Koncepcja przeprowadzenia próby skręcania elementów ze stali 20CrNiMo2-2 wytworzonych z zastosowaniem technik przyrostowych

In recent years, additive manufacturing (AM) technologies, have been one of the fastest developing methods of production of various components. As far as building material is concerned, they allow for using not only polymers, but also composites or metals. Products fabricated using said technologies are used in various areas of industries, for instance in medicine, architecture, entertainment, and in particular in the construction of parts and components of machinery and equipment. To recognize and determine the products’ strength properties in a more comprehensive manner, 3D printing products used in mechanical applications are subject to various tests, e.g. static tensile test. This paper contains research about static torsion test on cylindrical samples made of high grade 20CrNiMo2-2 steel using the selective laser melting (SLM). Such an approach allowed to observe the material behaviour and to determine specific values of strength properties, such as the maximum tangential stresses in the material and bulk modulus of elasticity (shear modulus). The determination of such parameters allowed to compare them with the results of the tests carried out on components manufactured using other methods (e.g. a cold drawn solid bar sample).W ostatnich latach przyrostowe techniki wytwarzania, a w szczególności druk 3D, są jednymi z najszybciej rozwijających się metod produkcji różnych elementów. Pozwalają one na wykorzystanie jako materiału budulcowego nie tylko polimerów, ale również kompozytów czy metali. Produkty powstałe z zastosowaniem opisywanych technik znajdują zastosowanie w różnych dziedzinach życia, dla przykładu w medycynie, architekturze, rozrywce a w szczególności w budowie części i elementów maszyn i urządzeń. Aby lepiej poznać i określić właściwości wytrzymałościowe wyrobów, kluczowe w przypadku wykorzystania produktów druku 3D w dziedzinie mechanicznej, poddaje się je wielu badaniom np. statycznej próbie rozciągania. Rozważanym pomysłem jest przeprowadzenie statycznej próby skręcania walcowych próbek wytworzonych z wysoko-gatunkowej stali 20CrNiMo2-2 z zastosowaniem techniki selektywnego spiekania proszku metalu (SLM). Pozwoli ono na obserwację zachowania się materiału oraz wyznaczenie konkretnych wartości właściwości wytrzymałościowych, takich jak maksymalne naprężenia styczne występujące w materiale oraz moduł sprężystości poprzecznej (modułu Kirchoffa). Dzięki ich znajomości możliwym będzie porównanie ich z wynikami badań przeprowadzanych nad elementami wytwarzanymi w inny sposób (np. próbka z litego pręta ciągnionego)

Metal Additive Manufacturing (MAM) Applications in Production of Vehicle Parts and Components—A Review

In this article, the significance of additive manufacturing techniques in the production of vehicle parts over the past several years is highlighted. It indicates the industries and scientific sectors in which these production techniques have been applied. The primary manufacturing methods are presented based on the materials used, including both metals and non-metals. The authors place their primary focus on additive manufacturing techniques employing metals and their alloys. Within this context, they categorize these methods into three main groups: L-PBF (laser-powder bed fusion), sheet lamination, and DED (directed energy deposition) techniques. In the subsequent stages of work on this article, specific examples of vehicle components produced using metal additive manufacturing (MAM) methods are mentioned

Predicting Injuries in Football Based on Data Collected from GPS-Based Wearable Sensors

The growing intensity and frequency of matches in professional football leagues are related to the increasing physical player load. An incorrect training model results in over- or undertraining, which is related to a raised probability of an injury. This research focuses on predicting non-contact lower body injuries coming from over- or undertraining. The purpose of this analysis was to create decision-making models based on data collected during both training and match, which will enable the preparation of a tool to model the load and report the increased risk of injury for a given player in the upcoming microcycle. For this purpose, three decision-making methods were implemented. Rule-based and fuzzy rule-based methods were prepared based on expert understanding. As a machine learning baseline XGBoost algorithm was considered. Taking into account the dataset used containing parameters related to the external load of the player, it is possible to predict the risk of injury with a certain precision, depending on the method used. The most promising results were achieved by the machine learning method XGBoost algorithm (Precision 92.4%, Recall 96.5%, and F1-score 94.4%)

Predicting Injuries in Football Based on Data Collected from GPS-Based Wearable Sensors

The growing intensity and frequency of matches in professional football leagues are related to the increasing physical player load. An incorrect training model results in over- or undertraining, which is related to a raised probability of an injury. This research focuses on predicting non-contact lower body injuries coming from over- or undertraining. The purpose of this analysis was to create decision-making models based on data collected during both training and match, which will enable the preparation of a tool to model the load and report the increased risk of injury for a given player in the upcoming microcycle. For this purpose, three decision-making methods were implemented. Rule-based and fuzzy rule-based methods were prepared based on expert understanding. As a machine learning baseline XGBoost algorithm was considered. Taking into account the dataset used containing parameters related to the external load of the player, it is possible to predict the risk of injury with a certain precision, depending on the method used. The most promising results were achieved by the machine learning method XGBoost algorithm (Precision 92.4%, Recall 96.5%, and F1-score 94.4%)

Bending Strength of Polyamide-Based Composites Obtained during the Fused Filament Fabrication (FFF) Process

The research shows the comparison between two types of polyamide-based (PA) composites and pure, base material. The conducted analysis describes how the additions of carbon fibers and glass microbeads affect the material’s properties and its behavior during the bending tests. All samples have been tested in the three main directions available during the FFF process. To extend the scope of the research, additional digital-image-correlation tests and fracture analyses were made. The obtained results indicated a positive influence of the addition of carbon fibers into the material’s volume (from 81.39 MPa in the case of pure PA to 243.62 MPa in the case of the PA reinforced by carbon fibers)