Risk-based approach in the problems of modeling metrological support for a measuring instrument fleet

The article considers methods for managing metrological support for a fleet of measuring instruments (MIs). The present situation is described where the MI fleet is heterogeneous and includes obsolete MIs with a long service life and significant operating time, as well as modern high-tech MIs. Of note is that the proportions of these MI groups change over time as MIs age and move from one group to another. Also, the MI fleet is renewed as a result of procuring new and modernizing existing instruments. The heterogeneity of the MI fleet leads to the need to develop and apply new methods for managing its metrological support, including the use of mathematical modeling. A promising method was proposed for managing metrological support for the MI fleet that relies on the risk-based approach (RBA). As a risk factor for the MI fleet, the authors adopted the probability of finding a randomly selected MI from the fleet in an unavailable state at a random point in time. As per the RBA, the MI fleet was divided into risk classes. An algorithm was developed for assigning MIs to different risk classes that is based on solving a series of problems of fleet operation optimization, taking into account its aging and renewal. The results are presented of RBA application in modeling metrological support for the heterogeneous MI fleet, including both modern and obsolete instruments having different metrological characteristics, operating time to failure, and life. It was established that by dividing all MIs into risk classes and verifying them in each risk class at rational (near optimal) intervals and with tolerance for the monitored parameters, it is possible to minimize the total average risk for such a fleet while conserving instrument life.