Life Data Analysis Research Articles

A New Cubic Transmuted Inverse Weibull Distribution: Theory and Applications

This paper introduces a new cubic transmutation of the inverse Weibull distribution, known as a cubic transmuted inverse Weibull distribution. The model is thought to be useful for the analysis of complex life data, modeling failure times, accessing product reliability, and many other fields like economics, hydrology, biology, and engineering. Some statistical features of the proposed distribution are explored. These include moments, generating functions, quantile functions, reliability functions, and hazard rate functions. The distribution of order statistics for the proposed cubic transmuted inverse Weibull distribution is also studied. The maximum likelihood estimation approach is used to estimate the model parameters. The effectiveness of the estimation is investigated through extensive simulation study. The suitability of the proposed distribution has been studied by using five real-life datasets. It is found that the proposed distribution is the most suitable fit for the used data sets.

The prognostic role of histomorphological subtyping in nonmetastatic papillary renal cell carcinoma after curative surgery: is subtype really irrelevant? A propensity score matching analysis of a multi-institutional real life data

Background and AimThe role of histomorphological subtyping is an issue of debate in papillary renal cell carcinoma (papRCC). This multi-institutional study investigated the prognostic role of histomorphological subtyping in patients undergoing curative surgery for nonmetastatic papRCC. Patients and MethodsA total of 1,086 patients undergoing curative surgery were included from a retrospectively collected multi-institutional nonmetastatic papRCC database. The patients were divided into 2 groups based on histomorphological subtyping (type 1, n = 669 and type 2, n = 417). Furthermore, a propensity score-matching (PSM) cohort in 1:1 ratio (n = 317 for each subtype) was created to reduce the effect of potential confounding variables. The primary outcome of the study, the predictive role of histomorphological subtyping on the prognosis (recurrence free survival [RFS], cancer specific survival [CSS] and overall survival [OS]) in nonmetastatic papRCC after curative surgery, was investigated in both overall and PSM cohorts. ResultsIn overall cohort, type 2 group were older (66 vs. 63 years, P = 0.015) and more frequently underwent radical nephrectomy (37.4% vs. 25.6%, P < 0.001) and lymphadenectomy (22.3% vs. 15.1%, P = 0.003). Tumor size (4.5 vs. 3.8 cm, P < 0.001) was greater, and nuclear grade (P < 0.001), pT stage (P < 0.001), pN stage (P < 0.001), VENUSS score (P < 0.001) and VENUSS high risk (P < 0.001) were significantly higher in type 2 group. 5-year RFS (89.6% vs. 74.2%, P < 0.001), CSS (93.9% vs. 84.2%, P < 0.001) and OS (88.5% vs. 78.5%, P < 0.001) were significantly lower in type 2 group. On multivariable analyses, type 2 was a significant predictor for RFS (HR:1.86 [95%CI:1.33–2.61], P < 0.001) and CSS (HR:1.91 [95%CI:1.20–3.04], P = 0.006), but not for OS (HR:1.27 [95%CI:0.92–1.76], P = 0.150). In PSM cohort balanced with age, gender, symptoms at diagnosis, pT and pN stages, tumor grade, surgical margin status, sarcomatoid features, rhabdoid features, and presence of necrosis, type 2 increased recurrence risk (HR:1.75 [95%CI: 1.16–2.65]; P = 0.008), but not cancer specific mortality (HR: 1.57 [95%CI: 0.91–2.68]; P = 0.102) and overall mortality (HR: 1.01 [95%CI: 0.68–1.48]; P = 0.981) ConclusionsThis multiinstitutional study suggested that type 2 was associated with adverse histopathologic outcomes, and predictor of RFS and CSS after surgical treatment of nonmetastatic papRCC, in overall cohort. In propensity score-matching cohort, type 2 remained the predictor of RFS. Eventhough 5th WHO classification for renal tumors eliminated histomorphological subtyping, these findings suggest that subtyping is relevant from the point of prognostic view.

DELTD: An R Package for Kernel Density Estimation using Lifetime Distributions

The R package DELTD is for estimating densities by asymmetrical kernels and calculating MSE. This package is to estimate densities that are free of boundary bias. The major concern of the package is to enhance its usefulness in performing inference regarding stated kernels. For this purpose, some lifetime distributions, i.e. Beta, Birnbaum-Saunders, Erlang, Gamma, and Lognormal are considered here due to their usefulness in life data analysis, where their estimated values for density estimation can also be observed. Tuna data is also presented in this package. By using these kernels, densities will be free of boundary problems. This package is a collection of asymmetrical kernels which belong to the lifetime distribution.

Life Analysis of TBC on an Aero Engine Combustor Based On In-Service Failures Data

TBC (Thermal Barrier Coatings) mostly find application in the combustion sections of aircraft turbine engines. With the demand for fuel economy and increased power, combustion temperatures are approaching the design limits of the metal alloys from which hot end components are made. Modern TBCs are required to not only limit heat transfer through the coating but to also protect engine components from oxidation and hot corrosion. When a TBC fails, it exposes the underlying substrate to very high gas temperatures and the life of the component gets reduce drastically. With a failed TBC, a component can even fail within its prescribed service life. This is an airworthiness issue. So it is essential to estimate the TBC life accurate possibly to ensure airworthiness of the aircraft at any given time. Premature failure are observed in the TBC applied over combustion section of a turboprop engine. The engine is 800 shp class and it powers a commuter aircraft. The objective of this paper is to find out mean life of the coating by life data analysis. The data has been fitted to Weibull distribution. The Weibull parameters have been discussed which highlights the dominating cause for TBC failure and hence suggestion for life improvement of TBC system has also been made. The need for TBC system redesign has been emphasized. In addition to this, it also presents a comparison between different users/ operators.

Effect of graphene nanoplatelets on fatigue performance of Glass Fiber Reinforced Composite materials based on recycled polyethylene terephthalate

Utilization of recycled polyethylene terephthalate (PET) based resins for manufacturing composites is an environment friendly and cost effective solution. This study attempts to explore the influence of graphene nanoplatelets (GPnP) addition on the fatigue performance of glass fiber reinforced composites based on recycled PET in terms of S–N Data, area of hysteresis loops during fatigue loading, fatigue life distributions, self generated temperature during fatigue loading and stiffness degradation. Incorporation of GPnP in rPET-UPR based composites brings their fatigue performance at par with virgin polyester resin based composites. Statistical analysis of fatigue life data using two parameter Weibull distribution established that GPnP addition has only marginal effect in increasing dispersion in fatigue lives.

Fatigue life analysis and damage evaluation in glass fiber reinforced composite materials based on recycled polyethylene terephthalate

Viability of recycling polyethylene terephthalate (PET) can be enhanced by increasing its usage as a matrix material in manufacturing of composite materials. Structural applications of composite materials almost always involve fatigue loading and evaluation of fatigue behaviour is essential to explore the full potential of composite materials based on recycled PET. With an aim to increase the acceptability of recycled PET based resins, fatigue performance of glass fiber reinforced composite materials based on unsaturated polyester resin derived from recycled PET (rPET-UPR) has been evaluated in the present research. Glass fiber composites laminates of stacking sequence [0/(±45)2/0]T have been fabricated using vacuum infusion process. Fatigue tests were performed at the stress ratio of 0.1, where the stress level varied from 40%–80% of the ultimate tensile strength (UTS). The results of fatigue tests show that the fatigue lives of composites based on rPET-UPR were lower as compared to virgin polyester matrix composites. However, Statistical analysis of the fatigue life data using two parameter Weibull distribution, established that there is no deleterious effect on the scatter observed in fatigue lives of these composites, as compared to composites based on virgin polyester resin. Due to higher degradation of rPET-UPR matrix as well as weak interfacial properties, 13% higher self generated temperature was observed during fatigue loading in comparison to virgin resin based composite materials. A three phase stiffness degradation curve has been observed for these composite materials indicating stiffness loss in the range of 20%–35% till the time of failure, which correlates well with the experimental damage observations. A nonuniform and rapid damage growth was observed at high-stress levels, whereas a more uniform damage zone was observed at the low-stress levels.

A Robust Design for Lifecycle Cost with Reliability Analysis Integration

Maintenance, repair, and overhaul (MRO) is the most significant cost driver over a complex engineering asset lifecycle. Therefore, high-value manufacturers are required to plan MRO occurrences to optimize the overhaul cost while achieving the desired performance. This trade-off imposes a shift towards a proactive maintenance strategy. However, creating a long-term proactive maintenance plan is challenging due to uncertainties in the performance of the asset and its critical components. Hence, this paper presents a robust design framework for the lifecycle cost estimation process by integrating reliability life data analysis. The level of data availability across the lifecycle is considered. The framework is proposed based on a literature review and the Delphi method. This study highlights that the level of robustness in the lifecycle cost estimates can be achieved by continuous feedback to the design phase and to the body of knowledge over the asset lifecycle. Moreover, this study suggests that the optimization model for the trade-off between cost and reliability should fulfil safety and environmental sustainability requirements when providing a cost-effective reliability solution.

Temperature Acceleration-Based Life Data Analysis and Acceleration Test Method for EPDM in High-Pressure Fuel System Sealing Materials for Fuel Cell Electric Vehicles

Purpose: In this study, to shorten the EC 79 test time, an accelerated test method for nonmetallic materials such as ethylene propylene diene monomer (EPDM), which constitute the major component of the high-pressure fuel system of fuel-cell electric vehicles, was studied.BRMethods: After failure mode and effect analysis, heat was selected as the accelerating stress, and an accelerated thermal-aging experiment was conducted for each temperature condition of EPDM. The acceleration of the Weibull distribution was verified from the life data analysis using the Minitab program. Further, the Arrhenius acceleration model was employed to derive acceleration factors for each temperature condition.BRResults: Using the derived acceleration factors, when the temperature was accelerated to 110,130°C, the average life expectancy was reduced by 45% and 65%.BRConclusion: If the temperature condition is accelerated, the average life of nonmetallic EPDM is effectively shortened. In further research, this result will be verified by applying an accelerated test method to major components comprising EPDM.

Reliability for Weibull Distribution using Ms-Excel

The weibull distribution is mostly used in reliability analysis life data analysis due to its versatility. Depending on the values of the parameters, the weibull distribution can be used to model a variety of life behaviors. The three parameter weibull distribution can estimate the probability of null wind speed and gives greater weight to low wind speeds. We also discuss least square method of estimation problems and hypothesis testing issues, with the emphasis on graphical methods and some weibull analysis software are also provided. The analysis is also applicable in the design stage and in-service time as well and it is not only limited to the production stage. Now, the techniques to perform the Weibull analysis process are done by statistical software programs.

Some properties of weighted survival extropy and its extended measures

We study some properties of weighted survival extropy measure. This is a shift dependent measure and put more weights to the large values of the observed random variable. Then we introduce weighted extended survival extropy and its dynamic version. Various properties of the proposed measures are obtained. Some generalized inequalities related to weighted extended survival extropy are studied. Non-parametric estimators of these measures are proposed and their asymptotic properties are investigated. The performance of the estimators is assessed through a simulation study. Finally, it is shown that weighted survival extropy measure can be used in model discrimination and as an alternative risk measure. Analysis of real life data is considered for illustration.

Local polynomial smoothing based on the Kaplan–Meier estimate

The local polynomial modeling of the Kaplan–Meier estimate for random designs under the right censored data setting is investigated in detail. Two classes of boundary aware estimates are developed: estimates of the distribution function and its derivatives of any arbitrary order and estimates of integrated distribution function derivative products. Their statistical properties are quantified analytically and their implementation is facilitated by the development of corresponding data driven plug-in bandwidth selectors. The asymptotic rate of convergence of the plug-in rule for the estimates of the distribution function and its derivatives is quantified analytically. Numerical evidence is also provided on its finite sample performance. A real life data analysis illustrates how the methodological advances proposed herein help to generate additional insights in comparison to existing methods.

Warranty data maturity—Effect of observation time on reliability prediction and the warranty management process

AbstractWarranty data analysis is a form of life data analysis and is part of the engineering and business process of assessing product reliability and predicting the number of parts failing in the field and the associated warranty cost. However, oftentimes the prediction is started early and is based only on a few months of field data, which raises a question of data maturity. As data matures and the product is operating longer in the field the prediction changes, since the failure distribution becomes the function of the observation time. Data maturation has been known as a complicating factor in warranty data analysis affecting the accuracy of prediction, however there were very few attempts to look at how the data maturity affects the failure patterns and the probability of failure as the time in the field and consequently the observation time increases.This paper discusses the causes of data maturity, presents an analytical model to assess the maturation trends and presents several case studies based on the automotive electronics warranty data. The paper analyzes the patterns of how warranty data matures as more field data becomes available and how it affects the accuracy of prediction. It also suggests the criteria of determining the levels of data maturity.

A new class of the Weibull-generalized truncated Poisson distribution for reliability and life data analysis

A new class of the Weibull-generalized truncated Poisson distribution for reliability and life data analysis

Correlates of palpitations during menopause: A scoping review.

Objective:Palpitations during peri- and post-menopause are common. It is unclear what variables are related to palpitations in peri- and post-menopausal women. The purpose of this scoping review was to summarize potential correlates of palpitations in women transitioning through menopause.Methods:The review followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Authors included English-language, full-length, peer-reviewed, cross-sectional research articles on palpitations in menopausal women published through December 18, 2021, from PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and PsycINFO searches. Following de-duplication, screening of titles and abstracts, and review of full-texts, independent reviewers extracted data on variables studied in relationship to palpitations from 84 articles and resolved discrepancies. Authors extracted data on (1) demographic, clinical, biomarker, and symptom/quality of life variables and (2) data analysis method (bivariate, multivariate). Authors classified each variable as a likely, unlikely, or unclear correlate of palpitations.Results:Articles were diverse in region of origin, sample sizes, and variables assessed in relationship to palpitations. Evidence for any one variable was sparse. Likely correlates of palpitations included race/ethnicity, lower physical activity, worse vasomotor symptoms (VMSs), worse sleep, and worse quality of life. Unlikely correlates included age, employment, education, marital status, socioeconomic status, comorbidities, body mass index, and sexual difficulties. Unclear correlates due to equivocal evidence were menopausal status, smoking, and depression. Unclear correlates due to insufficient evidence (less than three articles) included all of the assessed biomarkers, anxiety, and stress.Conclusion:Likely correlates were identified including race/ethnicity, physical activity, VMS, sleep, and quality of life. However, additional research is needed to better understand potential correlates of palpitations.

Accelerated tribological testing based life prediction of aluminium-graphite tribo composite

Electrical sliding contacts in electrical motors and generators are subjected to severe friction and wear conditions. Conventional materials such as carbon and electrographite do not have longer life due to the generation of carbon dust. This creates environmental pollution and also affects the operation of an electrical machine. Aluminium-graphite composites are well suited for such applications. However, the life of the components made out of aluminum-graphite composite is to be evaluated in order to optimize their performance at the design stage itself. Traditional life data analysis at normal usage conditions is time-consuming. In the present study, aluminum-graphite composites were manufactured through the energy-efficient microwave sintering, and the life of components was estimated using Accelerated Life Testing (ALT) procedure. The experimental wear data were analyzed using an inverse power law model. Reliability and failure rate models were developed using the time-to-failure data. Life at normal usage conditions was predicted using these models. The calculated reliability at normal usage conditions was more than five years at a 99% confidence limit.

Competing risks survival data under middle censoring—An application to COVID-19 pandemic

Survival data is being analysed here under the middle censoring scheme, using specifically quantile function modelling under competing risks. The use of middle censoring scheme has been shown to be very appropriate under the COVID-19 pandemic scenario. Cause-specific quantile inference under middle censoring is employed. Such quantile inferences are obtained through cumulative incidence function based on cause-specific proportional hazards model. The baseline lifetime is assumed to follow a very general parametric model namely the Weibull distribution, and is independent of the censoring mechanism. We obtain estimates of the unknown parameters and cause specific quantile functions under classical as well as a Bayesian set-up. A Monte Carlo simulation study assesses the relative performance of the different estimators. Finally, a real life data analysis is given for illustration of the proposed methods.

A new extended log-Weibull regression: Simulations and applications

The induction of one or more parameter(s) in parent distributions opened new doors for flexible modeling in modern distribution theory. Among well-established generalized (G) classes for flexible modeling, the exponentiated-G, Marshall-Olkin-G and odd log-logistic-G families offer induction of one additional parameter while the beta-G and Kumaraswamy-G classes offer two extra shape parameters. The Marshall-Olkin-odd-loglogistic-G (MOOLL-G) family serves as an alternative to the beta-G and Kumaraswamy-G classes. A new motivation for the MOOLL-G family for competing risk scenarios, some useful properties, and parameter estimation are addressed. The new log-MOOLL-Weibull regression is useful for analysis of real life data. The accuracy of the estimates and the residuals is addressed via Monte Carlo simulations. The presented models outperform some other well-known models.

Long-term follow-up outcomes and treatment among patients previously treated with Zizao Yangrong granules (ZYG) for egfris–related skin xerosis.

e24054 Background: Traditional Chinese medicine (TCM) has broad prospects in the treatment of targeted drugs–related dermatologic toxicity. In our previous study (ChiCTRIOR-17013498), Zizao Yangrong granules (ZYG) made effect on EGFRIs-related xerosis and improve the quality of life. However, some people still doubt that TCM could affect therapeutic benefit for patients treated with EGFRIs. Methods: Patients with EGFRIs related xerosis who underwent ZYG and vitamin E ointment from May 2016 to January 2018 were retrospectively reviewed. Survival data and quality of life data analysis were performed. Besides, patients who used ZYG for more than 8 weeks were also summarized, followed by telephone follow-up and questionnaire survey. Results: Of 68 participates randomly assigned, 54 patients were successfully followed up. Median PFS in Vitamin E Ointment plus ZYG group was 41.6 months, and that in Vitamin E Ointment group was 40.9 months, with no statistical difference (HR 0.85, 95% CI 0.48 to 1.51, P = 0.586). Subsequently, 19 patients who used ZYG for longer than 8 weeks were also included. 2 patients reported complete response, 14 patients reported partial response, and 3 patients reported no response. The overall effective rate was 84.2%. The total DLQI score of patients with long-term intervention of ZYG was 4.47±3.10. Compared with baseline DLQI score (7.00±2.91), the DLQI of patients after ZYG intervention has been significantly improved (P = 0.000). During the continuous use of ZYG treatment, incidence of adverse effects was 57.9%. Treatment-related adverse reactions were mostly mild, with no grade 3/4 adverse events. Conclusions: ZYG did not affect progression free survival of patients treated with EGFRIs. And long time-scale ZYG intervention could continuously relieve EGFRI-related xerosis and significantly improve the quality of life of patients without serious adverse effects. Clinical trial information: ChiCTRIOR-17013498.

Automation of Life Data Analysis Processes

Life data analysis is an effective statistical process to gain information on the reliability of technical facilities. The Weibull analysis is a widely-used method for modeling the probabilities of different functional failures. For its application in modern manufacturing and maintenance processes, an automation of this analysis is expedient. An exemplary process of data collection and fitting of a parametric model with continuous time scale is analyzed in this article. Its automation with different statistic software tools is described and comparatively evaluated. With the ambition of minimizing manual effort in the process, a highly automated solution was developed in this research. We describe this self-implemented solution in “R” and justify that this procedure automatizes the process more than the examined commercial implementations. The here presented work proves to be a practical real-time assistance, right now applied in aircraft maintenance.

Indicators of psychomotor development of premature infants by perinatal CNS lesion

IntroductionThe birth premature babies with hypoxic-ischemic damage to the neutral system with the subsequent development of hypoxic encephalopathy (HIE). Monitoring of the mental development and neurological status of such prematurely born children is carried out taking into account the corrected age and traditional scales.ObjectivesTo compare indicators of psychomotor development in preterm infants (gestational age &lt; 32 weeks) with and without hypoxic-ischemic encephalopathy.MethodsA prospective study was carried out in the neurological department. The study included data from infants with a gestational age of &lt; 32 weeks of gestation. Scale score immediately after birth and at corrected ages in the first, third and sixth months of life (data analysis according to Griffiths Scales).ResultsData from 95 newborns were eligible for conclusion. Of these, 67 children took part in the study, 32,8% of them were diagnosed with hypoxic-ischemic encephalopathy. In newborns with HIE gestational age at birth was less so they received parenteral nutrition for a longer time, the body weight gained during the hospital stay was less, they needed more time to switch to enteral nutrition. And only at the 3rd (80% of children) and 6th months of life, there were no statistically significant differences in psychomotor development between groups with and without hypoxic-ischemic encephalopathy.ConclusionsIn this study, it was shown that in premature infants with hypoxic-ischemic encephalopathy, normal indicators of psychomotor development and neurological status were restored at the corrected age only by 6 months of age.DisclosureNo significant relationships.