All major factors causing high operational expenses and losses due to failures are revealing in machinery operation life, when cumulative damage directly depends on timeliness of failure detection and adequacy of personnel actions depending on various speed of resource losses due to wear of machinery elements. The later the personnel reacts to worsening of machinery condition the greater resources are required to restore it, and if the situation is critical the total costs may exceed the ones enough for building a new facility. In turn, personnel’s reaction rate is determined by two main factors: machinery condition observability and adequacy of reaction to its worsening which mostly is influenced by manager’s being demanding and aware of the situation’s criticality level.
Thus, it is necessary to ensure failure skipping risk monitoring in real-time, i.e. provide managers of all levels with financial assessment of the current rates of possible costs and losses to the company in existing operational conditions of hazardous production facilities. Observability of the machinery degradation process in real time and good labour discipline allow to avoid the risk of accidents.
Data on machinery condition and its malfunctions and developing defects of the most critical parts of a machine are presented by the COMPACS® systems to all levels of production management. The systems automatically, without involving diagnostic specialists, detect all major classes of machinery malfunctions and for each of them issues several prescriptions automatically diagnosing defects of centrifugal and piston compressors, pumps, air-coolers and other machinery. Multiple analysis of maintenance works carried out by system’s prescriptions has revealed that all shutdowns of machines in “Unacceptable” state due to the system’s prescriptions were really necessary. In 100% of cases not only the necessity of maintenance works, but the machinery defects detected by the COMPACS® system were proved to be real.
Kostyukov V.N., Kostyukov Al.V., Kostyukov A.V. Real-time condition monitoring of machinery // Controlling. - 2014. - №4. - P. 44-49.
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