OC Curve with Hypergeometric Method


The operating characteristic curve is used to understand lot sampling plan. It graphically provides a relationship between the unknown lot’s defect rate (or total) and the probability of the specific sampling plan to accept the lot. Very good plans discriminate between good and bad lots. Poor plans may accept bad lots or reject good lots to easily. Continue reading

Root cause knowledge and models


Two short questions to evaluate your knowledge of failure mechanisms (root causes) and common reliability models. The answers will be posted in a comment, later.

Which of the following failure root causes is most likely NOT due to power line variation (electronic based product)?

A. Circuit design margin exceeded
B. Power dissipation
C. In-rush current response
D. Mechanical fatigue Continue reading

Sequential Sampling by Attributes


There a few different ways to sample a lot (or group) of material to determine if it has an acceptably low failure rate (or proportion that are considered ‘bad’). The following is an example for the sequential sampling method, which happens to be rather efficient by generally using the fewest samples for the same risk protection.. Continue reading

life testing question


Hi Fred,

I would take this oppportunity to ask the reliability guru about bath tub curve for hardware reliability. I am running 27 units for life test for a million cycles around 555 hours. I have one failure at 300,000 cycles and the rest of the units are running fine. Would this be classified as a early life failure? Also how do i make a determination of when the early life failure time interval ends and constant failure rate starts in this example based on failure rate of remaining units? Thanks. Continue reading

Extended bogey testing


Reaching for a goal may include taking some risks. In reliability testing we are often limited by the number of samples available for testing. And, in the case where time is available or the acceleration factor is high we can take advantage of testing longer. Continue reading