| Abstract: | Statistically designed experiments provide a proactive means for improving reliability; moreover, they can be used to design products that are robust to noise factors which are hard or impossible to control. Traditionally, failure‐time data have been collected; for high‐reliability products, it is unlikely that failures will occur in a reasonable testing period, so the experiment will be uninformative. An alternative, however, is to collect degradation data. Take, for example, fluorescent lamps whose light intensity decreases over time. Observation of light‐intensity degradation paths, given that they are smooth, provides information about the reliability of the lamp, and does not require the lamps to fail. This paper considers experiments with such data for ‘reliability improvement’, as well as for ‘robust reliability achievement’ using Taguchi's robust design paradigm. A two‐stage maximum‐likelihood analysis based on a nonlinear random‐effects model is proposed and illustrated with data from two experiments. One experiment considers the reliability improvement of fluorescent lamps. The other experiment focuses on robust reliability improvement of light‐emitting diodes. Copyright © 2001 John Wiley & Sons, Ltd. |
