Predicting Product Life Using Reliability Analysis Methods

Speaker

Instructor: Steven Wachs
Product ID: 702096

Location
  • 20
  • November 2024
    Wednesday
  • 10:00 AM PT | 01:00 PM ET
    Duration: 90 Min
Achieving high product reliability has become increasingly vital for manufacturers in order to meet customer expectations amid the threat of strong global competition. Poor reliability can doom a product and jeopardize the reputation of a brand or company. Inadequate reliability also presents financial risks from warranty, product recalls, and potential litigation. When developing new products, it is imperative that manufacturers develop reliability specifications and utilize methods to predict and verify that those reliability specifications will be met. This presents a difficult challenge in many industries with short product cycles and compressed product development time frames. This webinar provides an overview of quantitative methods for predicting product reliability from data gathered from physical testing or from field data.
LIVE ONLINE TRAINING

November 20, Wednesday 10:00 AM PT | 01:00 PM ET
Duration: 90 Min

 

$199.00
One Dial-in One Attendee

$899.00
Group-Max. 10 Attendees/Location
(For multiple locations contact Customer Care)

$379.00

$449.00

$249.00
1 Person Unlimited viewing for 6 month info Recorded Link and Ref. material will be available in My CO Section 48 hrs after completion of Live training
(For multiple locations contact Customer Care)

$349.00
Downloadable file is for usage in one location only. info Downloadable link along with the materials will be emailed within 2 business days after completion of Live training
(For multiple locations contact Customer Care)

 

 

Customer Care

Fax: +1-650-362-2367

Email: [email protected]

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Why Should You Attend:

Participants will gain awareness of the 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. Participants will also learn how to calculate sample sizes for reliability testing.

Learning Objectives:

  • Understand key aspects of reliability data
  • Learn what an effective reliability goal/target looks like
  • Learn how reliability performance is typically measured (e.g. reliability statistics)
  • How to determine appropriate probability distributions to model failure data
  • How to use reliability models to predict reliability performance
  • How much data is needed to estimate or demonstrate reliability

Areas Covered in the Webinar:

  • Reliability Concepts and Reliability Data

    • Reliability in Product and Process Development
    • Unique Characteristics of Reliability Data
    • Censored Data
    • Setting Reliability Targets
  • Probability and Statistics Concepts

    • Probability Distributions (e.g. Weibull, Lognormal, etc.)
    • Reliability and Failure Probability
    • Hazard Rate
    • Mean Time to Failure
    • Percentiles
  • Assessing and Selecting Parametric Models for Failure Time Distributions

    • Probability Plotting
    • Identify the Best Distributions
  • Parametric Estimation of Reliability Characteristics

    • Weibull Analysis and Other Distributions
    • Precision of Estimates/Confidence Intervals
  • Introduction to Reliability Test Planning

    • Reliability Estimation Test Plans
    • Reliability Demonstration Test Plans

Who Will Benefit:

The target audience includes anyone with a vested interest in product quality and reliability

  • Product Engineers
  • Reliability Engineers
  • Design Engineers
  • Quality Engineers
  • Quality Assurance Managers
  • Project/Program Managers
  • Manufacturing Personnel
Instructor Profile:
Steven Wachs

Steven Wachs
Principal Statistician, Integral Concepts, Inc

Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. He 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.

Mr. Wachs is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Mr. Wachs regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.

He has an M.A. in Applied Statistics from the University of Michigan, an M.B.A, Katz Graduate School of Business from the University of Pittsburgh, 1992, and a B.S., Mechanical Engineering from the University of Michigan.

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Refund Policy

Our refund policy is governed by individual products and services refund policy mentioned against each of offerings. However in absence of specific refund policy of an offering below refund policy will be effective.
Registrants may cancel up to two working days prior to the course start date and will receive a letter of credit to be used towards a future course up to one year from date of issuance. ComplianceOnline would process/provide refund if the Live Webinar has been cancelled. The attendee could choose between the recorded version of the webinar or refund for any cancelled webinar. Refunds will not be given to participants who do not show up for the webinar. On-Demand Recordings can be requested in exchange. Webinar may be cancelled due to lack of enrolment or unavoidable factors. Registrants will be notified 24hours in advance if a cancellation occurs. Substitutions can happen any time. On-Demand Recording purchases will not be refunded as it is available for immediate streaming. However if you are not able to view the webinar or you have any concern about the content of the webinar please contact us at below email or by call mentioning your feedback for resolution of the matter. We respect feedback/opinions of our customers which enables us to improve our products and services. To contact us please email [email protected] call +1-888-717-2436 (Toll Free).

 

 

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