Integrating Machine Learning into Additive Manufacturing of Metallic Biomaterials: A Comprehensive Review by Shangyan Zhao, Yixuan Shi, Chengcong Huang, Xuan Li, Yuchen Lu, Yuzhi Wu, Yageng Li, Luning Wang

“…This review explores the application of ML in AM of metallic biomaterials, focusing on four key areas: (1) component design, where ML guides the optimization of multi-component alloys for improved mechanical and biological properties; (2) structural design, enabling the creation of intricate porous architectures tailored to specific functional requirements; (3) process control, facilitating real-time monitoring and adjustment of manufacturing parameters; and (4) parameter optimization, which reduces costs and enhances production efficiency. …”
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Modeling the compressive strength of concrete at different curing regimes using machine learning by Kennedy C. Onyelowe, Ahmed M. Ebid, Rosa Belén Ramos Jiménez, Angel Geovanny Lozano Guamán, Diego Ramiro Ñacato Estrella, Juan Carlos Cayán Martínez, Eduardo Francisco García Cabezas, Paul Awoyera

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Machine learning-based modelling and analysis of carbonation depth of recycled aggregate concrete by Xuyong Chen, Xuan Liu, Shukai Cheng, Xiaoya Bian, Xixuan Bai, Xin Zheng, Xiong Xu, Zhifeng Xu

“…This paper used machine learning to model the prediction of carbonation depth and the analysis of feature parameters for recycled aggregate concrete (RAC). …”
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Machine Learning Model for Early Detection of COVID-19 by Heart Rhythm Abnormalities by M. S. Mezhov, V. O. Kozitsin, Iu. D. Katser

“…The work aims at creating a mathematical model based on machine learning algorithms to automate the process of detecting covid abnormalities in the heart rhythm. …”
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Securing Electric Vehicle Performance: Machine Learning-Driven Fault Detection and Classification by Mahbub Ul Islam Khan, Md. Ilius Hasan Pathan, Mohammad Mominur Rahman, Md. Maidul Islam, Mohammed Arfat Raihan Chowdhury, Md. Shamim Anower, Md. Masud Rana, Md. Shafiul Alam, Mahmudul Hasan, Md. Shohanur Islam Sobuj, Md. Babul Islam, Veerpratap Meena, Francesco Benedetto

“…In addition, the superiority of the proposed fault detection and classification approaches using ML tools was assessed by comparing the detection and classification efficiency through some statistical performance parameter comparisons among the classifiers.…”
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Machine Learning Prediction of Airfoil Aerodynamic Performance Using Neural Network Ensembles by Diana-Andreea Sterpu, Daniel Măriuța, Grigore Cican, Ciprian-Marius Larco, Lucian-Teodor Grigorie

“…This finding highlights the often-overlooked impact of seed initialization on model performance and highlights the necessity of treating seed choice as an active design parameter in ML aerodynamic predictions.…”
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An Ensemble Learning-Based Predictive Parameterization Approach for Permanent Magnet Synchronous Machines by Sema Nur Ipek, Nur Bekiroglu, Murat Taskiran

“…Thus, the model’s capacity to accurately predict parameters and represent machine behavior has been revealed, and this method offers a feasible option for the effective use of resources, such as time and labor, in the estimation of PMSM parameters.…”
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Three-Dimensional Stability Lobe Construction for Face Milling of Thin-Wall Components with Position-Dependent Dynamics and Process Damping by Jinjie Jia, Lixue Chen, Wenyuan Song, Mingcong Huang

“…This work provides a systematic framework for optimizing machining parameters in thin-walled component manufacturing, offering improved accuracy in stability prediction compared to traditional two-dimensional SLD methods. …”
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Identification of Voltage Sag Source in Distribution Network Based on BAS-SVM by Haitao LIU, Xiaoyi YE, Ganyun LÜ, Huajun YUAN, Zongpu GENG

“…The penalty factor and kernel function parameters of SVM are optimized by BAS, and a BAS-SVM classifier is constructed. …”
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Enhance triangular fuzzy parametric framework for solid multi objective transportation problem with split decision variables by Vishwas Deep Joshi, Medha Sharma, Lenka Čepová, Huda Alsaud, Kanak Kalita

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Machine learning assisted zero-area pulse design in an open quantum system by Yi-Ye Li, Lian-Ao Wu, Zhao-Ming Wang

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Features of the dynamic properties of the working bodies of technological machines with inertial excitation of vibrations by Andrey V. Eliseev, Vladimir B. Kashuba, Nikita Z. Kinash, Sergey V. Eliseev

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Calculation of Mobile Machine Oscillations in view of Internal Processes in Pneumo- hydraulic Suspension by M. I. Zhilevich

“…It enables to analyze the rate of influence of design parameters of suspension cylinders and properties of a working body on output parameters of automobile oscillations and also to select rational values of these parameters. …”
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Implementing artificial neural networks and support vector machines to predict lost circulation by Ahmed K. Abbas, Najim A. Al-haideri, Ali A. Bashikh

“…The application of the machine learning methods could assist drilling engineers in modifying drilling parameters to minimize the likelihood of lost circulation. …”
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Automation of design works at development of machine drives with the use of functional semantic networks by Mironova M.N.

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A Modeling Study on Surface Roughness of Spinneret Mold Sections Machined By WEDM by Erdoğan Kanca, Volkan Cem Taşkın, Ali Günen

“…In this context, a newmodel was developed to predict the surface quality of spinneret mold sectionsmachined using WEDM by Analysis of variance. Machining parameters such asvoltage, current, pulse time and wire feed rate were used as independent inputvariables and surface roughness was used as dependent output parameters. …”
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Machine learning-assisted finite element modeling of additively manufactured meta-materials by Alexander Meynen, HMA Kolken, Michiel Mulier, Amir A. Zadpoor, Lennart Scheys

“…A critical condition for accurate simulation results is the identification of correct modelling parameters. This study proposes a machine learning-based strategy for identifying model parameters, including material properties and model boundary conditions, to enable accurate simulations of macro-scale mechanical behavior. …”
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Application of Modern Machine Diagnostic Systems to Improve Safety in the Underground Mining Process by Trzop Konrad, Kuric Ivan, Brodny Jarosław, Tutak Magdalena

“…Currently used machine diagnostic systems are based on very modern solutions based on the acquisition and recording of their operating parameters in real time. …”
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Comprehensive Experimental Analysis of Electrochemical Jet Machining (ECJM) for Advanced Material Processing by Shailesh Shirguppikar, Aleksandar Ašonja, Eleonora Desnica, Vaibhav Ganachari, Pankaj B. Gavali, Lakshmanan Selvarajan, Blaža Stojanović

“…This study examines the capabilities and optimisation of electrochemical jet machining (ECJM), a component of the electrochemical machining (ECM) production chain. …”
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Determination of the sound power of a machine inside an industrial room by the inversion method by Janusz PIECHOWICZ

“…The presented investigations constitute a part of the research program related to the application of inversion methods in the assessment of acoustic parameters of machines operating under industrial conditions, as well as to the comparative analysis of the hereby obtained results with the results obtainable by other methods of testing. …”
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