Supporting Maintenance Scheduling: a case Study
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| 5. Conclusion An algorithm is being developed to construct a quick scheduling solution, taking into account availability of equipment and technicians, processing times of maintenance tasks, due date, competence level required and downtime of production line. The algorithm orders the maintenance tasks by a criticality index equipment and due date and the allocation to technicians occurs after verifying the availability of required spare parts. Thus, the algorithm that supports the scheduling support tool is composed by identification of availability times, an ordering method and an allocation method, and aims to minimize the total tardiness. Through an application example, it was possible to show the proposed algorithm’s effectiveness. The ordering method adopted in this initial approach can lead to situations that decrease the efficiency of scheduling, such as the maintenance tasks related to equipment with lower BIR value that have higher impact on the quality and performance of the equipment are not scheduled, because the algorithm only prioritizes the equipment with higher BIR. The same goes to spare parts, where this method can lead to situations where the spare parts are allocated to equipment with higher BIR value, when it can be more urgent to allocate them toequipmentwith lower BIR value (if the spare required is the same. In this first computing experience, it was possible to conclude that the PMS is a promising scheduling approach method. Future work will be focused on tasks ordering considering the impact of not performing the maintenance task as well as the possible tolerance in due date fora given task. After the complete definition of the algorithm, the associated computational application will be developed to be integrated in the company’s CMMS. Download 305.56 Kb. Share with your friends:
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