OPTIMIZE MAINTENANCE PATTERN AND PLANNED REPAIR OF MAIN ENGINE TYPE DEUTZ AG TBD 620 V 16 KRI SULTAN NUKU -873

Warships of the Republic of Indonesia (KRI) is one of the prime weapons systems that has an important role in
order to accomplish operation of the Indonesian Navy. One of type warship the Navy owned Koarmatim Ujung
Surabaya is KRI.Sultan Nuku-873. This Warship consist of the amount of vital sistem that need maintenance of
prevent system reliability and availability. One of vital sistem in Warship operation is engine system.
Government budgeting is one of reasoning that task maintenance of engine system Warship nowadays just
basedupon maintenance manual book, its means determine components residual life time, component replaced if
failed only. Such a thing resulted higher pinalty cost is failed occur in operation. Recently, engine system in
warships have failure rate that gradually increase year by year. This is especially because of high flight
hoursand old components. That requires a maintenance method that can improve the reliability KRI trend for
increased damage to critical engine components can be reduced, one method that can be used is to create a
pattern of planned maintenance and repairs on engines with a minimum cost.
From the analysis has been done on the basis of data damage to the engine components can be know failure rate
distribution, the value of reliability, probability of failure and failure rate. From the four parameters were
added to the data amount of the costs of replacement, it can be made system modeling and calculation
optimization in order to obtain the interval of time and optimal replacement costs based on the value of CostBenefit Ratio for the lowest, and the risk matrix that underlies the determination whether or not to do the
replacement parts.
The optimization result show that with 7 components warships through ,the optimum interval task replacement
between 3124 to 5525 hours, and the minimal total replacement cost between $ 165,00 to $ 1250,00. The risk
matrix result show that with applied this model, failed occur risk of each components , between 1-8 failed every
to hours.