Papers

Design and implementation of a digital infrastructure for autonomous open-die forging

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Design and implementation of a digital infrastructure for autonomous open-die forging Roy Rechenberg1*, Grzegorz Korpala1, Magdalena Jabłońska2, Marek Wojtaszek3, Krystian Zyguła3, Marek Tkocz4, Iwona Bednarczyk4, Karolina Kowalczyk5, Ulrich Prahl1 1TU Bergakademie Freiberg, Akademiestraße 6, 09599 Freiberg, Germany. 2Lukasiewicz Research Network – Institute of Non-Ferrous Metals, ul. Sowińskiego 5, 44-100 Gliwice, Poland. 3AGH University of Krakow, … Read more

Statistical evaluation of the measurement of residual stresses in the surface layer of CP1000 steel sheets using the magnetic Barkhausen noise and X-ray methods

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Statistical evaluation of the measurement of residual stresses in the surface layer of CP1000 steel sheets using the magnetic Barkhausen noise and X-ray methods Janusz Kliś1, Rafał Nawrat1, Jakub Olbrych1, Michał Węgrzyniak1, Damian Szydło1, Grzegorz Toczek1, Liwia Sozańska-Jędrasik2* 1ArcelorMittal Distribution Solution Poland sp. z o.o. 2Łukasiewicz Research Network – Upper Silesian Institute of Technology. *corresponding … Read more

Review of XAI methods for application in heavy industry

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Review of XAI methods for application in heavy industry Wojciech Jędrysik*, Piotr Hajder, Łukasz Rauch AGH University of Krakow, Department of Applied Computer Science and Modelling, Krakow, Poland. *corresponding author DOI: https://doi.org/10.7494/cmms.2025.1.1013 Abstract: In recent years, considerable progress has been made in the field of artificial intelligence and machine learning. This progress allows us to … Read more

Development of a constitutive material model of Mo-Mn-Fe-Co-Ni high entropy alloy through a structured two-phase inverse analysis

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Development of a constitutive material model of Mo-Mn-Fe-Co-Ni high entropy alloy through a structured two-phase inverse analysis Aitor Orbea Larrañaga1*, Joseba Mendiguren Olaeta1, Kamil Cichocki2, Lukasz Madej2 1Mondragon Unibertsitatea, Loramendi 4, 20500 Mondragon, Spain. 2AGH University of Krakow, al. A. Mickiewicza 30, 30-019, Krakow, Poland. *corresponding author DOI: https://doi.org/10.7494/cmms.2025.1.1014 Abstract: High entropy alloys, characterized by … Read more

Mechanical behavior of adhesive joints: A review on modeling techniques

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Mechanical behavior of adhesive joints: A review on modeling techniques Maximilian Ries Institute of Applied Mechanics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany. DOI: https://doi.org/10.7494/cmms.2024.4.1010 Abstract: In the pursuit of lighter designs, many industries are shifting from conventional fasteners to adhesive joints, which offer a better strength-to-weight ratio and facilitate the use of fiber-reinforced polymers. However, modeling adhesive joints … Read more

Detecting dents in car bodies using machine learning and structured light projection

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Detecting dents in car bodies using machine learning and structured light projection Izabela Potasz*, Sławomir Potasz, Michał Laska VUMO sp. z o.o. Skotnicka 252A, 30-394 Kraków, Poland *corresponding author DOI: https://doi.org/10.7494/cmms.2024.3.0836 Abstract: This article discusses feasible methods for detecting dents in car bodies caused by transportation damage, commuting collisions, and hail. The authors review existing … Read more

An evaluation of the capabilities of image-based metal component defect recognition with deep learning techniques

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An evaluation of the capabilities of image-based metal component defect recognition with deep learning techniques Michał P. Wójcik*, Kacper Pawlikowski, Łukasz Madej AGH University of Krakow, Mickiewicza 30, 30-059 Krakow, Poland. *corresponding author DOI: https://doi.org/10.7494/cmms.2024.3.0839 Abstract: In the era of Industry 4.0, deploying highly specialised machine learning models trained on unique and often scarce datasets … Read more

Shear strength estimation of a FRP-strengthened RC beam: A comparison between an artificial neural network and guideline equations

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Shear strength estimation of a FRP-strengthened RC beam: A comparison between an artificial neural network and guideline equations Hamid Nezaminia Department of Civil Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran. DOI: https://doi.org/10.7494/cmms.2024.3.0830 Abstract: In recent years, several experimental tests have been conducted on the shear strengthening of reinforced concrete (RC) beams strengthened by … Read more

Modeling the thermo-mechanical response and phase changes in metallic additive manufacturing (MAM) processes using a dissipative phase-field model

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Modeling the thermo-mechanical response and phase changes in metallic additive manufacturing (MAM) processes using a dissipative phase-field model Roya Darabi*, Erfan Azinpour, Ana Reis, Jose Cesar de Sa Faculty of Engineering of University of Porto (FEUP), FEUP campus, Rua Dr. Roberto Frias, 400, Porto, 4200-465, Portugal. *corresponding author DOI: https://doi.org/10.7494/cmms.2024.2.0834 Abstract: Additive manufacturing (AM) has … Read more

A universal convolutional neural network for the pixel-level detection and monitoring of weld beads

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A universal convolutional neural network for the pixel-level detection and monitoring of weld beads Zhuo Wang, Metin Kayitmazbatir, Mihaela Banu* Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109, USA. *corresponding author DOI: https://doi.org/10.7494/cmms.2024.2.0835 Abstract: In weld-based manufacturing processes such as welding and metal deposition additive manufacturing (AM), the weld bead is a … Read more