## 1 Introduction  
The concept of reliability encompasses the strategy, methodology, and planning that guide the actions necessary to optimize the performance of production systems. The primary objective is to guarantee that robotic equipment performs its intended function without failure, within the stipulated timeframe, and with the requisite precision. A comprehensive reliability approach integrates all of these initiatives into a unified, systematic framework. The reliability and service life of gear mechanisms or transmission systems used in advanced applications depend not only on their design, precision manufacturing, and appropriate dimensioning according to operational and load conditions, but also on the application of tribological and tribodiagnostic knowledge. The importance of lubrication and oil care is reflected in various ways in practical applications. It is certainly easier to check the oil level in the reservoir and top it up if necessary or visually monitor for potential lubricant leaks while walking through the production hall than to later investigate the causes of increased vibrations due to high contamination of the lubrication system--or, even worse, to deal with serious damage to the production equipment. This issue is addressed from multiple perspectives. One article [1] presents a systematic review of vibration-based condition monitoring in rotating machinery, with a focus on the methodologies used in the key phases of automatic fault diagnosis, including signal measurement, pre-processing, processing, feature selection, and fault diagnosis. It explores the application of vibration monitoring across various mechanical systems and components, highlighting the main techniques used in each diagnostic phase. The review analyzes the effectiveness of different signal processing, feature selection, and diagnostic methods, with an emphasis on their impact based on the specific aspects studied. The findings provide insights into current research trends and innovations in vibration-based diagnostics, offering valuable directions for future developments in the field. The impact of oil type on vibration characteristics--particularly the influence of oil viscosity and pressure on vibration levels in pumps and rotating machinery--plays a crucial role in system performance and reliability. Key oil properties, such as viscosity, significantly affect both average vibration values and the dynamics of peak-to-peak acceleration. Additionally, the physicochemical composition of various oils, including engine, hydraulic, and gear oils, contributes to cavitation behavior and vibration response. These factors are especially important in the context of optimizing and designing more equipment. Another article [2] is devoted to a systematic study and detailed analysis of these aspects. A third study [3] is devoted to the development of a test rig for monitoring the impact of various operating conditions, such as shaft load, shaft speed, lubrication level, and abrasive contamination, on level gear mechanisms over different operating hours. The results demonstrate that combining sound and vibration monitoring provides a reliable approach for diagnosing fault conditions in level gears. Gear misalignment is a critical factor contributing to gearbox failure, leading to increased wear and oil degradation. Real-time monitoring using a combination of sensors enables the detection of misalignment effects through changes in lubricant condition and wear particle generation. The development and implementation of an online diagnostic system integrating these aspects is the focus of this study [4]. A newly developed compound diagnostic system, integrating a compound sensor and signal processor, enables simultaneous monitoring of vibration acceleration and acoustic emission for rolling contact fatigue in grease-lubricated ball bearings, presented in [5]. Diagnostic features, such as RMS, mean, variance, skewness, and kurtosis, are extracted to evaluate bearing condition, with the RMS of vibration acceleration proving most effective.