This master´s thesis deals with the acoustic emission of the gearbox housing. It contains a description of the procedure of solving individual numerical approaches and their results. Finally, it compares the influence of design modifications on acoustic emission.

The aim of the diploma thesis is the design of mechanical parts of the rear axle driveline suitable for rebuilding of a given sports car into an electric car. The introductory part briefly explains the physical principles of the drive and contains a brief summary of the current concepts of electric vehicle propulsion. Afterwards, there is a comparison and selection of a suitable concept for a given electric vehicle, determination of the basic vehicle parameters based on the calculation of the longitudinal vehicle dynamics and the gearbox calculation on the basis of which the design is solved. The next part is dedicated to the computational inspection of parts using the finite element method. The final part deals with the placement of the assembly inside the vehicle and the evaluation of the drive mechanism.

This thesis is devoted to the problem of the production of hulls of the gearboxes. The text of this final thesis shows the production technology for single and series production. At the same time, a critical amount of products for a different production options were established.

This diploma thesis concerns the design proposal for a bicycle gearbox powered by human force. The first part summarizes the existing solutions. The second part includes the proposal of the new design, together with the calculation of the strength for selected parts. Attached are the drawings documenting the findings.

This diploma thesis is about machining of exact hole specifications to fit the bearings from the the theoretical overviewof the fiiting. Another purpose is to describe; the overview of machines, the choices in bearings, and the types of gearboxes. Finally, it deals with the different methods of surface finishing, how to produce the holes for the bearings to fit in gearboxes.Finally, it deals with the different methods of surface finishing and how to produce the holes for the bearings to fit in the gearboxes

The aim of these theses was the creation of a single-stage gearbox by additive technology FDM / FFF. By chosen values was made dimension calculation for gears. The 3D model of the gearbox was designed in 3D software Autodesk Inventor. Single parts were produced on an FDM 3D printer by Prusa Research. Manufacturing programs for parts were prepared in PrusaSlicer. These programs were used for producing individuals parts on 3D Printer. Transparent material and printing parameters for the top of the gearbox were chosen by visual test and test of light intensity. The total cost of model production is calculated in the work. The result of these is a completely working model of a single-stage gearbox with a transparent top of the gearbox.

This diploma thesis deals with designing electric vehicle gearbox. Gearbox should serve as virtual replacement for actual transmission of VW ID.3 EV. Designed gearbox has two gears. In the first section there is an extensive search processed of drivetrain and transmission of battery electric vehicles. Next section contains choice of transmission concept and analyses solving of individual structural nodes – gear wheels, band breaks (components that engage individual gears), carriers, shaft, bearing. In the conclusion of diploma thesis, the two-gear planetary transmission is evaluated.

Background: The gearbox and machinery faults prediction are expensive both in terms of repair and loss output in production. These losses or faults may lead to complete machinery or plant breakdown.  Objective: The goal of this study was to apply advanced machine learning techniques to avoid these losses and faults and replace them with predictive maintenance. To identify and predict the faults in industrial machinery using Machine Learning (ML)  and Deep Learning (DL) approaches.  Methods: Our study was based on two types of datasets which includes gearbox and rotatory machinery dataset. These datasets were analyzed to predict the faults using machine learning and deep neural network models. The performance of the model was evaluated for both the datasets with binary and multi-classification problems using the different machine learning models and their statistics. Results: In the case of the gearbox fault dataset with a binary classification problem, we observed random forest and deep neural network models performed equally well, with the highest F1-score and AUC score of around 0.98 and with the least error rate of 7%.  In addition to this, in the case of the multi-classification rotatory machinery fault prediction dataset, the random forest model outperformed the deep neural network model with an AUC score of 0.98.  Conclusions: In conclusion classification efficiency of the Machine Learning (ML) and Deep Neural Network (DNN) model were tested and evaluated. Our results show Random Forest (RF) and Deep Neural Network (DNN) models have better fault prediction ability to identify the different types of rotatory machinery and gearbox faults as compared to the decision tree and AdaBoost.  Keywords: Machine Learning, Deep Learning, Big Data, Predictive Maintenance, Rotatory Machinery Fault Prediction, Gearbox Fault Prediction, Machinery Fault Database, Internet of Things (IoT), Spectra quest machinery fault simulator, Cloud Computing, Industry 4.0

The diploma works demonstrates the thermodynamic calculation and design of the geometry flow profile of the back-pressure steam turbine for specified inlet and outlet conditions of steam. Next target of the work is to design the drawing of the turbine axial cross section. Structuring of this diploma work calculation is following: - regulating stage thermodynamic calculation - turbine stages calculation - equalizing-balancing piston calculation - entire turbine intrinsic efficiency and power rating determination - basic calculation of gearbox parameters and RENK-type gearbox selection for turbine and generator arrangement

This thesis describes the design of cartesian robot for precise measurement microphones. It contains design of robot, which is set from motorized linear stage and welded steel profiles structure. Model of described robot was computed in Inventor and then strength analysed in Ansys. Individual motors of linear stages and their sensors were designed at the end.