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Predicting Failures of Repairable Systems (MFG675U)

Presented by: Steven Wachs
 
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Event Description

Analyze Repairable Systems Data to Predict Lifecycle of Repaired Systems

Many Product Development Engineers, Quality, and Reliability professionals are familiar with the standard life data analysis methods (e.g. Weibull Analysis) to predict product reliability over time. However, these methods are only appropriate for the reliability modeling and prediction of non-repairable systems (e.g. items that are discarded and replaced once they fail). The typical models used such as Weibull or Lognormal are used to predict the time until the first failure is observed.

Of course, most complex and expensive systems such as automobiles, airplanes, oil and gas drilling equipment, etc. are not discarded upon failure but are repaired and put back into service. The reliability of such systems depends on the previous repairs that have occurred. Analyzing repairable systems data (or recurrent event data, more generally), allows important questions to be answered such as:

  • How many failures do I expect to see in the next week, month, or year?
  • Is the system stable, improving, or degrading over time?
  • How is the failure rate changing over time?
  • What is the average time between failures?
  • How many spare parts should I keep in inventory?
  • Should I continue to repair the system or replace it?
  • What is the probability of surviving the next "mission" or specified service time without a failure?

This webinar by expert speaker Steven Wachs will summarize the methods and models used to describe repairable systems data to improve decision making regarding key assets. Through this event, Steven will help you distinguish between applications for traditional life data analysis (e.g. Weibull Analysis) and repairable systems analysis. He will share how you can analyze repairable systems data, forecast future failures, failure rates, and mean time between failures, predict reliability of a repairable system, as well as perform both nonparametric and parametric analyses.

Session Highlights

  • Review of traditional life data analysis and applications
  • Key features of repairable systems data and analyses
  • Non-parametric analysis of repairable systems
  • Mean cumulative function
  • Rate of Occurrence of Failure (ROCOF)
  • Stable, degrading, & improving systems
  • Parametric modeling of repairable systems data
  • HPP and NHPP Models
  • Estimating number of failures and failure rates over time
  • Estimating MTBF
  • Estimating reliability and conditional reliability
  • Introduction to general renewal process models to account for partial restoration of system

Who should attend

  • Product development personnel
  • Quality and Reliability personnel
  • Product/Project Managers involved in analysis of Field Data
  • Warranty Engineers
  • Plant personnel
  • Maintenance personnel
About Our Speaker(s)

Steven Wachs | Reliability Analysis SpeakerSteven Wachs
Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.... More info

 
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    Event Title: Predicting Failures of Repairable Systems
    Presenter(s): Steven Wachs

 
 
 
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