Reliability demonstration of a multi-component Weibull system under zero-failure assumption.

This dissertation is focused on finding lower confidence limits for the reliability of systems consisting of Wei bull components when the reliability demonstration testing (RDT) is conducted with zero failures. The usual methods for the parameter estimation of the underlying reliability functions like maximum likelihood estimator (MLE) or mean squares estimator (MSE) cannot be applied if the test data contains no failures. For single items there exists a methodology to calculate the lower confidence limit (LCL) of reliability for a certain confidence level. But there is no comparable method for systems. This dissertation provides a literature review on specific topics within the wide area of reliability engineering. Based on this and additional research work, a first theorem for the LCL of system reliability of systems with Weibull components is formulated. It can be applied if testing is conducted with zero observed failures. This theorem is unique in that it allows for different Wei bull shape parameters for components in the system. The model can also be applied if each component has been exposed to different test durations. This can result from accelerated life testing (AL T) with test procedures that have different acceleration factors for the various failure modes or components respectively. A second theorem for Ex -lifetime, derived from the first theorem, has been formulated as well. The first theorem on LCL of system reliability is firstly proven for systems with two components only. In the following the proof is extended towards the general case of n components. There is no limitation on the number of components n. The proof of the second theorem on Bx - lifetime is based on the first proof and utilizes the relation between Bx and reliability. The proven theorem is integrated into a model to analyze the sensitivity of the estimation of the Wei bull shape parameter p. This model is also applicable if the Weibull parameter is subject to either total uncertainty or of uncertainty within a defined range. The proven theorems can be utilized as the core of various models to optimize RDT plans in a way that the targets for the validation can be achieved most efficiently. The optimization can be conducted with respect to reliability, Bx -lifetime or validation cost. The respective optimization models are mixed-integer and highly non-linear and therefore very difficult to solve. Within this research work the software package LINGO™ was utilized to solve the models. There is a proposal included of how to implement the optimization models for RDT testing into the reliability process in order to iteratively optimize the RDT program based on failures occurred or changing boundary conditions and premises. The dissertation closes with the presentation of a methodology for the consideration of information about the customer usage for certain segments such as market share, annual mileage or component specific stress level for each segment. This methodology can be combined with the optimization models for RDT plans

An overview of reliability growth models and their potential use for NASA applications

An overview is provided of reliability growth literature over the past 25 years. This includes a thorough literature review of different areas of the application of reliability growth such as design, prediction, tracking/management, and demonstration. Various reliability growth models use different bases on how they characterize growth. Different models are discussed. Also, the use is addressed of reliability growth models to NASA applications. This includes the application of these models to the space shuttle main engine. For potential NASA applications, we classify growth models in two groups, which are characterized

Reliability analysis of structural ceramic components using a three-parameter Weibull distribution

Described here are nonlinear regression estimators for the three-Weibull distribution. Issues relating to the bias and invariance associated with these estimators are examined numerically using Monte Carlo simulation methods. The estimators were used to extract parameters from sintered silicon nitride failure data. A reliability analysis was performed on a turbopump blade utilizing the three-parameter Weibull distribution and the estimates from the sintered silicon nitride data

Dynamic Modeling and Statistical Analysis of Event Times

This review article provides an overview of recent work in the modeling and analysis of recurrent events arising in engineering, reliability, public health, biomedicine and other areas. Recurrent event modeling possesses unique facets making it different and more difficult to handle than single event settings. For instance, the impact of an increasing number of event occurrences needs to be taken into account, the effects of covariates should be considered, potential association among the interevent times within a unit cannot be ignored, and the effects of performed interventions after each event occurrence need to be factored in. A recent general class of models for recurrent events which simultaneously accommodates these aspects is described. Statistical inference methods for this class of models are presented and illustrated through applications to real data sets. Some existing open research problems are described.Comment: Published at http://dx.doi.org/10.1214/088342306000000349 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Practical reliability. Volume 3 - Testing

Application of testing to hardware program

A RISK-INFORMED DECISION-MAKING METHODOLOGY TO IMPROVE LIQUID ROCKET ENGINE PROGRAM TRADEOFFS

This work provides a risk-informed decision-making methodology to improve liquid rocket engine program tradeoffs with the conflicting areas of concern affordability, reliability, and initial operational capability (IOC) by taking into account psychological and economic theories in combination with reliability engineering. Technical program risks are associated with the number of predicted failures of the test-analyze-and-fix (TAAF) cycle that is based on the maturity of the engine components. Financial and schedule program risks are associated with the epistemic uncertainty of the models that determine the measures of effectiveness in the three areas of concern. The affordability and IOC models' inputs reflect non-technical and technical factors such as team experience, design scope, technology readiness level, and manufacturing readiness level. The reliability model introduces the Reliability- As-an-Independent-Variable (RAIV) strategy that aggregates fictitious or actual hotfire tests of testing profiles that differ from the actual mission profile to estimate the system reliability. The main RAIV strategy inputs are the physical or functional architecture of the system, the principal test plan strategy, a stated reliability-bycredibility requirement, and the failure mechanisms that define the reliable life of the system components. The results of the RAIV strategy, which are the number of hardware sets and number of hot-fire tests, are used as inputs to the affordability and the IOC models. Satisficing within each tradeoff is attained by maximizing the weighted sum of the normalized areas of concern subject to constraints that are based on the decision-maker's targets and uncertainty about the affordability, reliability, and IOC using genetic algorithms. In the planning stage of an engine program, the decision variables of the genetic algorithm correspond to fictitious hot-fire tests that include TAAF cycle failures. In the program execution stage, the RAIV strategy is used as reliability growth planning, tracking, and projection model. The main contributions of this work are the development of a comprehensible and consistent risk-informed tradeoff framework, the RAIV strategy that links affordability and reliability, a strategy to define an industry or government standard or guideline for liquid rocket engine hot-fire test plans, and an alternative to the U.S. Crow/AMSAA reliability growth model applying the RAIV strategy

Methods for dependability analysis of small satellite missions

The use of small-satellites as platforms for fast-access to space with relatively low cost has increased in the last years. In particular, many universities in the world have now permanent hands-on education programs based on CubeSats. These small and cheap platforms are becoming more and more attractive also for other-than-educational missions, such as for example technology demonstration, science application, and Earth observation. This new objectives require the development of adequate technology to increase CubeSat performances. Furthermore, it is necessary to improve mission reliability. The research aims at studying methods for dependability analysis conducted by small satellites. The attention is focused on the reliability, as main attribute of the dependability, of CubeSats and CubeSats missions. The work has been structured in three main blocks. The first part of the work has been dedicated to the general study of dependability from the theoretical point of view. It has been studied the dependability attributes, the threads that can affect the dependability of a system, the techniques that are used to mitigate the threads, parameters to measure dependability, and models and techniques for dependability modelling. The second part contains a study of failures occurred during CubeSats missions in the last ten years and their observed reliability evaluation have been conducted. In order to perform this analysis a database has been created. This database contents information of all CubeSats launched until December 2013. The information has been gathered from public sources (i.e. CubeSat projects webs, publications on international journals, etc.) and contains general information (e.g. launch date, objectives) and data regarding possible failures. All this information is then used to conduct a quantitative reliability analysis of these missions by means of non-parametric and parametric methods, demonstrating that these failures follow a Weibull distribution. In the third section different methods, based on the concept of fault prevention, removal and tolerance, have been proposed in order to evaluate and increase dependability, and concretely reliability, of CubeSats and their missions. Concretely, three different methods have been developed: 1) after an analysis of the activities conducted by CubeSat’s developers during whole CubeSat life-cycle, it has been proposed a wide range of activities to be conducted during all phases of satellite’s life-cycle to increase mission rate of success, 2) increase reliability through CubeSats verification, mainly tailoring international ECSS standards to be applied to a CubeSat project, 3) reliability rising at mission level by means of implementing distributed mission architectures instead of classical monolithic architectures. All these methods developed in the present PhD research have been applied to a real space projects under development at Politecnico di Torino within e-st@r program. The e-st@r program is being conducted by the CubeSat Team of the Mechanical and AeroSpace Engineering Department. Concretely, e-st@r-I, e-st@r-II, and 3STAR CubeSats have been used as test cases for the proposed methods. Moreover, part of the present research has been conducted within an internship at the European Space research and Technology Centre (ESTEC) of the European Space Agency (ESA) at Noordwijk (The Netherlands). In particular, the partially realisation of the CubeSats database, the analysis of activities conducted by CubeSat developers and statement of activities for mission rate of success increase have been conducted during the internship

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples, volume 1

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented