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PEOPLE@HES-SO – Annuaire et Répertoire des compétences
PEOPLE@HES-SO – Annuaire et Répertoire des compétences

PEOPLE@HES-SO
Annuaire et Répertoire des compétences

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Sallem Haifa

Sallem Haifa

Professeur-e HES Associé-e

Compétences principales

Additive manufacturing

Modeling and simulation

Materials Science and Engineering

LPBF SLM Process Analysis

Powder technologies

Manufacturing process optimisation

  • Contact

  • Enseignement

  • Recherche

  • Publications

  • Conférences

Contrat principal

Professeur-e HES Associé-e

Téléphone: +41 58 606 87 45

Bureau: ENP.23.N114

HES-SO Valais-Wallis - Haute Ecole d'Ingénierie
Rue de l'Industrie 23, 1950 Sion, CH
HEI - VS
Domaine
Technique et IT
Filière principale
Systèmes industriels
BSc HES-SO en Energie et techniques environnementales - HES-SO Valais-Wallis - Haute Ecole d'Ingénierie
  • Science des matériaux
  • matériaux polymères
  • statique des structures
  • Reverse Engineering
  • Choix des matériaux -Granta
MA BFH/HES-SO en Architecture - HES-SO Master
  • Traitements de surfaces
  • Matériaux Polymères et Composites

En cours

Contrôle in-situ des pièces imprimées par fusion laser sélective SLM) en utilisant le Machine Learning

Rôle: Requérant(e) principal(e)

Financement: HES SO

Description du projet :

Développer une méthode de contrôle qualité in-situ des pièces imprimées par SLM en temps et en conditions réels.

Cette approche est basée sur l’analyse des données remontées depuis les capteurs cyber-physiques avec les techniques de l’IA

Equipe de recherche au sein de la HES-SO: Sallem Haifa

Partenaires académiques: Ghorbel Hatem, HE-Arc Ingénierie

Durée du projet: 01.03.2021 - 16.01.2022

Statut: En cours

Robust heat flux sensor for high temperature industrial processes

Rôle: Co-requérant(s)

Financement: Innosuisse

Description du projet :

The field of this project is high temperature industrial processes, which represent an important share of overal energy consumption (ca.10%), usually show high energy cost for the concerned industries (>1'000'000 CHF/yr on a single site), but also have an impact on their CAPEX and OPEX in terms of equipment operating at high temperature and its maintenance/lifetime/hazards.  Insufficient monitoring or control of processes, and ageing or failing equipment lead to substantial waste heat losses for these producers/users. Reducing these heat losses will improve their competitiveness by reducing their energy bills and maintenance/repair costs, and could increase their productivity, efficiency, and product quality. In addition, this will often limit CO2 emissions and other environmental impact of these industries, for which they may be taxed, hence saving tax cost. High temperature industrial processes are not often optimized because of their complexity, uneasy access, unavailability of direct loss measurements and lack of predictive maintenance. From experience, substantial energy savings (10-20%) can be achieved by relatively simple low cost measures - if properly located.

The aim of this project is to help these industries by proposing a novel heat flux sensor capable of being deployed in challenging industrial environments (200-1000°C). In addition to temperature indication only, a heat flux sensor directly quantifies heat loss (in W/m2) at locations of interest in the high temperature process, opening the way to better process monitoring and process control, to the surveillance/detection of potential defects or anomalies, and to conditional maintenance of equipment or component parts.

We see applications in: steel making, metallurgical foundries; glass making; cement; chemical plants, oil and gas industry; incineration; power plants; engines, heat exchangers, furnaces, gas turbines, boilers, etc.; even the watch industry expressed interest in such sensors.

Equipe de recherche au sein de la HES-SO: Rey-Mermet Samuel , Joris Steve , Sallem Haifa , Cinna Adeline

Partenaires académiques: Jan Van Erle, EPFL-Sion

Partenaires professionnels: Confidentiel, Confidentiel Suisse

Durée du projet: 01.03.2021 - 28.02.2023

Montant global du projet: 700'000 CHF

Statut: En cours

Valorisation de la biomasse en electricité - ELECTRIVERT

Rôle: Requérant(e) principal(e)

Description du projet :

The ELECTRIVERT project aims to transform biomass into clean and efficient electricity using Solid Oxide Fuel Cell (SOFC) technology powered by biogas. A significant part of this project focuses on the development of advanced materials and manufacturing processes to optimize the performance, durability, and efficiency of SOFC systems for biogas applications.

Equipe de recherche au sein de la HES-SO: Sallem Haifa

Statut: En cours

Prothèse Fémorale Bionique Innovante : Biomimétisme, Fabrication Additive et Revêtement à l'Hydroxyapatite pour une Intégration Osseuse Optimale

Rôle: Requérant(e) principal(e)

Description du projet :

This project focuses on the development of an innovative bionic femoral prosthesis that leverages cutting-edge technologies such as biomimicry, additive manufacturing (Selective Laser Melting - SLM), numerical simulation using Finite Element Method (FEM), and surface functionalization through a hydroxyapatite coating. The goal is to achieve optimal osseointegration and enhance the mechanical and biological performance of femoral prostheses.

Equipe de recherche au sein de la HES-SO: Sallem Haifa

Statut: En cours

Echangeur de chaleur 3D pour piles à combustible à oxydes solides (SOFC/SOEC).

Rôle: Requérant(e) principal(e)

Description du projet :

Les objectifs de ce projet consistent à concevoir et fabriquer par SLM un échangeur thermique multicanaux permettant d’améliorer le rendement de la chaîne de conversion énergétique au niveau des piles SOFC.

Equipe de recherche au sein de la HES-SO: Sallem Haifa

Partenaires professionnels: CELECTIS Sàrl

Statut: En cours

Collaborative Framework for effective Education of reliable 3D Printing Technologies: Virtual & Physical Prototyping

Rôle: Requérant(e) principal(e)

Financement: Leading House MENA

Description du projet :

The goal of this project is integration and the dissemination of reliable AM technologies into engineering teaching, and to bring more scientific comprehension of the process. To that end, this project fosters synergies between the skills provided by the two academic institutions (HEI Valais-Switzerland and UTM/ENIT-Tunisia) to develop a collaborative framework for effective education of a reliable metal AM technologies based on the combination of both virtual and physical prototyping, respectively through the development of numerical predictive models, and printing tangible 3D samples. This approach aims to characterize the achievement of an AM part considering its qualification criteria.This will help future engineers, master students, PhD candidates and researchers from MENA region and Switzerland to develop skills in common processing equipment based on scientific concepts and to be immersed in an innovative technology allowing a flexible integration of the metal AM toward the industry4.0.

Equipe de recherche au sein de la HES-SO: Sallem Haifa

Partenaires académiques: Prof. Tarek Mabrouki, Université de Tunis El Manar – Ecole nationale d'ingénieurs de Tunis (ENIT)

Statut: En cours

Terminés

Contrôle in-situ par ondes électromagnétiques de l'intégrité des pièces imprimées par fusion laser sélective en utilisant le Machine Learning
AGP

Rôle: Requérant(e) principal(e)

Financement: HES-SO Rectorat

Description du projet : de révolutionner le secteur de fabrication. En comparaison avec les procédés conventionnels, cette technique repousse les limites en termes de précision, de design et de délais. Cependant, la SLM pose des défis liés aux phénomènes physiques complexes (thermiques, mécaniques métallurgiques, etc.) qui la régissent et qui ont une influence directe sur l'intégrité structurelle de la pièce (porosité, fissures, etc.). Dans la majorité des cas, un manque d'évaluation cohérente de la qualité des pièces fabriquées engendre une analyse post-processus coûteuse qui peut impacter la reproductibilité du procédé. Ceci constitue un frein technologique majeur en particulier dans les secteurs fortement réglementés comme l'aérospatiale et la fabrication de dispositifs médicaux. Afin de surmonter ce problème et mieux maîtriser le procédé SLM, il est nécessaire de développer des méthodes de contrôle adéquates capables de fournir une évaluation rapide et fiable de ces défauts. Aujourd'hui, les approches basées sur l'analyse des données remontées depuis les capteurs cyber-physiques avec les techniques de l'IA sont matures pour fournir une réponse à ce problème. Nous proposons de développer une méthode de contrôle qualité in-situ des pièces imprimées par SLM en temps et en conditions réels. Cela sera réalisé en mettant sur pied un algorithme d'apprentissage automatique entraîné pour la détection des défauts de type porosité ou fissures générés au cours de la fabrication à partir des données récoltées. L'algorithme sera capable de qualifier la qualité de la partie imprimée de la pièce dès la formation des défauts sans autant attendre la fin du processus. La qualification sera basée sur des paramètres et des critères comme par exemple la taille des défauts, leurs formes ou encore leur nombre et leur répartition par couche. L'inspection couche par couche des défauts générés sera faite in-situ en appliquant une technique électromagnétique (EM) d'essais non destructifs à l'aide capteurs développés par Sensima que nous intégrerons dans la machine SLM. L'algorithme sera entrainé par les données collectées avec ces capteurs lors des tests d'impression instrumentés des pièces dont on évaluera la qualité mécanique et opérationnelle par le biais des critères et des essais normés. L'originalité de ce projet réside dans l'approche directe et rapide de qualification du processus et de la qualité des pièces fabriquées par SLM. Actuellement la tomographie à rayons X, est la méthode standard utilisée dans l'industrie pour le contrôle de la porosité/fissures dans les pièces. Cette technique post-mortem permet l'analyse de la pièce après essais et s'avère coûteuse et longue. Le monitoring rapide in-situ que nous proposons dans le cadre de ce projet et qui est basé sur la technique EM, permettra une meilleure maîtrise de la SLM en temps réel et nous laissera donc la possibilité d'agir au cours de l'impression afin d'optimiser le processus. L'approche basée sur l'analyse en continue des données avec les nouvelles techniques de l'IA constitue également un défi de taille afin d'assurer un traitement suffisamment robuste et favorable à intégration industrielle pérenne et viable. Ce projet a un impact énorme et suscite beaucoup d'intérêt de plusieurs industriels comme Sensima. Les résultats renforceront les liens avec ces derniers et boosteront d'autres acquisitions de fonds.

Equipe de recherche au sein de la HES-SO: Ghorbel Hatem , Baer Edouard , Pralong Jean , Gauchat Loan , De Salis Emmanuel , Goffinet Edouard , Sallem Haifa , Cinna Adeline , Albertetti Fabrizio , Steudler Evelyne

Partenaires académiques: VS - Institut Systèmes industriels; Analyse de données

Durée du projet: 01.03.2021 - 28.02.2023

Montant global du projet: 241'500 CHF

Statut: Terminé

2024

A comparative study on microstructure and mechanical properties of 17-4PH processed by a laser powder bed fusion vs rolling process
Article scientifique ArODES

Thabet A. M. Sghaier, Habib Sahlaoui, Tarek Mabrouki, Haifa Sallem, Joël Rech

Progress in Additive Manufacturing,  2024

Lien vers la publication

Résumé:

This study provides a comprehensive benchmark comparison of microstructure, mechanical properties, and their evolution during subsequent heat treatment of 17-4PH Martensitic stainless steel (MSS) processed by laser powder bed fusion (LPBF) and its commercially rolled counterparts. The results reveal that LPBF samples exhibit a finer martensitic microstructure with presence of structural defects, pores, and some non-metallic inclusions randomly distributed at the grain boundaries and within the grains and an almost absence of austenite, compared to rolled samples. Additionally, after identical heat treatment, LPBF samples maintain a relatively unchanged microstructure while aging of rolled samples leads to a reduction in martensite in favor of austenite and Cu- and Si-rich precipitates. The LPBF samples demonstrate slightly elevated hardness (HV0.5 + 20%), mechanical strength (UTS + 15%) compared to rolled ones. Nevertheless, LPBF samples display a distinct behavior, characterized by abrupt fracture and reduced elongation at failure (El% max. 4% vs. 17.5%). Specifically, failure in LPBF samples is attributed to cleavage and cavities’ coalescence contrasting with the progressive failure mechanism observed in rolling ones driven by plasticity and damage evolution. Furthermore, the impact resistance of LPBF samples is notably weak (K max. 12.5 J/cm2 vs. 155 J/cm2), which is likely caused by macro- and microstructural defects generated by the LPBF process and the nucleation of harmful precipitates. The study proposes that the ductility of LPBF samples could be improved by implementing appropriate heat treatment and reducing defects through parameter optimization and by specific thermal cycle control during the LPBF process.

Optimizing novel multi-scaled simulation method for deviation analysis of generatively designed aileron bracket using laser powder bed fusion
Article scientifique ArODES

Yupiter H. P. Manurung, Thoufeili Taufek, Mohd Shahriman Adenana, Nur Izan Syahriah Hussein, Muhd Mufqi Aminallah, Fitri Iskandar Jamaludin, Loucas Papadakis, Haifa Sallem

The International Journal of Advanced Manufacturing Technology,  2024, 132, 11-12, 5855-5871

Lien vers la publication

Résumé:

This research is devoted to forecast the distortion of aileron brackets by means of generative design (GD) and multi-scaled numerical simulation comprising meso- and macro-scaled simulation based on thermomechanical method (TMM) and inherent strain method (ISM), respectively. The multi-scaled simulation began with TMM-based virtual calibration test (VCT) including mesh sensitivity and volume fraction analysis to identify the best meshing voxel size. In finding inherent strain tensors, optimization was implemented using pattern search algorithm referring to the minimum relative error. Further, macro-scaled simulation was implemented to estimate bracket distortion behavior by applying the inherent strain tensors in ISM. For experiment, the conventional aileron bracket shape was first improved by complying the internal rules of GD throughout the desired design space with respect to stress goal and weight reduction based on iterative material distribution. After obtaining the new generatively designed component, linear static analysis was implemented to improve the stress magnitude and surface smoothness level by mesh and material sculpting. Then, the component is manufactured using laser powder bed fusion with manual postprocessing of support structure followed by sand blasting. The finished aileron bracket was then measured using a 3D scanner GOM Atos Q. As conclusion, this novel multi-scaled simulation method based on GD, static stress, and virtual calibration test allows a forecast of an acceptable surface deviation within relative single point and mean errors up to 11% and 5% respectively. By neglecting the tedious and time-consuming procedure of real calibration, a huge time reduction for preparation up to a few days and for computation up to 35% compared to pure TMM can be achieved.

Optimizing novel multi-scaled simulation method for deviation analysis of generatively designed aileron bracket using laser powder bed fusion
Article scientifique

Sallem Haifa

DOI: 10.1007/s00170-024-13714-5, 2024

Résumé:

DOI: 10.1007/s00170-024-13714-5

A comparative study on microstructure and mechanical properties of 17-4PH processed by a laser powder bed fusion vs rolling process
Article scientifique

Sallem Haifa

Progress in Additive Manufacturing, 2024

Lien vers la publication

Résumé:

DOI: 10.1007/s40964-024-00837-0

Experimental Study of Morphological Defects Generated by SLM on 17-4PH Stainless Steel
Article scientifique

Sallem Haifa

Lecture Notes in Mechanical Engineering, 2024

Lien vers la publication

Résumé:

For cyclic loading applications and critical structural, the emergence of flaws in additively manufactured components is a key concern. This study highlighted the defects generated by selective laser melting (SLM) to the 17-4 PH stainless steel parts. The defects were quantified using an experimental study: Optical microscope and roughness meter to evaluate surface morphology (roughness and porosity) and microstructure. Tensile tests to evaluate the mechanical performance. The defects recorded take several forms, the most important of which are the rough and heterogeneous surface, prominent bumps on the outer surface in the shape of a hemisphere, cavities inside the spaced and adjacent parts of different shapes, internal cracks perpendicular to the printing direction, undissolved particles confined in the dissolving structure layers, brittle behaviour, non-resistant attractive and heterogeneous structure etc.

In-Situ Monitoring of Selective Laser Melted Ti–6Al–4V Parts Using Eddy Current Testing and Machine Learning
Article scientifique

Sallem Haifa, Ghorbel Hatem

Lecture Notes in Mechanical Engineering book series (LNME), 2024

Lien vers la publication

Résumé:

Metal laser powder bed fusion (L-BPF) technology is one of the most common and evolved additive manufacturing technologies to fabricate metal components. However, the control of defects generated during the SLM process remains an essential technological challenge for its implementation in production lines. In this work, based on the combination of eddy current testing (ECT) and machine learning (ML) approach, we propose a methodology allowing the in-situ monitoring of LPBF process porosity defects of Ti-6AL-4V components. The present empirical approach is achieved by setting up trained AI algorithms for the in-situ detection of porosity defects generated during the part fabrication. The algorithms are fed with data collected layer by layer using a specific experimental set up composed of an ECT system mounted on the machine recoater of the SLM machine. Comparison between predicted and experimental outcomes shows the effectiveness of the proposed framework which allows the prediction of porosity defects layer by layer with a mean absolute error (MAE) of 0.1% for CNN2D algorithm and 0.11% for LSTM one. The framework developed in this study can be effectively applied to quality control in additive manufacturing.

2023

Design and manufacture by SLM of a heat exchanger for SOFC
Article scientifique
Conception et fabrication par SLM d'un échangeur de chaleur pour piles SOFC

Joris Steve, Sallem Haifa, Aguiar E Silva Filipe, Peter Hugh Middleton

Advances In Additive Manufacturing (AIAM'2023), 2023

Résumé:

The objectives of this project are to design and manufacture, using 3D printing, a highly energy-efficient multi-channel hydrogen heat exchanger that will both improve the efficiency of the energy conversion chain in the fuel cells and high-temperature electrolysis (SOFC / SOEC) developed by Celectis Sàrl, and recover the excess heat emitted by these systems. The approach consists of designing a multi-channel heat exchanger with an architectural structure, then optimising its geometry by means of a CFD analysis of the flow rates, and finally producing a prototype in refractory alloy (INCONEL ® Alloy HX) by additive manufacturing using SLM (Selective Laser Melting). This manufacturing technique gives considerable design freedom (e.g. TPMS structure) and will enable high exchanger compactness to be achieved, thermal inertia to be reduced and exchanger designs to be adapted to environmental constraints. The printed heat exchanger will be characterised in the laboratory in order to assess its performance and tightness. This study will also help to understand and determine the limitations of the SLM process and the advantages of this manufacturing technology for this type of application.

Mechanical Properties of Additively Manufactured 17-4PH SS: Heat Treatment
Article scientifique

Sallem Haifa

Lecture Notes in Mechanical Engineering, 2023

Lien vers la publication

Résumé:

he effects of the thermal post-treatments on the mechanical properties of SLMed 17-4PH stainless steel are studied. Three thermal post-treatments are carried out: (E0) as received state, (E1 and E2) solution annealing treatment and (E3) aging treatment. Microhardness, impact-strength, and wear tests are carried out to determine the effect of treatment on the mechanical properties of SLMed 17-4PH. The results showed that the hardness of 17-4PH at the E0 state is a greater than the hardness of the powder. This hardness decreases slightly from 418 HV to 384 HV after the solution annealing treatment E2 and increase again after E3 ageing treatment to around 447HV. A hardness difference between the two manufacturing directions was also observed. This difference almost disappears after the E3 ageing treatment. The impact strength results show a huge drop in impact strength for 17-4PH obtained by SLM. An improvement in wear behaviour following heat treatment, especially in the case of ageing.

Nitinol Stents Printed by Selective Laser Melting
Article scientifique

Sallem Haifa

Lecture Notes in Mechanical Engineering book series (LNME), 2023

Lien vers la publication

Résumé:

Nitinol alloys stents have been printed by Selective Laser Melting from a gas atomized powder with a composition of 50.8 at% Ni. The energy density has been adapted to set the austenite finish temperature just below the human body temperature, therefore the stent diameter can be reduced by plastic strain at lower temperature and recover its former expanded shape after being inserted in the artery. Several mesh geometries have been mechanically analyzed by finite elements modeling to ensure that the local strain will not exceed superelastic reversible capacity of 4% while squeezing the stent diameter by a factor of 4. The stent surface has been treated by electropolishing to reduce its roughness to Ra < 0.02 mm. After polishing, some samples have been coated by a 50 nm thick TiO2 layer by Atomic Layer Deposition. Biocompatibility and hemocompatibility analysis demonstrated that the TiO2 coating significantly improved hemocompatibility. Nevertheless, uncoated stents are also biocompatible and hemocompatible according to ISO-10993–12 guidelines

Advances in Additive Manufacturing: Materials, Processes and Applications
Livre

Sallem Haifa

2023,  Suisse : Springer Nature,  246  p.

Lien vers la publication

Résumé:

This book reports on research and developments in the field of 3D printing, with a special emphasis on methods to analyse the products of additive manufacturing, and optimize different steps of the manufacturing process. Gathering selected contributions to the 2nd Advances in Additive Manufacturing Conference (AIAM' 2023), held on Mai 18-20, 2023, in Hammamet, Tunisia, this book covers a variety of topics, including: analysis of microstructure and material behavior, numerical simulation and model techniques for optimization of manufacturing processes, machine learning for quality control and automated monitoring, among others.  Offering a good balance of fundamental research and industrially relevant findings, this book provides researchers and professionals with a timely snapshot of and extensive information on current developments in the field and a source of inspiration for future research and collaboration.

Selective Laser Melting of Stainless-Steel: A Review of Process, Microstructure, Mechanical Properties and Post-Processing treatments
Article scientifique

Sallem Haifa

International Journal of Material Forming, 2023

Lien vers la publication

Résumé:

Additive Manufacturing (AM) using Selective Laser Melting (SLM) has gained significant prominence across various industries involved in stainless steel part manufacturing. Selective Laser Melting makes it possible to manufacture parts with very complex geometry and with remarkable mechanical and physicochemical properties by controlling the microstructure via the appropriate choice of process parameters. This study presents a comprehensive literature review aiming to provide the scientific and technical communities with an overview of existing knowledge and experimental data regarding the effects of Selective Laser Melting parameters and conditions on the microstructure and mechanical properties of stainless-steel parts. The objective is to highlight the impact of various factors, such as process parameters, building atmosphere, post-heat treatments and initial powder characteristics on phase transformation, porosity and microcracks formation, microstructure evolution and mechanical properties of SLMed stainless steels. Additionally, the integration of emerging Smart Additive Manufacturing (SAM) requires experimental databases, properties prediction and processing parameters optimization to enhance the entire process spanning from design to final product.

2023

Mechanical properties of additively manufactured 17-4PH SS :
Conférence ArODES
heat treatment

Thabet A. M. Sghaier, Habib Sahlaoui, Tarek Mabrouki, Haifa Sallem, Joël Rech

Advances in Additive Manufacturing: Materials, Processes and Applications ; Proceedings of the 2nd Advances in Additive Manufacturing Conference (AIAM'2023), 13-20 May 2023, Hammamet, Tunisia

Lien vers la conférence

Résumé:

The effects of the thermal post-treatments on the mechanical properties of SLMed 17-4PH stainless steel are studied. Three thermal post-treatments are carried out: (E0) as received state, (E1 and E2) solution annealing treatment and (E3) aging treatment. Microhardness, impact-strength, and wear tests are carried out to determine the effect of treatment on the mechanical properties of SLMed 17-4PH. The results showed that the hardness of 17-4PH at the E0 state is a greater than the hardness of the powder. This hardness decreases slightly from 418 HV to 384 HV after the solution annealing treatment E2 and increase again after E3 ageing treatment to around 447HV. A hardness difference between the two manufacturing directions was also observed. This difference almost disappears after the E3 ageing treatment. The impact strength results show a huge drop in impact strength for 17-4PH obtained by SLM. An improvement in wear behaviour following heat treatment, especially in the case of ageing.

Nitinol stents printed by selective laser melting
Conférence ArODES

Jean Pralong, Livia Lerjen, Bruno Schnyder, Oksana Banakh, Tony Journot, Haifa Sallem, Samuel Rey-Mermet

Advances in Additive Manufacturing: Materials, Processes and Applications ; Proceedings of the 2nd Advances in Additive Manufacturing Conference (AIAM'2023), 13-20 May 2023, Hammamet, Tunisia

Lien vers la conférence

Résumé:

Nitinol alloys stents have been printed by Selective Laser Melting from a gas atomized powder with a composition of 50.8 at% Ni. The energy density has been adapted to set the austenite finish temperature just below the human body temperature, therefore the stent diameter can be reduced by plastic strain at lower temperature and recover its former expanded shape after being inserted in the artery. Several mesh geometries have been mechanically analyzed by finite elements modeling to ensure that the local strain will not exceed superelastic reversible capacity of 4% while squeezing the stent diameter by a factor of 4. The stent surface has been treated by electropolishing to reduce its roughness to Ra < 0.02 mm. After polishing, some samples have been coated by a 50 nm thick TiO2 layer by Atomic Layer Deposition. Biocompatibility and hemocompatibility analysis demonstrated that the TiO2 coating significantly improved hemocompatibility. Nevertheless, uncoated stents are also biocompatible and hemocompatible according to ISO-10993–12 guidelines.

Experimental study of morphological defects generated by SLM on 17-4PH stainless steel
Conférence ArODES

Thabet A. M. Sghaier, Habib Sahlaoui, Haifa Sallem, Tarek Mabrouki, Joël Rech

Advances in Additive Manufacturing: Materials, Processes and Applications ; Proceedings of the 2nd Advances in Additive Manufacturing Conference (AIAM'2023), 18-20 May 2023, Hammamet, Tunisia

Lien vers la conférence

Résumé:

For cyclic loading applications and critical structural, the emergence of flaws in additively manufactured components is a key concern. This study highlighted the defects generated by selective laser melting (SLM) to the 17-4 PH stainless steel parts. The defects were quantified using an experimental study: Optical microscope and roughness meter to evaluate surface morphology (roughness and porosity) and microstructure. Tensile tests to evaluate the mechanical performance. The defects recorded take several forms, the most important of which are the rough and heterogeneous surface, prominent bumps on the outer surface in the shape of a hemisphere, cavities inside the spaced and adjacent parts of different shapes, internal cracks perpendicular to the printing direction, undissolved particles confined in the dissolving structure layers, brittle behaviour, non-resistant attractive and heterogeneous structure etc.

In-situ monitoring of selective laser melted Ti–6Al–4V parts using eddy current testing and machine learning
Conférence ArODES

Haifa Sallem, Hatem Ghorbel, Edouard Goffinet, Adeline Cinna, Jean Pralong, Jonatan Wicht, Bernard Revaz

Advances in Additive Manufacturing: Materials, Processes and Applications ; Proceedings of the 2nd Advances in Additive Manufacturing Conference (AIAM'2023), 13-20 May 2023, Hammamet, Tunisia

Lien vers la conférence

Résumé:

Metal laser powder bed fusion (L-BPF) technology is one of the most common and evolved additive manufacturing technologies to fabricate metal components. However, the control of defects generated during the SLM process remains an essential technological challenge for its implementation in production lines. In this work, based on the combination of eddy current testing (ECT) and machine learning (ML) approach, we propose a methodology allowing the in-situ monitoring of LPBF process porosity defects of Ti-6AL-4V components. The present empirical approach is achieved by setting up trained AI algorithms for the in-situ detection of porosity defects generated during the part fabrication. The algorithms are fed with data collected layer by layer using a specific experimental set up composed of an ECT system mounted on the machine recoater of the SLM machine. Comparison between predicted and experimental outcomes shows the effectiveness of the proposed framework which allows the prediction of porosity defects layer by layer with a mean absolute error (MAE) of 0.1% for CNN2D algorithm and 0.11% for LSTM one. The framework developed in this study can be effectively applied to quality control in additive manufacturing.

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