1 / 5

Reliability Model for Compressor Failure

Reliability Model for Compressor Failure. SMRE Term Project Paul Zamjohn August 2008. Proposal Compressor Failure Data: Case 2.16 of Blischke-DATA

declan-martin
Télécharger la présentation

Reliability Model for Compressor Failure

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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

More Related