Abstract
In reality, preventive maintenance (PM) tasks usually include lubrication, cleaning, inspection, adjustment, alignment and/or replacement. They should be planned before failure occurs, aiming to improve the overall reliability and availability of the production system. In the literature on PM scheduling, researchers usually consider maintenance as a single task and schedule it together with the production schedule. This may result in poor predictions on maintenance scheduling since different kinds of PM tasks have different maintenance intervals and require different durations. Production also involves various kinds of resources, such as plastics production requiring injection machines and moulds. These resources require different sets of maintenance treatment. If maintenance schedules for different resources are not harmonised, the planned production will be disturbed dramatically by the non-availability of resources. In this aspect, this paper proposes a joint scheduling (JS) method to handle production–maintenance scheduling that considers multiple resources and maintenance tasks. A genetic algorithm approach is applied to hypothetical numerical examples with the objective of minimising the makespan. The numerical solutions obtained show that the proposed JS method significantly reduces the makespan in this new scheduling problem.
Acknowledgements
The work described in this paper was substantially supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. PolyU 510410), and a grant from the Innovation and Technology Commission of the Hong Kong Special Administrative Region, China (Project No. UIT/105).