Integrated Maintenance Decision Making Platform for Gantry Cranes in Container Terminal

The paper presents a risk-based model to coordinate the preventive-predictive maintenance process of gantry cranes in a container terminal with vessels high demand. The model coordinates the preventive-predictive maintenance process minimizing the risk of Gantry Cranes Inefficiency (GCI). The risk is estimated with a sequential Markov Chain Monte Carlo (MCMC) simulation model. In this paper, the Preventive-Predictive Maintenance Scheduling (PPMS) process of gantry cranes is non-linear stochastic optimization problem and it is efficiently solved with the algorithms Particle Swarm Optimization (PSO). The model allows the terminal container operators to obtain a maintenance schedule that minimizes the risk of GCI, as much as possible in a container terminal; as well as establishing the desired level of risk. The paper demonstrates the proposed model effectiveness with data of a real container terminal.