ASQ RRD series webinar: Calculate Reliability with No Recorded Failures (“Zero Failures”)

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ASQ RRD series webinar: Calculate Reliability with No Recorded Failures (“Zero Failures”)

Presented by Tim Adams
Thursday, January 11, 2024 12:00 PM – 1:00 PM
(UTC-04:00) Eastern Time (US & Canada)

Register for webinar

https://asq.webex.com/weblink/register/r3c3d19fa587f8a5d00f08e28748947d5

Agenda
This presentation for the practitioner provides methods with an illustrated Microsoft Excel tool to calculate reliability when the life-data set contains no recorded failures (zero Failures). The methods address both types of data (discrete and continuous) and both types of statistics (classical and Bayesian).

The desired outcome is: Given life data with no failures and the zero-failure Excel tool, calculate reliability, interpret the result, and describe the method(s) used.

The prerequisites are familiarity (not mastery) with the following concepts (jargon): point estimate, interval estimate, confidence limit, one-sided confidence bound, probability distribution, probability density function, Bayesian inference, and Bayesian’s prior distribution and likelihood function that make the posterior distribution.

The following probability distributions are used in the methods based on classical statistics: (1) Discrete data: Binomial uses F-distribution, Beta Inverse, (2) Continuous data: Exponential uses Chi-Square, and (3) Discrete data or continuous data: Informal-Bayesian Weibull distribution (Weibayes is a special case).

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Upcoming Webinars

ASQ RRD series webinar: Calculate Reliability with No Recorded Failures (“Zero Failures”)

ASQ RRD series webinar: Calculate Reliability with No Recorded Failures (“Zero Failures”) Presented by Tim AdamsThursday, January 11, 2024 12:00 PM – 1:00 PM(UTC-04:00) Eastern Time (US & Canada) Register for webinar https://asq.webex.com/weblink/register/r3c3d19fa587f8a5d00f08e28748947d5 AgendaThis presentation for the practitioner provides methods with an illustrated Microsoft Excel tool to calculate reliability when the life-data set contains no

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