The Poisson distribution is useful for calculating the probability that a certain number of failures will occur over a certain length of time for equipment exhibiting a constant failure rate. If events
are Poisson distributed, they occur at a constant average rate and the number of events occurring in any time interval is independent of the number of events occurring in any other time interval.
Therefore, given a part population (n), the failure rate of the part (λ) and a time interval (t) during which no further spares will be available, the Poisson
distribution can be used to predict the number of failures that will occur, with a certain probability, and thus the number of spares required for some time period of interest. The calculation
of spares required for a given time period assumes that failed items are not repaired and put back into inventory during the time period of interest. Part failure rates should be entered in failures per million hours (FPMH).
Input #1 is either copy and paste five columns (fields) from Microsoft Excel, or pipe delimited (|) data if entered manually or prepared in a text file editor. Each input line represents a single part (i.e., quantity=1), so to calculate spares required to support 20 items of the same part number requires 20 identical input lines. This is easily accomplished by first preparing input data in the Microsoft Excel input template below and pasting it into box #1.
The five expected fields are from left to right:
Part Number, Part Description, Failure Rate (FPMH), Time Period (hours), and Confidence Level (0.01 to 0.9999). If anomalies exist (e.g., different failure rates entered for the same part number), the last entry for a given part number takes precedence.
Input data templates:
Example Excel template
Example pipe delimited text file template