Application of a 3D-Printed Part with Conformal Cooling in High-Pressure Die Casting Mould and Evaluation of Stress State During Exploitation.

The article addresses stress formation in the structural 3D-printed elements of a high-pressure die casting die mould used for production of aluminum castings. The 3D-printed elements with conformal cooling are manufactured of 18Ni300 powder. Initial numerical calculations were performed on a test die mould made of standard steel X40CrMoV5 to determine temperature distribution and stress state, providing a baseline for comparing 3D-printed 18Ni300 parts.

Decision Support Tool in the Selection of Powder for 3D Printing.

The work presents a tool enabling the selection of powder for 3D printing. The project focused on three types of powders, such as steel, nickel- and cobalt-based and aluminum-based. An important aspect during the research was the possibility of obtaining the mechanical parameters.

Analysis of the Possibility of Using Selected Tools and Algorithms in the Classification and Recognition of Type of Microstructure.

The aim of this research was to develop a solution based on existing methods and tools that would allow the automatic classification of selected images of cast iron microstructures. As part of the work, solutions based on artificial intelligence were tested and modified. Their task is to assign a specific class in the analyzed microstructure images.

Analyze the Wear Mechanism of the Longwall Shearer Haulage System.

The wear characteristics and related mechanisms of the Longwall Shearer Haulage System were investigated. Wear is one of the main reasons for failures and downtimes. This knowledge can help solve engineering problems.

Development of a CT Image Analysis Model for Cast Iron Products Based on Artificial Intelligence Methods.

This paper presents an assessment of the possibility of using digital image classifiers for tomographic images concerning ductile iron castings. The results of this work can help the development of an efficient system suggestion allowing for decision making regarding the qualitative assessment of the casting process parameters. Special attention should be focused on the fact that automatic classification in the case of ductile iron castings is difficult to perform.

Technological Optimization of the Stirrup Casting Process with the Use of Computer Simulations.

The article presents the optimization of high-pressure die casting process technology for equestrian stirrups with the application of computer simulation. In the initial stage, the output technology was analyzed, and on the basis of a series of virtual experiments the cause of defects in the casting was highlighted. The optimization process includes different designs of a gating system.

Assessment of the Quality and Mechanical Parameters of Castings Using Machine Learning Methods.

The aim of the work is to investigate the effectiveness of selected classification algorithms and their extensions in assessing microstructure of castings. Experiments were carried out in which the prepared algorithms and machine learning methods were tested in various conditions and configurations, as well as for various input data, which are photos of castings (photos of the microstructure) or information about the material (e.g.