Maintenance processes modelling and optimisation

• Published in: Reliability engineering & system safety 2017-12, Vol.168, p.150-160
• Main Authors: Zhang, Yang, Andrews, John, Reed, Sean, Karlberg, Magnus
• Format: Article
• Language: English
• Subjects: Braking; Completion time; Computer Aided Design; Computer simulation; Costs; Datorstödd maskinkonstruktion; Discrete event systems; Discrete-event simulation; Error correction; Failure mode and effect analysis; Genetic algorithm; Genetic algorithms; Maintenance; Optimisation; Optimization; Reliability engineering; Repair & maintenance; System availability
• ISSN: 0951-8320; 1879-0836; 1879-0836
• DOI: 10.1016/j.ress.2017.02.011

A Maintenance Procedure is conducted in order to prevent the failure of a system or to restore the functionality of a failed system. Such a procedure consists of a series of tasks, each of which has a distribution of times to complete and a probability of being performed incorrectly. The inclusion of tests can be used to identify any maintenance errors which have occurred. When an error is identified it can be addressed through a corresponding correction sequence which will have associated costs and add to the maintenance process completion time. A modified FMEA approach has been used to identify the possible tests. By incorporating any selection of tests into the maintenance process it can then analysed using a discrete-event simulation to predict the expected completion time distribution. The choice of tests to perform and when to do them is then made to successfully complete the maintenance objective in the shortest possible time using a genetic algorithm. The methodology is demonstrated by applying it to the repair process for a car braking system. The developed method is suitable for application in abroad range of industries. •An approach which considers tests performed to detect faults in the maintenance process has been developed.•Given any series of tests selected, the maintenance process can be simulated to predict the distributions of times to successful completion of the maintenance task.•By embedding the simulation modelling into a genetic algorithm the tests can be selected which will minimise the time to successfully complete maintenance accounting for any errors which occur.•The approach is demonstrated through application to the repair of a car braking system.