Tools and Methodologies to Predict and Improve Product Reliability

Improving product reliability may be the primary objective of reliability analysis; yet, there are many possible reasons for collecting and analyzing reliability data. There are many examples of collecting and analyzing reliability data. This could be done to assess product reliability in the field. It could be to predict product warranty costs. It could be for estimating replacement part/spares requirements.

Other examples of collecting and analyzing reliability data include:

  • To assess the effect of a proposed design change
  • To demonstrate product reliability to customers or government agencies
  • To compare components from multiple suppliers
  • To compare components from different production periods, operating environments, or materials
  • For improving reliability through the use of laboratory experiments.

Methodologies for doing these

There is a certain overall methodology for setting reliability targets, estimating product reliability from test data and/or field data, and determining whether or not reliability targets are achieved. The intricacies of this methodology will be the content of a two-day, in person live seminar that is being organized by GlobalCompliancePanel, a leading provider of professional trainings for the regulatory compliance areas.

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Steve Wachs, who is currently a Principal Statistician at Integral Concepts, Inc., brings over 25 years of wide-ranging industry experience in both technical and management positions. To derive the benefit of hearing this experienced professional, just log on to http://www.globalcompliancepanel.com/control/globalseminars/~product_id=900409SEMINAR to register. This course has been pre-approved by RAPS as eligible for up to 12 credits towards a participant’s RAC recertification upon full completion.

Calculating sample sizes

Steve will discuss the methods for estimating the reliability of subsystems and systems. He will also show how to calculate sample sizes for reliability testing and utilize reliability models to develop forecasts of future failures (e.g. warranty forecasts).

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This course will immensely benefit anyone with an interest in product quality and reliability, such as Product Engineers, Reliability Engineers, Design Engineers, Quality Engineers, Quality Assurance Managers, Project/Program Managers, or Manufacturing Personnel.

Steve will help participants with the following:

  • Understand reliability concepts and unique aspects of reliability data
  • Understand underlying probability and statistical concepts for reliability analysis
  • Develop competency in the modeling and analysis of time-to-failure data
  • Understand reliability metrics and how to estimate and report them
  • Estimate reliability of subsystems and systems
  • Determine if reliability specifications are met (at specified confidence level) or whether design improvements are required
  • Develop competency in the planning of reliability tests (excluding ALT)
  • Analyze existing warranty data to predict future returns
  • Develop awareness of more advanced topics in Reliability

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