Optical monitoring system availability optimization via semi-Markov processes and genetic algorithms

System availability optimization is one of the main issues to oil production managers: the greater the system availability the greater the production profits are. Provided that preventive maintenance actions promote rejuvenation impact on availability indicator, this paper proposes an approach to maximize the mean availability by identifying an optimal maintenance policy for downhole optical monitoring systems, which are modeled according to non-homogeneous semi-Markov processes. In order to solve the resulting optimization problem constrained by system performance costs, new real-coded GA operators are also presented. The proposed approach is exemplified by means of an application to a real scenario in onshore oil wells in Brazil.