Bucket conveyors are widely used in various industrial sectors due to their efficiency in material transport. However, like any machinery, they are susceptible to degradation during operation, leading to a decrease in performance and an increase in the risk of failure. Therefore, research was...

Cigarette production is a highly automated process in which friction between fibrous materials plays a key role in the handling, transport, and packaging of tobacco products. Excessive friction often leads to sorting slot blockages and production line downtime, highlighting clear economic...

As part of the research conducted, the correctness of the serial peripheral interface (SPI) communication was tested using the Raspberry Pi 4B. The purpose of the experiment was to confirm the possibility of stable data exchange between the control unit and external peripheral circuits, with...

The aim of this study was to conduct an advanced analysis of the MEMS sensor, including both experimental tests and numerical simulations, in order to determine its mechanical properties and operational dynamics in detail. It is challenging to find publications in the literature that are not based on theoretical assumptions or general manufacturer data, which do not reflect the actual microstructural characteristics of the sensor. This study uses a numerical model developed in MATLAB/Simulink, which allows the experimentally determined material characteristics to be combined with predictive dynamic modelling. The model takes into account key mechanical parameters such as stiffness, damping and response to dynamic loads, and the built-in optimisation algorithm allows the structural parameters of the MEMS accelerometer to be estimated directly from experimental data. In addition, SEM microscopic studies and EDS chemical composition analysis provided detailed information on the sensor’s microstructure, allowing its impact on mechanical properties and dynamic parameters to be assessed. The integration of advanced experimental methods with numerical modelling has resulted in a model whose response closely matches the measurement results, which is an important step towards further research on design optimisation and improving the reliability of MEMS sensors in diverse operating conditions.