally subsequent grain growth are compared within this work.
Measurement and Analysis of Deformation Behavior of Polyethylene Tube Subjected to Linear Loading and Unloading Stress Paths with Large Strain
Authors: Kubo Sohta , Kuwabara Toshihiko , Sumiyama Takuya , Kobayashi Takaya , Fruichi Kenji , Nonomura Chisato
Published: July 2022

A material testing apparatus for measuring the biaxial deformation behavior of a polymer tube has been developed to quantitatively evaluate the deformation behavior of polymeric materials. The testing apparatus can apply axial force and internal pressure to a tubular specimen. A noncontact strain measurement system was also developed, and the biaxial strain components and the radius of curvature in the axial direction of the bulging specimen are continuously measured to control the stress path applied to the specimen. Polyethylene tube with an outer diameter of 17 mm and a thickness of 2 mm are used as a test sample. The tubular specimens were subjected to linear stress paths with stress ratios of σΦ:σθ =1:0, 4:1, 2:1, 4:3, 1:1, 3:4, 1:2, 1:4, and 0:1, where σΦ and σθ are the axial and circumferential stress components, respectively, applied to the central area of the bulging specimen. Loading and unloading tests were performed to determine the biaxial true stress-logarithmic plastic strain curves. The strain rate was 1×10-3s-1. From these test results, contours of plastic work and the directions of the plastic strain rates were measured to identify a proper material model for the test sample using the Yld2000-2d yield function (Barlat et al., 2003).
Finite Element Analysis of AA 6016-T4 Sheet Metal Forming Operations Using a New Polycrystalline Model
Authors: Revil-Baudard Benoit , Cazacu Oana , Chandola Nitin
Published: July 2022

A major challenge in forming polycrystalline aluminum alloy sheets is their strong plastic anisotropy, namely the flow stresses and plastic strains depend on the loading direction. This plastic anisotropy is due to the anisotropy of the constituent crystals and the preferred orientations that they assume in the polycrystalline material i.e. crystallographic texture. Recently, in [1] we developed a single-crystal yield criterion that involves the correct number of anisotropy coefficients such as to satisfy the intrinsic symmetries of the constituent crystals and the condition of yielding insensitivity to hydrostatic pressure. This single-crystal criterion is defined for any stress state. It is shown that a polycrystalline model that uses this single-crystal criterion in conjunction with appropriate homogenization procedures leads to an improved prediction of the plastic anisotropy in macroscopic properties under uniaxial tension and shear loadings for polycrystalline aluminum alloy 6016-T4. Moreover, results of FE simulations of cup forming operations demonstrate the predictive capabilities of this polycrystalline model.
Characterization of Abrasion and Erosion Mechanisms during Abrasive Waterjet Machining of Hard Metals
Authors: Morisset Raphaël , Gilles Patrick , Cohen Guillaume , Gregoire Michel
Published: July 2022

Abrasive water jet machining is a process that removes material using sand and water. This versatile process uses a high-pressure water jet loaded with abrasive particles of mineral origin. It allows the machining of all materials and is particularly suitable for machining or stripping applications on hard metal sheets. Due to a local action, the abrasive water jet limits heating and deformation. During machining, the removal of material occurs abrasion and erosion [1]. The identification of the respective importance of this abrasion and this erosion conditions the precision of the modeling of the machined depth. In this study, these mechanisms are presented and characterized for machining on 6mm thickness TiAl6V titanium alloys sheets with or without inclination of the jet. It is possible to model an elementary passage and it allows predicting the pocket bottom profile obtained after a succession of passages. During machining, two mechanisms appear. Abrasion occurs when machining an elementary pass. Erosion will characterize the effect of repetition of passages. The analysis of the machined profiles makes it possible to characterize the influence of the abrasion mechanism and abrasion mechanism. The variation of the coefficients associated with these mechanisms can be characterized as a function of the angle of inclination of the jet.Keywords: Abrasive water jet machining, Material removal mechanism, Abrasion, Erosion, Titanium alloy, Abrasive particles
Material Characterization of Hybrid Components Manufactured by Laser-Based Directed Energy Deposition on Sheet Metal Substrates
Authors: Kreß Maximilian , Bartels Dominic , Schmidt Michael , Merklein Marion
Published: July 2022

Laser-based directed energy deposition (DED-LB/M) allows the application of a wear-resistant metal coating to the surface of a sheet metal substrate. Subsequent deep drawing of the part enables high material efficiency, significantly shorter production times, and lower unit costs compared to, for example, solely machined production of the entire component. At the same time, energy-intensive global heat treatment strategies can be avoided. For the numerical analysis of such hybrid process chains, both the sheet metal substrate and the additively applied coating are usually characterized individually. However, the low thickness of the coating in combination with a relatively high welding depth, which is required for a good bond to the sheet metal substrate during subsequent forming, lead to a strong gradient of the mechanical properties as well as complex mechanical interactions in the bonding zone. Therefore, appropriate characterization methods are required. In this work, an investigation of different influencing factors, like the rolling, hatch and tensile direction, is carried out with the aid of tensile tests using hybrid specimens. In this way, interactions between the influencing factors are identified. As substrate, 3.5 mm thick 16MnCr5 blanks are used, with an approximately 0.68 mm thick coating of Bainidur® AM. In addition, an optical surface roughness measurement and metallographic analysis of the tensile specimen’s edge area after laser cutting is performed.
Towards a Holistic Approach for an Efficient Determination of the Rheological Behavior of Sheet Molding Compounds for Process Simulation
Authors: Imbsweiler Anna Julia , Shinoura Yasutaka , Colin David , Zaremba Swen , Drechsler Klaus
Published: July 2022

Sheet Molding Compound (SMC) materials offer attractive specific strength and stiffness properties. With an addition of short cycle times, the possibility for complex geometries and a high recycling potential, this material is a promising solution for the manufacture of lightweight components of numerous industrial sectors. Accurate and reliable simulation can contribute to a fast and competitive development process and effectively reduce the time-to-market. Especially, the accuracy of the simulative filling process is crucial to be able to predict the mechanical properties and hence, pave the way to structural parts. An appropriate characterization of the rheological behavior is therefore, crucial for accurate simulation results. To this purpose bar flow tests are performed and the experimental results are compared to the numerical results. A sensitivity analysis is performed to investigate the influence of each parameter on the simulation outcome. Furthermore, guidelines to improve the simulation accuracy and the testing equipment are derived. In the testing method some improvement potential was identified and the necessity for a testing method closer to the compression process could be established.
Drawing Capability of High Formable Packaging Steel: Comparison of Limiting Drawing Ratio and Forming Limit Curve
Authors: Knieps Fabian , Köhl Manuel , Merklein Marion
Published: July 2022

To assess the suitability of different packaging steels for complex deep drawing applications, nowadays, the total elongation and the Lankford coefficients in simple tensile tests are used. However, the simple use of uniaxial tensile tests is not supposed to predict the limiting drawing ratio precisely and thus the suitability for deep drawing applications. At the same time, the conduction of limiting drawing ratio experiments is extensive and requires a high testing effort. Therefore, in this work, the correlation between the forming limit curve results were compared to the results of limiting drawing ratio experiments to predict the formability of packaging steel by a much simpler criterion. At the same time, different approaches to calculate the plane strain forming limit by tensile test data were used to assess the drawing capability of packaging steel. Results revealed a strong correlation between the measured plane strain forming limit and the limiting drawing ratio at a fixed blank holder force. However, calculation methods based on tensile test data were not able to predict the drawing capability sufficiently.
Data-Driven Derivation of Sheet Metal Properties Gained from Punching Forces Using an Artificial Neural Network
Authors: Schenek Adrian , Görz Marcel , Liewald Mathias , Riedmüller Kim Rouven
Published: July 2022

The ongoing digitization of production processes provides new possibilities and potentials for process monitoring of forming and stamping processes. The component quality achievable by these processes is strongly dependent on the properties of the sheet metal material, so that a permanent digital recording of material data offers high potential for monitoring each component produced. In this context, presented paper deals with a novel AI-based method for the direct determination of ma-terial parameters from measured punching force curves. Using software systems Python and Tensor-Flow, an artificial neural network was first set up to determine mechanical material parameters (out-put data) from punching force curves (input data). As data basis for the adopted neural network, force curves were measured during punching of various sheet metal materials using a punching tool equipped with a direct force measurement device. Punching force curves were experimentally deter-mined for the sheet metal materials DP1200, DP1000, DP800, DP600, HX380LA, DC03 and DX54. Additionally, tensile tests were performed for these sheet metal materials to determine ultimate tensile strengths (Rm), yield strengths (Rp0.2, Re), uniform strains (Ag), elongations at break (At) and strain hardening exponents (n). The presented paper reveals that neural networks can accurately quantify the relationship between characteristic parameters of punching force curves and the mentioned me-chanical material properties.
Material Parameters Sensitivity on Springback Modelling of Simple Bending Process
Authors: Béres Gábor J. , Lukács Zsolt , Tisza Miklós
Published: July 2022

Springback is one of the major defects that continuously concerns the sheet metal experts’ community. It is has long been known that the sheet thickness, the bending angle and the yield stress of the material primarily affect the angle change after the tools’ release. Besides, the consideration of the kinematic hardening (KH) model has powerful influence on the modelling results, too. In this study, we overviewed several possible factors on the springback with finite element modeling of a simple V-die bending operation, highlighting the effect of the material variables on the final shape. AutoForm® R7 software and the built-in theory of kinematic hardening were used for the material characterization, coupled with the Hockett-Sherby isotropic hardening rule as well as the Yld89 yield criterion. The material data for modeling kinematic hardening behavior were obtained by cyclic tension-compression tests, whilst the isotropic hardening and the yield surface parameters were acquired by simple uniaxial tension tests. The simulation results were compared to the experimental springback observations obtained by a CNC bending machine, without using springback compensation. A detailed parametric study was also carried out to highlight the level of criticality of the applied material variables on the final angle change.
Selective Laser Melting of Ti6Al4V: Effects of Heat Accumulation Phenomena due to Building Orientation
Authors: Palmeri Dina , Buffa Gianluca , Pollara Gaetano , Fratini Livan
Published: July 2022

Titanium alloy Ti6Al4V is one of the most utilized alloys in the field of additive manufacturing due to the excellent combination of mechanical properties, density and good corrosion behavior. These characteristics make the use of this material particularly attractive for additively manufacturing components with complex geometry in sectors such as aeronautics and biomedical. Selective Laser Melting (SLM), by which a component is fabricated by selectively melting of stacked layers of powder using a laser beam, is the one of most promising additive manufacturing technologies for Ti6Al4V alloy. Although this technique offers numerous advantages, it has some critical issues related to the high thermal gradients, associated with the process, promoting the formation of a metastable martensitic microstructure resulting in high tensile strength but poor ductility of the produced parts. The formation of microstructural defects such as balling and porosity can occur together with the presence of residual stresses that may significantly affect the mechanical characteristics of the component. Specific process parameters and geometries can determine heat accumulation phenomena that result in a progressive decrease in thermal gradients between layers. These heat accumulation phenomena are influenced by the number of layers deposited, but also by the building orientation that, for a given geometry, determines a variation of the deposited surface for each layer.
Damage Analysis of Hybrid Composites Under Multi-Impact Loads: An Experimental and Numerical Study
Authors: Bruno Matteo , Carrino Luigi , Donadio Federica , Esposito Luca , Lopresto Valentina , Papa Ilaria , Viscusi Antonio
Published: July 2022

Laminated composite structures are subjected to impact damage during maintenance and manufacturing operations and their life service. Driven by the necessity to value damage tolerance and durability of composite materials, an analysis of multi-hit impact is conducted to reproduce the real service conditions. Despite many studies in the literature investigated the properties of composites at low impact velocity, in contrast the behavior of the hybrid configuration, especially at repeated impacts, result still little known. This work presents an experimental and numerical study of the dynamic behavior at the repeated low-velocity impact of a carbon and glass fibers hybrid composite laminate.
Methodology to Investigate the Transformation Plasticity for Numerical Modelling of Hot Forging Processes
Authors: Behrens Bernd-Arno , Brunotte Kai , Wester Hendrik , Kock Christoph
Published: July 2022

Hot forging is a complex process involving the mutual influence of numerous thermo-mechanical-metallurgical material phenomena. In particular, the strains of transformation-induced plasticity (TRIP) have a significant influence on the distortions and residual stresses of the components. The TRIP strains refer to the anisotropic strains depending on the orientation and significance of the stress conditions during cooling superimposed to the phase transformation. With the use of numerical models, the impact of this effect can be investigated in order to ensure the production of high quality components. However, an experimental determination of the characteristic values of TRIP is challenging, which is why only few corresponding data are available in the literature. Therefore, this paper presents an experimental and numerical methodology as well as the results of studies on the interaction between stresses and phase transformations in the materials AISI 4140 and AISI 52100. The investigations of the TRIP strains are carried out using hollow specimens, which are thermo-mechanically treated in the physical forming simulator Gleeble 3800-GTC. The specimens are austenitised, quenched to test temperature and held there while diffusion controlled phase transformation takes place. The extent of TRIP as a result of different superimposed tensile or compressive loads is determined by means of dilatometry. In addition, the extent of TRIP for diffusionless martensitic phase transformations was investigated by continuous cooling tests under tensile and compressive loads. It was found that the transformation plasticity varies depending on the material, the phase type, the temperature and the tensile or compressive stresses. Subsequently, simulations of the physical experiments using the FE software Simufact.Forming verified the determined phase specific values of TRIP.
Ultrasonic Monitoring of Part’s Height and Layer Thickness in Powder Bed Fusion
Authors: Raffestin Marc , Domashenkov Alexey , Faverjon Pierre , Bertrand Philippe , Courbon Cédric
Published: July 2022

This paper presents a preliminary study on an in-situ ultrasonic measurement technique applied to monitoring part’s height and defect occurrence during the Laser Powder Bed Fusion process. Firstly the ultrasonic wave speed is determined for LPBF manufactured 100Cr6 samples with a pulse echo configuration and a 10Mhz ultrasonic wave. A measured propagation speed value, of 5660 ±100m/s in every direction confirms the isotropy of the obtained LPBF samples. Secondly, the ultrasonic pulse echo technique is used to monitor the part’s height evolution during the process based on the measured propagation velocity. This new method provides in-situ measurements showing that the actual remelted layer thickness value oscillates in the range of ± 30% of the theoretical layer thickness.
Porosity Prediction in AM Using PBF-LB Employing Time-Series Classification
Authors: Mahato Vivek , Brabazon Dermot , Caputo Annalina
Published: July 2022

Additive Manufacturing (AM) using Powder-Bed Fusion Laser-Beam (PBF-LB) has great potential; however, it has challenges due to its sensitivity to the process parameters [1]. The availability of big data generated in AM facilitates the employment of Machine Learning (ML) tools to understand the process and have a predictive control over the production. An intelligent system like this can thus reduce material wastage and energy cost while increasing a plant’s product quality and throughput. Time-series summary statistics (like mean and variance) can discard valuable discriminatory signatures embedded in raw sensor data. Therefore, special ML time-series classification (TSC) tools that can extract and utilise these signatures from the raw data are much more effective for a task like porosity prediction [1]. However, the data employed in [1] pertains to products with artificially designed pores or gaps. This study focuses on naturally occurring pores, rarer, and evaluates k-Nearest Neighbour (k-NN) with Dynamic Time Warping (DTW) over real-world manufacturing data to classify the porosity of individual raster scans. We believe that natural pores have more diverse signatures than artificial pores, as each pore varies in characteristics (like size and morphology).