Optimization of Maintenance Strategy for Electrical Power Devices at Risk and Uncertainty Optimization of Maintenance Strategy for Electrical Power Devices at Risk and Uncertainty Vladimír Blažek, Petr Toman Brno University of Technology Petr Skala EGÚ Brno, a.s. EGÚ Brno, a.s.

Maintenance of electrical power devices and Game theory Maintenance Periodical maintenance - carried out by time Reliability centered maintenance - based on factual state of the assets Game theory 2 players game Optimization of periodically performed maintenance Time intervals between the maintenances Order of precedence and types of maintenances 2

Basic elements of the decision-making issue Set of players Maintenance worker x Accident Set of maintenance strategies Set of types of failures Set of prospective results Game matrix Type of failure Maintenance strategy 3

Evaluation of the game matrix Bayes – Laplace criterion Risk-prone approach „Maintenance man“ knows the maintenance strategies and their useability that apply for the respective types of failures, and only the relative frequencies of occurrence of such failures from the list of failures are known 4

Hurwitz criterion Uncertainty-prone approach „Maintenance man“ knows the maintenance strategies and their useability that applies for the respective types of failures, but the relative frequencies of occurrence of such failures from the list of failures are not known Evaluation of the game matrix 5

Element of the game matrix Sensitivity analysis of the mathematical model Sensitivity analysis Analytical analysis Numerical analysis 6

Parameters of the model According to impact on the element of a matrix of games 1.Parameters having a significant impact Life expectancy (lifetime) Mean idle time of a specific construction element, caused by maintenance Mean time between failures Price for the non-supplied electric energy Non-supplied power during a period of failure and repair Mean maintenance costs Non-supplied power during the period of performing the maintenance works Parameter of the distribution function (<1) 2.Parameters having a comparably small impact Ageing factor Mean idle time caused by a failure and a subsequent repair Mean repair costs Degree of renewal after maintenance Parameter of the distribution function (>1) 3.Parameters having only a very small impact Degree of renewal after repair Coefficient of non-performed maintenance Sensitivity analysis of the mathematical model 7

Conclusion The theory of games can be used for the optimization of a time-bound periodical maintenance  Sequences of maintenance works and intervals between them can be optimized Data about failures and repairs of equipments are needed  The longer time period of data acquisition leads to the more reliable results The method could be combined with some of the diagnostic methods  Further research 8

Thank you for attention Thank you for attention Vladimír Blažek, Petr Toman Brno University of Technology Petr Skala EGÚ Brno, a.s. 9 EGÚ Brno, a.s.