How can equipment failure analysis and predictive maintenance be achieved?

First, you need to know what predictive maintenance is. Predictive maintenance, is based on the condition (Condition Based) maintenance, in the operation of the machine, the main (or need) parts of the regular (or continuous) condition monitoring and fault diagnosis, determine the state of the facilities and equipment, predict the future development trend of the state of the facilities and equipment, based on the development trend and the possible failure mode, the development of the maintenance plan in advance, to determine the facilities and equipment should be repaired when, what, how and the necessary technical and material support. Based on the development trend and possible failure mode, the maintenance program is formulated in advance to determine the time, content, mode and necessary technical and material support for the facilities and equipment to be repaired. Predictive maintenance integrates facility and equipment condition monitoring, fault diagnosis, fault prediction, maintenance decision support and maintenance activities. It is the application and realization of artificial intelligence in the industrial field.

Secondly, how to realize. Through intelligent, configured, modular monitoring devices, such as sensing equipment intelligent sensors, vibration, temperature, oil, rotational speed, etc., to achieve online real-time data collection of equipment and facility status parameters, and then through the algorithmic model, in order to achieve the function of condition monitoring, fault diagnosis, offline analysis, alarm and early warning;

Equipment predictive technology is mainly divided into the sensing layer, edge layer, platform layer and application layer. In order to adapt to different industries and application areas, predictive maintenance solutions will provide the necessary highly abstracted components and interfaces. This requires the development of a predictive maintenance platform or a complete ecosystem whose architecture should be modular so that functions such as sensing, condition monitoring and assessment, diagnostics, and forecasting can be easily added or enhanced.

Xi'an Innolink's predictive maintenance solutions have been successfully proven in more than 20 industries such as cement, coal, petrochemicals, steel, etc. You can search the official website to learn more.