Life based maintenance policy for minimum cost
T. Chitra
Abstract
T. Chitra
Abstract
The maintenance of any system can be categorized in two ways: failure based maintenance (corrective maintenance) and life based maintenance (preventive maintenance). The time interval at which the preventive maintenance could be scheduled is dependent on both the life distribution of the subsystems/components and the total cost involved in the maintenance activity. However, the corrective maintenance cannot be avoided when a random failure of a component occurs. The total cost of the maintenance depends on the number of components replaced during the entire operating period of the system and the respective cost involved in maintenance actions. In this paper the preventive maintenance schedule (t/sub 0/) is calculated taking the failure distribution of a component as Weibull. The variation in (t/sub 0/) with respect to the shape parameter (/spl beta/) and characteristic life (/spl alpha/) of the Weibull distribution was studied by the author for a given preventive maintenance cost and corrective maintenance cost. The ratio of the corrective maintenance cost to the preventive maintenance cost (R/sub cp/) has a significant effect on the maintenance schedule (t/sub 0/). Thus the variation of (t/sub 0/) with (R/sub cp/) is addressed in this paper. The ratio is varied between 10 and 1.5. It is found that the (t/sub 0/) value increases as shape parameter increases when the ratio is 10 whereas the (to) value decreases when the ratio is 1.5. This shows that as we decrease the cost ratio (R/sub cp/) the frequency of preventive maintenance decreases with shape parameter. This in turn implies that the frequency of the preventive maintenance schedule can be kept at minimum by bringing down the cost of corrective maintenance. Sensitivity analysis carried out on the (t/sub 0/) values indicates that the variation in the cost of maintenance is about 5 to 8 percent :in all the cases even when the value of (t/sub 0/) is increased. by 50% over the optimum value. This indicates, while the optimum value of (to) obtained may be of academic interest, one can 'in practice' choose a convenient value near the optimum without appreciably affecting the advantage in terms of cost.
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The maintenance of any system can be categorized in two ways: failure based maintenance (corrective maintenance) and life based maintenance (preventive maintenance). The time interval at which the preventive maintenance could be scheduled is dependent on both the life distribution of the subsystems/components and the total cost involved in the maintenance activity. However, the corrective maintenance cannot be avoided when a random failure of a component occurs. The total cost of the maintenance depends on the number of components replaced during the entire operating period of the system and the respective cost involved in maintenance actions. In this paper the preventive maintenance schedule (t/sub 0/) is calculated taking the failure distribution of a component as Weibull. The variation in (t/sub 0/) with respect to the shape parameter (/spl beta/) and characteristic life (/spl alpha/) of the Weibull distribution was studied by the author for a given preventive maintenance cost and corrective maintenance cost. The ratio of the corrective maintenance cost to the preventive maintenance cost (R/sub cp/) has a significant effect on the maintenance schedule (t/sub 0/). Thus the variation of (t/sub 0/) with (R/sub cp/) is addressed in this paper. The ratio is varied between 10 and 1.5. It is found that the (t/sub 0/) value increases as shape parameter increases when the ratio is 10 whereas the (to) value decreases when the ratio is 1.5. This shows that as we decrease the cost ratio (R/sub cp/) the frequency of preventive maintenance decreases with shape parameter. This in turn implies that the frequency of the preventive maintenance schedule can be kept at minimum by bringing down the cost of corrective maintenance. Sensitivity analysis carried out on the (t/sub 0/) values indicates that the variation in the cost of maintenance is about 5 to 8 percent :in all the cases even when the value of (t/sub 0/) is increased. by 50% over the optimum value. This indicates, while the optimum value of (to) obtained may be of academic interest, one can 'in practice' choose a convenient value near the optimum without appreciably affecting the advantage in terms of cost.
Key concepts: Corrective maintenance, Preventive maintenance, Weibull distribution, Reliability engineering, Schedule, Optimal maintenance, Interval (graph theory), Planned maintenance