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 to the Philip Slater book
“5 Myths of Inventory Reduction” (Initiate Action) a 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 multiplying the probability of failure times the consequences of the failure,
in this case, the probability of 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 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 the 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 a 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 on the risk to break
stocks, usually the probability is between 90 % and 99 % but it depends on every
situation; we calculate by a discrete probability distribution choosing a Poisson Distribution if is an HPP (Homogeneous Poisson Process) when the failure rate is constant, like an exponential distribution, or a Potential Model if is an NHPP (Non-Homogeneous 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.
