Trends in the Statistical Assessment of Reliability

Changes in technology have had and will continue to have a strong effect on changes in the area of statistical assessment of reliability data. These changes include higher levels of integration in electronics, improvements in measurement technology and the deployment of sensors and smart chips into more products, dramatically improved computing power and storage technology, and the development of new, powerful statistical methods for graphics, inference, and experimental design and reliability test planning. This paper traces some of the history of the development of statistical methods for reliability assessment and makes some predictions about the future

Accelerated Life Tests: Classical Methods for Design and Analysis

Accelerated life tests are used to obtain quickly information about the failure time distribution of very reliable technological products. Tests are conducted in conditions more severe than the normal operating ones with the aim of accelerating the mechanism of failure and thus shortening the life of components and materials of interest. An estimate of lifetime distribution at normal use conditions is extrapolated from data obtained at higher stresses by using appropriate statistical models, which incorporate special relationships accounting for the effect of stress on lifetime of products under study. After a brief introduction that describes motivations and objectives of accelerated testing, the following topics are addressed: • Methods for accelerating reliability tests. • Models for classical accelerated tests. • Procedures for point estimation, interval estimation, and model checking. Basic criteria for planning accelerate life tests. In this article, only classical fully parametric estimation procedures are discussed. Moreover, only models for constant stress ALT data are considered, that is, data obtained by running tests at constant stress with a single accelerating variable. All the models presented in this paper are for single failure mode: they cannot be used for products that may fail in more than one mode

Temporal trends and predictors of phthalate, phthalate replacement, and phenol biomarkers in the LIFECODES Fetal Growth Study

Background: Exposure to many phthalates and phenols is declining as replacements are introduced. There is little information on temporal trends or predictors of exposure to these newer compounds, such as phthalate replacements, especially among pregnant populations. Objective: Examine temporal trends and predictors of exposure to phthalates, phthalate replacements, and phenols using single- and multi-pollutant approaches. Methods: We analyzed data from 900 singleton pregnancies in the LIFECODES Fetal Growth Study, a nested case-cohort with recruitment from 2007 to 2018. We measured and averaged concentrations of 12 phthalate metabolites, four phthalate replacement metabolites, and 12 phenols in urine at three timepoints during pregnancy. We visualized and analyzed temporal trends and predictors of biomarker concentrations. To examine chemical mixtures, we derived clusters of individuals with shared exposure profiles using a finite mixture model and examined temporal trends and predictors of cluster assignment. Results: Exposure to phthalates and most phenols declined across the study period, while exposure to phthalate replacements (i.e., di(isononyl) cyclohexane-1,2-dicarboxylic acid, diisononyl ester [DINCH] and di-2-ethylhexyl terephthalate [DEHTP]) and bisphenol S (BPS) increased. For example, the sum of DEHTP biomarkers increased multiple orders of magnitude, with an average concentration of 0.92 ng/mL from 2007 to 2008 and 61.9 ng/mL in 2017–2018. Biomarkers of most chemical exposures varied across sociodemographic characteristics, with the highest concentrations observed in non-Hispanic Black or Hispanic participants relative to non-Hispanic White participants. We identified five clusters with shared exposure profiles and observed temporal trends in cluster membership. For example, at the end of the study period, a cluster characterized by high exposure to phthalate replacements was the most prevalent. Significance: In a large and well-characterized pregnancy cohort, we observed exposure to phthalate replacements and BPS increased over time while exposure to phthalates and other phenols decreased. Our results highlight the changing nature of exposure to consumer product chemical mixtures

Interval estimation for the two-parameter exponential distribution under progressive censoring

[[abstract]]The interval estimation of the scale parameter and the joint confidence region of the parameters of two-parameter exponential distribution under Type II progressive censoring is proposed. In addition, the simulation study for the performance of all proposed pivotal quantities is done in this paper. The criteria of minimum confidence length and minimum confidence area are used to obtain the optimal estimation. The predictive intervals of the future observation and the future interarrival times based on the Type II progressive censored sample are also provided. One biometrical example is also given to illustrate the proposed methods.[[notice]]補正完畢[[journaltype]]國外[[incitationindex]]SCI[[booktype]]紙本[[countrycodes]]NL