Papers

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. DOI: … 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. 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 solve increasingly … 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. DOI: https://doi.org/10.7494/cmms.2025.1.1014 Abstract: High entropy alloys, characterized by their near-equimolar … 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. 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 approaches exploiting their limitations, including smartphone-based ML … 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. 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 is an … 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. DOI: https://doi.org/10.7494/cmms.2024.2.0834 Abstract: Additive manufacturing (AM) has emerged as … 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. 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 direct indicator … Read more

An analytical model for the tool center point placement in Robotic Roller Forming

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An analytical model for the tool center point placement in Robotic Roller Forming Thomas Stewens1,2, Yi Liu1, Ling Wang3, Junying Min1 1School of Mechanical Engineering, Tongji University, Shanghai 201804, China.2Technical University of Darmstadt, Darmstadt, Germany.3Siemens DISW, Shanghai, China. DOI: https://doi.org/10.7494/cmms.2024.2.0838 Abstract: Robotic roller forming (RRF) is a novel process using an articulated robotic manipulator that … Read more