The main objective of this article is to analyse the structural design of tire lifting equipment for tire services. To gain a better insight into the problem, several steps must be taken. The first ...step is to conduct a market analysis, which involves identifying all available equipment. Several types of lifting devices were distinguished within the development process, which differ from each other in terms of design and power supply. The type of structure and power unit represent the second steps in the design process. This is a critical aspect of the design since the forces necessary to move the system change as a result of these attributes. The design itself is the last step in the device’s design. Passenger cars differ from each other by their weight, which is limited to 3.5 tons. Based on the weight, basic strength calculation and dimensioning of the lifting device are carried out. Based on the calculations, the scissor lift device is selected. The lower frame, scissor legs, ramp, mechanical lock, and scissors drive mechanism are five main components of the device. This type of structure is best used with a hydraulic drive unit, which is calculated in the article.
The paper deals with the engineering design of lifting device weighing up to 3.5 tons. The first part is devoted to market research and the use of lifting equipment. Variant with a scissor ...construction and a hydraulic drive is chosen. The design itself follows. The machine composes five main parts: the lower frame, the scissor structure, the ramp, the mechanical lock and the drive mechanism. The individual chapters are devoted to design and analysis of these components.
FEM analysis of the hatch for special use Fiačan, Jakub; Hrček, Slavomír; Jenis, Jozef ...
Transportation research procedia (Online),
2023, Letnik:
74
Journal Article
This study offers a complete analysis of the use of deep learning or machine learning, as well as precise recommendations on how these methods could be used in the creation of machine components and ...nodes. The examples in this thesis are intended to identify areas in mechanical design and optimization where this technique could be widely applied in the future, benefiting society and advancing the current state of modern mechanical engineering. The review begins with a discussion on the workings of artificial intelligence, machine learning, and deep learning. Different techniques, classifications, and even comparisons of each method are described in detail. The most common programming languages, frameworks, and software used in mechanical engineering for this problem are gradually introduced. Input data formats and the most common datasets that are suitable for the field of machine learning in mechanical design and optimization are also discussed. The second half of the review describes the current use of machine learning in several areas of mechanical design and optimization, using specific examples that have been investigated by researchers from around the world. Further research directions on the use of machine learning and neural networks in the fields of mechanical design and optimization are discussed.
PDF
