https://journals.prz.edu.pl/amme/issue/feedAdvances in Mechanical and Materials Engineering2025-02-17T07:46:16+00:00Tomasz TRZEPIECIŃSKI,amme@prz.edu.plOpen Journal Systems<div align="justify"> <p><strong>Advances in Mechanical and Materials Engineering</strong> is a continuation of „Scientific Letters of Rzeszów University of Technology. Mechanics” published in 1983-2022 and the research publications under the name „Dissertations – The Works of Mechanical Engineering Institute”, which were published from 1973 through 1982. Topics of interest include, but are not limited to mechanical engineering, materials engineering, structural engineering, automation and robotics, thermodynamics and metallurgy.</p> <p><a href="https://portal.issn.org/resource/ISSN/2956-4794"><strong>e-ISSN 2956-4794</strong></a></p> </div>https://journals.prz.edu.pl/amme/article/view/1853The Use of Artificial Neural Networks to the Analysis of Lubricating Performance of Vegetable Oils for Plastic Working Applications2025-01-27T15:09:06+00:00Marek Szewczykm.szewczyk@prz.edu.plMarwan T. Mezhermarwantahir90@gmail.comTanya Abdulsattar Jabertanya.galxy@mtu.edu.iq<p>Sheet metal forming is the basic method of processing of deep-drawing quality steel sheets used in the automotive industry. A properly planned technological process of forming should include guidelines for friction conditions, or rather the coefficient of friction. Determination of the coefficient of friction is carried out using various methods. In this article, the strip drawing test was used to analyse the friction of low-carbon DC04 steel sheets. The tests were carried out at different contact pressures and with the use of different vegetable-oil based biolubricants. The most common edible and non-edible oils were selected for the tests: sunflower, rape-seed, moringa and karanja. The analysis of the experimental results was carried out using multilayer artificial neural networks (ANNs). Different learning algorithms and different transfer functions were considered in ANNs. Based on the analysis of experimental data, it was noticed that the coefficient of friction decreased with increasing contact pressure. The lowest values of the coefficient of friction, in the entire range of analysed pressures, were observed during lubrication with karanja oil. It was also found that Levenberg-Marquardt training algorithm with log-sigmoid transfer function provided the lowest values of performance errors and at the same time the highest value of the coefficient of determination R2 = 0.94719.</p>2025-01-27T00:00:00+00:00Copyright (c) 2025 Advances in Mechanical and Materials Engineeringhttps://journals.prz.edu.pl/amme/article/view/1854A Review of Machine Learning Applications in Aviation Engineering2025-02-07T11:23:02+00:00Parankush Koulpkoul2.iit@gmail.com<p>This review paper investigates how machine learning (ML) has transformed multiple facets of aviation engineering. The work demonstrates substantial progress in flight operations and air traffic management (ATM) optimization through frameworks such as Reinforcement-Learning-Informed Prescriptive Analytics (RLIPA) and deep reinforcement learning (DRL) techniques applied to conflict resolution. The study highlights how ML contributes to operational efficiency through faster computational processes and better decision-making abilities for those who control air traffic. The paper examines how leading firms such as SpaceX and Raytheon use ML technology to enhance manufacturing processes, including predictive maintenance (PdM) and autonomous systems development. The paper discusses ML implementation obstacles, including model interpretability, and highlights further research requirements for adapting to real-world issues such as changing traffic volumes and weather variations. Overall, the study demonstrates how ML technology can transform aviation engineering through enhancements in safety standards as well as operational and process efficiency.</p>2025-02-07T08:50:09+00:00Copyright (c) 2025 Advances in Mechanical and Materials Engineeringhttps://journals.prz.edu.pl/amme/article/view/1829Concept of 3D Printed Powder Feeder for Thermal Spray Process – A Case Study2025-02-07T10:09:18+00:00Patryk Kamudakamuda.pat97@gmail.comMarek Góralmgoral@prz.edu.plKamil Ochałkochal@prz.edu.plDamian Nabeldamiannabel@prz.edu.plTadeusz Kubaszektkubaszek@prz.edu.pl<p>Thermal spraying is playing an increasingly important role among coating manufacturing methods because of its properties and ecology. An obstacle to their development is the price of the available equipment used in this process. The article presents the concept of making individual elements of a powder feeder by 3D printing. The designs are equipped with a volumetric feeding system using a disk driven by an electric motor and a worm gearbox. The individual elements of the feeder were designed and based on the drawings; they were made using several types of 3D printers. The design and fabrication were limited to the use of a small number of parts made of metal including little machining. In the following part, a prototype of the feeder was made and tested. It was shown to have correct characteristics of its operation and, in particular, correct linear characteristics of powder feed rate from disk speed similarly to commercial devices. Tests of the made feeder indicate the possibility of its use in thermal spraying systems.</p>2025-02-07T09:57:23+00:00Copyright (c) 2025 Advances in Mechanical and Materials Engineeringhttps://journals.prz.edu.pl/amme/article/view/1876Study on Mechanical Properties of Polyurethane Elastomers in Different Strength Tests2025-02-17T07:46:16+00:00Krzysztof Żabakrzyzaba@agh.edu.plMaciej Balcerzakbalcerzak@agh.edu.plŁukasz Kuczeklukasz.kuczek@agh.edu.pl<p class="a-abstract-EN" style="margin: 0cm 1.0cm .0001pt 0cm;"><span class="rynqvb"><span lang="EN-US" style="font-size: 12.0pt;">Elastomeric materials are used in the methods of plastic forming of sheets made of difficult-to-deform materials.</span></span> <span class="rynqvb"><span lang="EN-US" style="font-size: 12.0pt;">This article presents the results of strength tests of selected elastomeric materials intended for sheet metal stamping.</span></span> <span class="rynqvb"><span lang="EN-US" style="font-size: 12.0pt;">Polyurethane elastomers with a hardness of 50, 70 and 90 Sh A were used for the tests.</span></span> <span class="rynqvb"><span lang="EN-US" style="font-size: 12.0pt;">The behaviour of the materials was determined in a simple compression test, a volumetric compression test and a uniaxial tensile test. In the case of the simple compression test, the values of the maximum force for a set punch travel of 3 mm were 1400 N, 2250 N and 4950 N for samples with hardnesses of 50, 70 and 90 Sh A, respectively. In a volumetric compression test, the maximum compressive force for a sample with a hardness of 90 Sh A was more than twice lower than the compressive force of samples with a hardness of 50 and 70 Sh A.</span></span> <span class="rynqvb"><span lang="EN-US" style="font-size: 12.0pt;">In the tensile tests, the values of the obtained strains ranged from about 750% for the sample with a hardness of 50 Sh A to about 1350% for the sample with a hardness of 90 Sh A.</span></span></p>2025-02-17T07:42:52+00:00Copyright (c) 2025 Advances in Mechanical and Materials Engineering