One of the results of the RCM analysis is that allows us to optimize the stock of spare parts; it means important savings that can justify the analysis.
According the Philip Slater book “5 Myths of Inventory Reduction” (Initiate Action) an usual mistake is to think that reduce the stock of spare parts increase the risk of downtime, when the stocks usually are oversizing so to reduce it keeping a tolerable risk is possible.
In this respect, the RCM analysis allows us to define the risk that we are willing to assume to calculate the optimum spare parts stock.
We remind the risk is calculated by multiplied the probability of failure times the consequences of the failure, in this case, the probability of a failure without spare parts multiplied by the cost of no repair until we receive the spare parts.
We start with the logical tree that we already have used to define maintenance tasks and actions, we classify the tasks in:
- Condition Based Tasks: Initially we don’t need a stock of spare parts because the predictive strategy lets us know signals of failures, so we can ask the spare parts and planning a restoration or a discard. However, we must consider the probability of the predictive technique does not find the signals of the failure.
- Time Based Tasks: We don’t need a stock of spare parts too because we already have planned all the maintenance tasks so we can receive the spare parts just in time. However, we must consider the probability of a failure during the time between maintenance tasks.
- Failure Finding Tasks: In this case we must consider the probability to find a failure.
If the RCM Logic Tree gives us the result Run-To-Failure we must consider the probability of a failure during the time from place an order to deliver the spare parts. We need to have spare parts enough in our storeroom during this time to solve any restoration or discard.
NORSOK Standard Z-008 Risk based maintenance and consequence classification, in its Annex C3 (Informative) Risk assessment of spare parts proposes an example of risk matrix, in this matrix the spare parts not frequently used, capital spare parts, seldom or never used, with low or medium consequences have No Stock. And to study to use a central warehouse or calculate the minimum or optimum stock based in risk for the other frequencies and consequences.
Once we have decided to have spare parts we must decide a probability of success, based in the risk to break stocks, usually the probability is between 90 % and 99 % but it depends every situation; we calculate by a discrete probability distribution chossing a Poisson Distribution if is a HPP (Homogeneus Poisson Process) when the failure rate is constant, like an exponential distribution, or a Potential Model if is a NHPP (Non Homogeneus Poisson Process) if the failure rate is variable, like a Weibull distribution; the number of spare parts K to ensure that probability based in the expectation of failures during the time between the order and the delivery of the spare parts.