Optimisation of opportunistic maintenance of a multi-component system considering the effect of failures on quality and production schedule: A case study

被引:42
|
作者
Tambe, Pravin P. [1 ]
Mohite, Satish [1 ]
Kulkarni, Makarand S. [1 ]
机构
[1] Indian Inst Technol Delhi, Dept Mech Engn, New Delhi 110016, India
关键词
Opportunistic maintenance; Multi-component system; Schedule delay factor; Rejection cost; Simulated annealing; Genetic algorithm; SELECTIVE MAINTENANCE; REPAIRABLE SYSTEMS;
D O I
10.1007/s00170-013-5122-7
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
For a manufacturing equipment, any unplanned breakdown during the production period results into a high production loss. To keep the manufacturing facilities in good condition, preventive maintenance is planned. However, because of limited time and availability of resources, not all the system components can be or need to be repaired/replaced during a planned opportunity. Hence, the unplanned breakdowns can also be considered as an opportunity to do the maintenance activities for other components to take the advantage of economic dependency in multi-component system. However, when the system is under maintenance, it is very conservative to take the decision of maintenance actions on the components because of limited available time and resources. For such situation, this paper consider an opportunistic maintenance model for a multi-component system to take maintenance decision with a constraint on available time and the system availability requirements. The maintenance decisions for each component involves one of the three actions namely, repair, replace or do nothing to achieve the target availability with minimum maintenance cost. The model also considers the effect of component failures on the quality of product being manufactured as well as the production schedule on the machine. The cost of rejections is considered in the total failure cost along with the maintenance and downtime costs. The production schedule delay factor is considered as a constraint for the maintenance decision to account for the effect on production schedule delay. The optimal solution for the model is obtained using three solution methodologies namely simulated annealing, genetic algorithm and sequence heuristics. Using a real-life example of high pressure die casting machine, the opportunistic maintenance approach is demonstrated and results are discussed.
引用
收藏
页码:1743 / 1756
页数:14
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