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Publications (10 of 21) Show all publications
Lattanzi, L., Jarfors, A. E. .. & Awe, S. A. (2024). On the possibility of using secondary alloys in the production of aluminum-based metal matrix composite. Crystals, 14(4), Article ID 333.
Open this publication in new window or tab >>On the possibility of using secondary alloys in the production of aluminum-based metal matrix composite
2024 (English)In: Crystals, ISSN 2073-4352, Vol. 14, no 4, article id 333Article in journal (Refereed) Published
Abstract [en]

Aluminum-based composites provide tribological performance and thermophysical properties that, combined with being lightweight, are suitable for their application in automotive brake discs. Aluminum alloys allow the use of secondary materials to produce composites, with the drawback of several elements, impurities, and oxides that can harm the mechanical and thermophysical properties. This preliminary study explored the mechanical and thermophysical performance of a composite material produced with a secondary matrix alloy. Overall, the results are promising, with a minimal decrease in mechanical and thermophysical properties despite clustered silicon carbide particles in the composite with the secondary matrix. The challenges in effectively dispersing carbides in the melt seem linked to aluminum oxides, and future microstructural investigations will aim to clarify this aspect.

Place, publisher, year, edition, pages
MDPI, 2024
Keywords
MMC, recycled alloys, aluminum, composite
National Category
Metallurgy and Metallic Materials
Identifiers
urn:nbn:se:hj:diva-63912 (URN)10.3390/cryst14040333 (DOI)001220266900001 ()2-s2.0-85191396564 (Scopus ID)GOA;;944342 (Local ID)GOA;;944342 (Archive number)GOA;;944342 (OAI)
Projects
MaReAl project
Funder
Vinnova, 2022-00828
Available from: 2024-04-02 Created: 2024-04-02 Last updated: 2024-05-27Bibliographically approved
Li, Z., Tan, H., Jarfors, A. E. .., Jansson, P. & Lattanzi, L. (2024). Smart-Cast: An AI-Based System for Semisolid Casting Process Control. Paper presented at 5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023 Lisbon 22 November 2023 through 24 November 2023. Procedia Computer Science, 232, 2440-2447
Open this publication in new window or tab >>Smart-Cast: An AI-Based System for Semisolid Casting Process Control
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2024 (English)In: Procedia Computer Science, E-ISSN 1877-0509, Vol. 232, p. 2440-2447Article in journal (Refereed) Published
Abstract [en]

To satisfy the rising demand for higher product quality and giga-casting requirements, the casting process is undergoing significant changes. However, current control methods rely significantly on human expertise and experience, making process availability and stability difficult to ensure. The semisolid casting process is more complicated than conventional liquid casting due to the additional casting parameters incorporated during the slurry preparation, which can have an effect on the quality of the final product. Therefore, an efficient tool is required to simplify the complete process of semisolid casting. The introduction of an AI system to aid in the supervision of the casting manufacturing procedure is one potential solution. This paper introduces a new casting system named”Smart-Cast” developed for this specific purpose. The paper describes the functions of the system and its current development process. Using an AI system as an assistant can help to achieve the goal of enhancing the efficacy of casting process control, and it can also help foundries step into the Industry 4.0 era.

Place, publisher, year, edition, pages
Elsevier, 2024
Keywords
AI system, Industry 4.0, Process control, Semisolid casting, Smart manufacturing system
National Category
Materials Engineering
Identifiers
urn:nbn:se:hj:diva-64007 (URN)10.1016/j.procs.2024.02.063 (DOI)2-s2.0-85189767838 (Scopus ID)HOA;;947156 (Local ID)HOA;;947156 (Archive number)HOA;;947156 (OAI)
Conference
5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023 Lisbon 22 November 2023 through 24 November 2023
Available from: 2024-04-15 Created: 2024-04-15 Last updated: 2024-04-15Bibliographically approved
Lattanzi, L. & Awe, S. A. (2024). Thermophysical properties of Al-based metal matrix composites suitable for automotive brake discs. Journal of Alloys and Metallurgical Systems, 5, Article ID 100059.
Open this publication in new window or tab >>Thermophysical properties of Al-based metal matrix composites suitable for automotive brake discs
2024 (English)In: Journal of Alloys and Metallurgical Systems, E-ISSN 2949-9178, Vol. 5, article id 100059Article in journal (Refereed) Published
Abstract [en]

The present work investigates the effects of Ni, Cu, La, and Ce on the thermophysical properties of aluminium-based metal matrix composites. Transition metals and rare-earth elements were added to improve the mechanical performance of the material to above 420 °C, which is the maximum operating temperature of the reference material. In contrast, the addition of alloying elements results in the formation of intermetallic phases, Al3Ni and Al11(La,Ce)3, which, in turn, affect the thermal and physical properties of the base alloy. The goal is to apply the improved composites to automotive brake discs. The addition of alloying elements decreased the thermal conductivity by 20% and increased the stiffness by 90% at temperatures up to 470 °C. When stiffness and thermal conductivity are critical requirements, the addition of these alloying elements represents a valid solution.

Place, publisher, year, edition, pages
Elsevier, 2024
Keywords
Metal–matrix composites (MMCs), Thermal properties, Characterisation, Material selection, Casting
National Category
Metallurgy and Metallic Materials
Identifiers
urn:nbn:se:hj:diva-63502 (URN)10.1016/j.jalmes.2024.100059 (DOI)2-s2.0-85186907166 (Scopus ID)GOA;;936293 (Local ID)GOA;;936293 (Archive number)GOA;;936293 (OAI)
Projects
Properties and formability of Al-SiCp MMCs (ProForAl)
Funder
Knowledge Foundation, 20200217
Available from: 2024-02-07 Created: 2024-02-07 Last updated: 2024-03-20Bibliographically approved
Lattanzi, L., Awe, S. A., Jansson, P., Rudenstam, C., Westergård, R. & Jarfors, A. E. .. (2023). Aluminium matrix composites for lightweight components. In: : . Paper presented at 17th European Congress and Exhibition on Advance Materials and Processes, FEMS EUROMAT 2023, 03-07 September 2023, Germany.
Open this publication in new window or tab >>Aluminium matrix composites for lightweight components
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2023 (English)Conference paper, Oral presentation only (Refereed)
National Category
Metallurgy and Metallic Materials
Identifiers
urn:nbn:se:hj:diva-63233 (URN)
Conference
17th European Congress and Exhibition on Advance Materials and Processes, FEMS EUROMAT 2023, 03-07 September 2023, Germany
Available from: 2024-01-09 Created: 2024-01-09 Last updated: 2024-01-09Bibliographically approved
Li, Z., Tan, H., Jarfors, A. E. .., Lattanzi, L. & Jansson, P. (2023). Enhancing Rheocasting Process Control with AI-based Systems. In: : . Paper presented at The 35th Swedish Artificial Intelligence Society (SAIS'23) annual workshop.
Open this publication in new window or tab >>Enhancing Rheocasting Process Control with AI-based Systems
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2023 (English)Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Semisolid casting has emerged as an attractivealternative to conventional casting methods due to its potentialto yield superior mechanical properties, reduce environmentalpollution, and decrease production costs. However, optimizingprocess parameters and controlling the casting process remainschallenging. Process control largely relies on human expertise,associated with significant time and cost expenditures. Inresponse, this study presents a third-circle research project toinvestigate the correlation between the casting process and thesolidification process. The study proposes leveraging AI technologyto digitize the entire process control, thereby increasing thereliability and stability of cast products’ quality. The researchwill focus on understanding the key factors influencing thecasting process and developing an AI-based decision supportsystem to aid in process parameter selection and optimization.The outcomes of this study are expected to contribute to thedevelopment of more reliable and efficient semisolid castingprocesses.

Keywords
semisolid casting, casting process control, AI application
National Category
Metallurgy and Metallic Materials
Identifiers
urn:nbn:se:hj:diva-62235 (URN)
Conference
The 35th Swedish Artificial Intelligence Society (SAIS'23) annual workshop
Funder
Knowledge Foundation, 2020-0044.
Available from: 2023-08-22 Created: 2023-08-22 Last updated: 2023-08-22
Du, A., Lattanzi, L., Jarfors, A. E. .., Zheng, J., Wang, K. & Yu, G. (2023). On the efficient particle dispersion and transfer in the fabrication of SiC-particle-reinforced aluminum matrix composite. Crystals, 13(12), Article ID 1621.
Open this publication in new window or tab >>On the efficient particle dispersion and transfer in the fabrication of SiC-particle-reinforced aluminum matrix composite
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2023 (English)In: Crystals, ISSN 2073-4352, Vol. 13, no 12, article id 1621Article in journal (Refereed) Published
Abstract [en]

Lightweight SiC-particle-reinforced aluminum composites have the potential to replace cast iron in brake discs, especially for electric vehicles. This study investigates the effect of SiC particle size and matrix alloy composition on the resulting transfer efficiency and particle distribution. The performance of a specially designed stirring head was studied using a water model, and the stirring head conditions were assessed to understand the particle transfer and dispersion mechanisms in the molten aluminum. The standard practice of thermal pre-treatment promotes the wetting of the reinforcing particles and commonly causes clustering before the addition to the melt. This early clustering affects the transfer efficiency and particle dispersion, where their interaction with the melt top-surface oxide skin plays an important role. In addition, the transfer efficiency was linked to the particle size and the chemical composition of the matrix alloy. Smaller particles aggravated the degree of clustering, and the addition of rare earth elements as alloying elements in the matrix alloy affected the particle dispersion. The stirring parameters should be selected to ensure cluster disruption when the carbides are added to the melt.

Place, publisher, year, edition, pages
MDPI, 2023
Keywords
casting, metal matrix composites, microstructure, simulation
National Category
Metallurgy and Metallic Materials
Identifiers
urn:nbn:se:hj:diva-63254 (URN)10.3390/cryst13121621 (DOI)001131247100001 ()2-s2.0-85180687350 (Scopus ID)GOA;intsam;926091 (Local ID)GOA;intsam;926091 (Archive number)GOA;intsam;926091 (OAI)
Funder
Knowledge Foundation, ProForAl-20201702
Available from: 2024-01-09 Created: 2024-01-09 Last updated: 2024-03-26Bibliographically approved
Li, Z., Tan, H., Lattanzi, L., Jarfors, A. E. .. & Jansson, P. (2023). On the Possibility of Replacing Scheil-Gulliver Modeling with Machine Learning and Neural Network Models. In: A. Pola, M. Tocci and A. Rassili (Ed.), Solid State Phenomena: (pp. 157-163). Trans Tech Publications, 347
Open this publication in new window or tab >>On the Possibility of Replacing Scheil-Gulliver Modeling with Machine Learning and Neural Network Models
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2023 (English)In: Solid State Phenomena / [ed] A. Pola, M. Tocci and A. Rassili, Trans Tech Publications, 2023, Vol. 347, p. 157-163Chapter in book (Refereed)
Abstract [en]

Resource-efficient manufacturing is a foundation for sustainable and circular manufacturing. Semi-solid processing typically reduces material loss and improves productivity but generally requires a better understanding and control of the solidification of the cast material. Thermal analysis is commonly used in high-pressure die casting (HPDC) processes to determine casting process parameters, such as liquidus and solidus temperatures. However, this method is inadequate for semi-solid casting processes because the eutectic temperature is also a crucial parameter for successful semi-solid casting. This study explores the feasibility of using machine learning and artificial neural networks to predict fundamental values in Al-Si alloy casting. The Thermo-Calc 2022 software Scheil-Gulliver calculation function was used to generate the training and the test datasets, which included features such as melting temperature, alpha aluminium solidification temperature, eutectic temperature, and the solid fraction amounts at eutectic temperature. The results show that both models have a symmetric mean absolute percentage error (SMAPE) of less than 2 % with temperature prediction, with the machine learning model achieving a better accuracy of less than 1 %. A case study comparing practical measurements with prediction results is also discussed, demonstrating the potential of AI methods for predicting semi-solid casting processes.

Place, publisher, year, edition, pages
Trans Tech Publications, 2023
Series
Solid State Phenomena, ISSN 1012-0394, E-ISSN 1662-9779 ; 347
Keywords
Aluminium; Semi-solid casting, Machine learning, Neural network, Segregation, Solidification, Training data collection
National Category
Materials Engineering
Identifiers
urn:nbn:se:hj:diva-62495 (URN)10.4028/p-m0SusZ (DOI)2-s2.0-85170515196 (Scopus ID)
Funder
Knowledge Foundation
Available from: 2023-09-19 Created: 2023-09-19 Last updated: 2024-02-09Bibliographically approved
Li, Z., Tan, H., Lattanzi, L., Jarfors, A. E. .. & Jansson, P. (2023). On the possibility of replacing Scheil-Gulliver modelling with machine learning and neural network models. In: : . Paper presented at 17th International Conference on Semi Solid Processing of Alloys and Composites (S2P2023), 6-8 September 2023, Brescia, Italy.
Open this publication in new window or tab >>On the possibility of replacing Scheil-Gulliver modelling with machine learning and neural network models
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2023 (English)Conference paper, Oral presentation only (Refereed)
National Category
Materials Engineering Computer Sciences
Identifiers
urn:nbn:se:hj:diva-63240 (URN)
Conference
17th International Conference on Semi Solid Processing of Alloys and Composites (S2P2023), 6-8 September 2023, Brescia, Italy
Available from: 2024-01-09 Created: 2024-01-09 Last updated: 2024-01-09Bibliographically approved
Du, A., Lattanzi, L., Jarfors, A. E. .., Zheng, J., Wang, K. & Yu, G. (2023). Role of matrix alloy, reinforcement size and fraction in the sliding wear behaviour of Al-SiCp MMCs against brake pad material. Wear, 530-531, Article ID 204969.
Open this publication in new window or tab >>Role of matrix alloy, reinforcement size and fraction in the sliding wear behaviour of Al-SiCp MMCs against brake pad material
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2023 (English)In: Wear, ISSN 0043-1648, E-ISSN 1873-2577, Vol. 530-531, article id 204969Article in journal (Refereed) Published
Abstract [en]

Aluminium metal matrix composites were produced by a newly developed stirring device for stir casting with different matrix alloys, SiC particle fractions and sizes to investigate these parameters' influence on the materials' wear performance. The wear performance of the composites was evaluated with dry sliding pin-on-plate tests against a high-speed train brake pad, and the study of wear surfaces was completed by electron microscopy. The formation of an iron-based tribolayer during wear protected the metal matrix composite from further wear damage. The composite reinforced with 19% SiC particles sized 32 μm showed an increasing coefficient of friction during wear, and the wear surface showed traces of third body wear. The rare earth and transition metal added to the matrix alloy increased the hardness of the composite, and the intermetallic phases reduced the development of the Fe-based tribolayer. The composites with small SiC particles presented the Fe transfer on the exposed aluminium surface, with a lower wear rate and friction coefficient than other composites. The direct comparison of composites produced with different sizes of SiC particles highlighted that the relationship between the wear rate and the coefficient of friction of the composites and the brake pad showed a linear trend.

Place, publisher, year, edition, pages
Elsevier, 2023
Keywords
Brakes, Electron microscopy, Metal-matrix composite, Sliding wear, Wear testing
National Category
Materials Engineering
Identifiers
urn:nbn:se:hj:diva-61328 (URN)10.1016/j.wear.2023.204969 (DOI)001025006600001 ()2-s2.0-85161592577 (Scopus ID)HOA;intsam;886506 (Local ID)HOA;intsam;886506 (Archive number)HOA;intsam;886506 (OAI)
Available from: 2023-06-20 Created: 2023-06-20 Last updated: 2023-08-18Bibliographically approved
Lattanzi, L., Awe, S., Jansson, P., Westergård, R., Sjögren, T. & Jarfors, A. E. .. (2023). The possibility of using secondary alloys for producing aluminium matrix composite components. In: : . Paper presented at 5th International Conference on Light Materials – Science and Technology (LightMAT 2023), 21–23 June 2023, Trondheim, Norway.
Open this publication in new window or tab >>The possibility of using secondary alloys for producing aluminium matrix composite components
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2023 (English)Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Aluminium-based metal matrix composites (MMCs) are valid candidates to substitute cast iron in the production of automobile brake discs. These materials provide good tribological performance and suitable thermophysical properties combined in a lightweight solution. The two main challenges lie in the high-temperature mechanical properties and the recyclability of the composite at the product’s end-of-life. Aluminium gives the opportunity of using secondary alloys in the production of these MMCs. The drawback is that secondary aluminium alloys usually include several impurities and oxides that can harm mechanical and thermophysical properties. The present study focuses on characterising Al-Si-based MMCs reinforced with 20 wt.% of SiC particles. The composites are produced by squeeze casting using 100 % of secondary alloy for the matrix and are compared to the current solution developed for light brake discs. The critical material properties for brake discs are good thermal conductivity and suitable coefficient of friction. The microstructure of the MMC produced with secondary alloy presented a higher number of clustered SiC particles, probably related to the presence of oxide films that wrap the carbides and hinder their dispersion in the melt. The presence of oxide-related porosities affected the thermal conductivity of the composites produced with secondary alloys, with a reduction in thermal conductivity of 15 % from 147 to 125 W/m*K at room temperature. The reduction was maintained with increasing temperature up to 500 °C. The wear performance was tested at room temperature with a pin-on-plate tribometer against the brake pad material. The coefficient of friction did not change with the presence of the recycled matrix alloy, reaching a maximum value of 0.2 over 4 hours of testing. The wear surface on the MMC presents a tribo-layer that develops at the beginning of the wear test and maintains a stable coefficient of friction over time.

National Category
Metallurgy and Metallic Materials
Identifiers
urn:nbn:se:hj:diva-63281 (URN)
Conference
5th International Conference on Light Materials – Science and Technology (LightMAT 2023), 21–23 June 2023, Trondheim, Norway
Available from: 2024-01-10 Created: 2024-01-10 Last updated: 2024-01-23Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-2361-8810

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