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A unique, design-based approach to reliability engineering Design for Reliability provides engineers and managers with a range of tools and techniques for incorporating reliability into the design process for complex systems. It clearly explains how to design for zero failure of critical system functions, leading to enormous savings in product life-cycle costs and a dramatic improvement in the ability to compete in global markets. Readers will find a wealth of design practices not covered in typical engineering books, allowing them to think outside the box when developing reliability requirements. They will learn to address high failure rates associated with systems that are not properly designed for reliability, avoiding expensive and time-consuming engineering changes, such as excessive testing, repairs, maintenance, inspection, and logistics. Special features of this book include: A unified approach that integrates ideas from computer science and reliability engineering Techniques applicable to reliability as well as safety, maintainability, system integration, and logistic engineering Chapters on design for extreme environments, developing reliable software, design for trustworthiness, and HALT influence on design Design for Reliability is a must-have guide for engineers and managers in R&D, product development, reliability engineering, product safety, and quality assurance, as well as anyone who needs to deliver high product performance at a lower cost while minimizing system failure.
Based on deep theoretical as well as practical experience in Reliability and Quality Sciences, Robust Design Methodology for Reliability constructively addresses practical reliability problems. It offers a comprehensive design theory for reliability, utilizing robust design methodology and six sigma frameworks. In particular, the relation between un-reliability and variation and uncertainty is explored and reliability improvement measures in early product development stages are suggested. Many companies today utilise design for Six Sigma (DfSS) for strategic improvement of the design process, but often without explicitly describing the reliability perspective; this book explains how reliability design can relate to and work with DfSS and illustrates this with real–world problems. The contributors advocate designing for robustness, i.e. insensitivity to variation in the early stages of product design development. Methods for rational treatment of uncertainties in model assumptions are also presented. This book promotes a new approach to reliability thinking that addresses the design process and proneness to failure in the design phase via sensitivity to variation and uncertainty; includes contributions from both academics and industry practitioners with a broad scope of expertise, including quality science, mathematical statistics and reliability engineering; takes the innovative approach of promoting the study of variation and uncertainty as a basis for reliability work; includes case studies and illustrative examples that translate the theory into practice. Robust Design Methodology for Reliability provides a starting point for new thinking in practical reliability improvement work that will appeal to advanced designers and reliability specialists in academia and industry including fatigue engineers, product development and process/ quality professionals, especially those interested in and/ or using the DfSS framework.
A component will not be reliable unless it is designed with required reliability. Reliability-Based Mechanical Design uses the reliability to link all design parameters of a component together to form a limit state function for mechanical design. This design methodology uses the reliability to replace the factor of safety as a measure of the safe status of a component. The goal of this methodology is to design a mechanical component with required reliability and at the same time, quantitatively indicates the failure percentage of the component. Reliability-Based Mechanical Design consists of two separate books: Volume 1: Component under Static Load, and Volume 2: Component under Cyclic Load and Dimension Design with Required Reliability. This book is Reliability-Based Mechanical Design, Volume 2: Component under Cyclic Load and Dimension Design with Required Reliability. It begins with a systematic description of a cyclic load. Then, the books use two probabilistic fatigue theories to establish the limit state function of a component under cyclic load, and further to present how to calculate the reliability of a component under a cyclic loading spectrum. Finally, the book presents how to conduct dimension design of typical components such as bar, pin, shaft, beam under static load, or cyclic loading spectrum with required reliability. Now, the designed component will be reliable because it has been designed with the required reliability. The book presents many examples for each topic and provides a wide selection of exercise problems at the end of each chapter. This book is written as a textbook for senior mechanical engineering students after they study the course Design of Machine Elements or a similar course. This book is also a good reference for design engineers and presents design methods in such sufficient detail that those methods are readily used in the design.
This research is to address the design optimization of systems for a specified reliability level, considering the dynamic nature of component failure rates. In case of designing a mechanical system (especially a load-sharing system), the failure of one component will lead to increase in probability of failure of remaining components. Many engineering systems like aircrafts, automobiles, and construction bridges will experience this phenomenon.In order to design these systems, the Reliability-Based Design Optimization framework using Sequential Optimization and Reliability Assessment (SORA) method is developed. The dynamic nature of component failure probability is considered in the system reliability model. The Stress-Strength Interference (SSI) theory is used to build the limit state functions of components and the First Order Reliability Method (FORM) lies at the heart of reliability assessment. Also, in situations where the user needs to determine the optimum number of components and reduce component redundancy, this method can be used to optimally allocate the required number of components to carry the system load. The main advantage of this method is that the computational efficiency is high and also any optimization and reliability assessment technique can be incorporated. Different cases of numerical examples are provided to validate the methodology.
"This thesis focuses on developing a methodology for accurately estimating series system probability of failure. Existing methods for series system based design optimization are not that accurate because they assign reliability to each failure mode; as a result complete system reliability goes down. According to method proposed in this work, the user will assign required system reliability at the start and then optimizer will apportion reliability to every failure mode in order to meet required system reliability level. Detlevson second order upper bounds are used to estimate system probability of failure. Several examples have been shown to verify the results obtained"--Abstract, leaf iii
Structural optimization methods have been developed and applied to a variety of engineering practices. This study aims to overcome technical challenges in applying design and topology optimization techniques to large-scale structural systems with uncertainties. The specific goals of this dissertation are: (1) to develop an efficient scheme for topology optimization; (2) to introduce an efficient and accurate system reliability-based design optimization (SRBDO) procedure; and (3) to investigate the reliability-based topology optimization (RBTO) problem. First, it is noted that the material distribution method often requires a large number of design variables, especially in three-dimensional applications, which makes topology optimization computationally expensive. A multiresolution topology optimization (MTOP) scheme is thus developed to obtain high-resolution optimal topologies with relatively low computational cost by introducing distinct resolution levels to displacement, density and design variable fields: the finite element analysis is performed on a relatively coarse mesh; the optimization is performed on a moderately fine mesh for design variables; and the density is defined on a relatively fine mesh for material distribution. Second, it is challenging to deal with system events in reliability-based design optimization (RBDO) due to the complexity of system reliability analysis. A new single-loop system RBDO approach is developed by using the matrix-based system reliability (MSR) method. The SRBDO/MSR approach utilizes matrix calculations to evaluate the system failure probability and its parameter sensitivities accurately and efficiently. The approach is applicable to general system events consisting of statistically dependent component events. Third, existing RBDO approaches employing first-order reliability method (FORM) can induce significant error for highly nonlinear problems. To enhance the accuracy of component and system RBDO approaches, algorithms based on the second-order reliability method (SORM), termed as SORM-based RBDO, are proposed. These technical advances enable us to perform RBTO of large-scale structures efficiently. The proposed algorithms and approaches are tested and demonstrated by various numerical examples. The efficient and accurate approaches developed for design and topology optimization can be applied to large-scale problems in engineering design practices.
In many design problems, designers typically utilize finite element models to predict the behavior and assess the safety of a system. It is challenging to perform probabilistic analysis, and design a reliable system, because repeated finite element analyses of large models are required, and these models must be coupled with an optimizer, which is often prohibitively expensive. This thesis presents a methodology for probabilistic analysis and reliability based design optimization (RBDO) to overcome the above challenge. RBDO incorporates probabilistic reanalysis (PRRA) into the optimization process so that the optimum design has a great chance of staying in the feasible design space despite the inevitable variability in the design variables/parameters. PRRA calculates very efficiently the system reliability for many probability distributions of the design variables by performing a single Monte Carlo simulation. Another part of work integrates PRRA with two alternative methods to create a new design tool that can perform reliability based optimization efficiently. The first is Trust Region methodology and the second is a Global-Local methodology. These two methods are demonstrated and compared on a ten-bar truss structure.
The second area of this research considers the use of dynamic local surrogates, or surrogate-based agents, to locate multiple candidate designs. Surrogate-based global optimization algorithms often require search in multiple candidate regions of design space, expending most of the computation needed to define multiple alternate designs. Thus, focusing on solely locating the best design may be wasteful. We extended adaptive sampling surrogate techniques to locate multiple optima by building local surrogates in sub-regions of the design space to identify optima. The efficiency of this method was studied, and the method was compared to other surrogate-based optimization methods that aim to locate the global optimum using two two-dimensional test functions, a six-dimensional test function, and a five-dimensional engineering example.