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Maintenance Philosophy Single spares storage warehouse? – Assumed to be the case Multiple spares storage warehouses? –If so, each will need to be equally.

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Presentation on theme: "Maintenance Philosophy Single spares storage warehouse? – Assumed to be the case Multiple spares storage warehouses? –If so, each will need to be equally."— Presentation transcript:

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2 Maintenance Philosophy Single spares storage warehouse? – Assumed to be the case Multiple spares storage warehouses? –If so, each will need to be equally stocked to provide the necessary spare when needed. –If it was determined that only 1 spare was mathematically needed to support the system, then the quantity will need to be increased to match the number of spare storage warehouses.

3 Spares Calculation Parameters Annual Operating Requirement (AOR) in Hours Pipeline Time (average time to receipt of part after ordering) Target Confidence Factor value (probability of having a spare when needed): usually 95% Total system quantity for parts to be spared

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5 Confidence Factor Formula The confidence factor value is the probability that a spare will be available in the event of a failure, expressed as a percentage. The higher the value, the greater the probability that a spare will be available. –Higher spares quantities yield higher confidence factor values. –Lower pipeline time yields higher confidence factor values. –Higher MTBF values yield higher confidence factor values. –Lower system quantities yield higher confidence factor values.

6 Spares Modeling Goal: Determine a recommended quantity of spare parts to achieve a desired confidence level. Tool: Applies the following logic to determine the recommended Spare Quantity value.

7 Spares Modeling This example shows how variable inputs impact the confidence factor Confidence Factors expressed as percentages. System Qty represents how many of the spared item are contained in a system.

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10 Replenishment Methodology Example For module XYZ12345, expected failures for 60 months is 0.26 The condemn rate indicates the percentage of failed assemblies that cannot be repaired after failure (5% for our example) When this occurs, a Replenishment Spare is needed as a replacement. Replenishment Spares values are driven by both the part criticality and the comfort level of program management: Minimal Sparing (expected failures * condemn rate) = 0.0 to 0.99 = no spare 1.0 to 1.99 = 1 spare 2.0 to 2.99 = 2 spares Etc… Average Sparing (expected failures * condemn rate) = 0.0 to 0.49 = no spare 0.5 to 1.49 = 1 spare 1.5 to 2.49 = 2 spares Etc… Maximize Sparing (expected failures * condemn rate) = 0.01 to 1.0 = 1 spare 1.01 to 1.99 = 2 spare 2.01 to 2.99 = 3 spares Etc…

11 Replenishment Quantity Report

12 Spares Cost Report

13 Expensive Spares – Trade-offs Here is an example to illustrate the impact of reducing the spare quantity by 1 of the most expensive items on the list. In some cases, the Confidence Factor may still be an acceptable level considering the money saved. For example, lets say we have a radar system and we are looking to spare the most expensive part in the system. In our example, the system normally requires 3 spares to support 4 radar systems (for Annual Operating Requirement of 2000 hours) to have a Confidence Factor greater than 95%. Consider the following: 3 spares yields a 98.23% Confidence Factor 2 spares yields a 92.36% Confidence Factor Is the trade-off acceptable?

14 For more information contact: Rich Herman


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