Modeling Accelerated Degradation Data for Product Reliability Improvement and Warranty Analysis

Georgia Tech Research Corporation, Atlanta GA

Investigators

Abstract

This grant supports research for deriving new methods for accelerated degradation testing, or ADT, which involves analyzing product or system degradation in various high stress environments in order to predict product lifetime or system performance. The research concentrates on existing gaps in current test methods used in industry, and works to extend these current methods to a larger domain of problems, including non standard degradation models that describe more realistic product degradation scenarios in manufacturing. Initial work is based on applied problems with vacuum fluorescent displays (VFDs), light-emitting diodes, and fiber optics manufacturing. VFD performance helps to motivate such models. Emitted electrons from its cathode serve to eliminate impurities in the vacuum, and VFD light intensity actually increases up to a certain point of time before it decreases due to age-induced degradation. Standard ADT models cannot characterize this phenomenon. Specific developments of this research include: (1) A general framework for stress dependent degradation models based on physically motivated degradation paths; (2) Building formulas for failure times of various complex (non-linear) ADT models, along with uncertainty estimates based on statistical resampling methods; (3) Combining failure time data with separate sets of degradation data to improve product lifetime estimates; and (4) Finding optimal test procedures (in terms of information gained) based on time and cost constraints associated with product development. The ADT models include (non linear) random coefficients to reflect variability between test units. Bootstrap resampling procedures are derived to ascertain uncertainty because simpler variance approximations are not generally available with such random coefficient degradation models. With degradation data, the proposed estimates of the product failure time distribution serves as a key quality measure for evaluating a company's process improvement in highly reliable products, and can help company managers decide their product warranty policy. If successful, the results of this research can strongly affect process condition changes, material selections, equipment innovations, maintenance schedule revisions and other production operation changes. Thus, the research provides valuable information for companies to improve their operation efficiency and profitability.