Activity Number:
|
29
|
Type:
|
Contributed
|
Date/Time:
|
Sunday, July 31, 2016 : 2:00 PM to 3:50 PM
|
Sponsor:
|
Quality and Productivity Section
|
Abstract #319318
|
|
Title:
|
Degradation Analysis with Measurement Errors
|
Author(s):
|
Chien-Yu Peng*
|
Companies:
|
Institute of Statistical Science, Academia Sinica
|
Keywords:
|
bootstrap ;
gamma process ;
inverse Gaussian process ;
random effect ;
Wiener process
|
Abstract:
|
Degradation models are widely used to assess the lifetime information for highly reliable products. When there are measurement errors in monotonic degradation paths, unsuitable model assumptions can lead to contradictions between physical/chemical mechanisms and statistical explanations. This study presents a L´evy degradation-based process that simultaneously considers the unit-to-unit variability, the within-unit variability and the measurement error in the degradation data. Several case studies show the advantages of the proposed models. This paper also uses a separation-of-variables transformation with a quasi-Monte Carlo-type method to estimate the model parameters and provides a simple model-checking procedure to assess the validity of model assumptions.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2016 program
|