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Reliability Model for Compressor Failure

This proposal outlines the analysis of failure data for large air compressors at a military base located near the seacoast. The focus is on understanding the probabilistic failure structure, particularly in relation to the bleed system, which is critical for compressor functionality. Salt-laden air is suspected to impact reliability significantly. The analysis will include generating descriptive statistics, selecting appropriate distributions, and calculating failure probability density functions, cumulative distribution functions, survival probabilities, and hazard functions, as well as performing Monte Carlo simulations to model and assess the reliability of the compressors.

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Reliability Model for Compressor Failure

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  1. Reliability Model for Compressor Failure SMRE Term Project Paul Zamjohn August 2008

  2. Proposal • Compressor Failure Data: Case 2.16 of Blischke-DATA • Data on “large air compressors” for a military base near the seacoast will be analyzed to determine the probabilistic failure structure. Air compressors require “bleeding” prior to operation to function properly, the data below represents failure due to binding in the bleed system. Salt air due to proximity to the ocean is believed to be a major contributor, nothing is known about other variables and their impact to reliability. • Analysis will include: • Generating the descriptive statistics • Selecting the distribution that best describes the data and the distribution parameters • Calculating the failure probability density function (f) • Calculate the cumulative distribution function (F) • Calculating the survival probability function (R) • Calculating the hazard function (z) • Determining the MTTF • Perform Monte Carlo simulation to model and assess reliability

  3. Compressor Failure Data

  4. Probability Distribution Function Failure vs. Reliability Function Hazard (failure) Rate Monte Carlo Simulation vs. Equation

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