Читать книгу Reliability Analysis, Safety Assessment and Optimization - Enrico Zio - Страница 12

Engineering systems, like process and energy systems, transportation systems, structures like bridges, pipelines, etc., are designed to ensure successful operation throughout the anticipated service lifetime in compliance with given all-around sustainability requirements. This calls for design, operation, and maintenance solutions to achieve the sustainability targets with maximum benefit from system operation. Reliability, availability, maintainability and Safety criteria (RAMS) are among the indicators for measuring system functionality with respect to these intended targets.

Today, modern engineering systems are becoming increasingly complex to meet the high expectations by the public for high functionality, performance, and reliability, and with this, RAMS properties have become further key issues in design, maintenance, and successful commercialization.

With high levels of RAMS being demanded on increasingly complex systems, the reliability assessment and optimization methods and techniques need to be continuously improved and advanced. As a result, many efforts are being made to address various challenges in complex engineering system lifecycle management under the global trend of systems integration. Mathematically and computationally, the reliability assessment and optimization are challenged by various issues related to the uncertain, dynamic, multi-state, non-linear interdependent characteristics of the modern engineering systems and the problem of finding optimal solutions in irregular search spaces characterized by non-linearity, non-convexity, time-dependence and uncertainty.

In the evolving and challenging RAMS engineering context depicted above, this book provides a precise technical view on system reliability methods and their application to engineering systems. The methods are described in detail with respect to their mathematical formulation and their application is illustrated through numerical examples and is discussed with respect to advantages and limitations. Applications to real world cases are given as a contribution to bridging the gap between theory and practice.

The book can serve as a solid theoretical and practical basis for solving reliability assessment and optimization problems regarding systems of different engineering disciplines and for further developing and advancing the methods to address the newly arising challenges as technology evolves.

Reliability engineering is founded on scientific principles and deployed by mathematical tools for analyzing components and systems to guarantee they provide their functions as intended by design.

On the other hand, technological advances continuously bring changes of perspectives, in response to the needs, interests, and priorities of the practical engineering world. As technology advances at a fast pace, the complexity of modern engineered systems increases and so do, at the same time, the requirements for performance, efficiency, and reliability. This brings new challenges that demand continuous developments and advancements in complex system reliability assessment and optimization.

Therefore, system reliability assessment and optimization is inevitably a living field, with solution methodologies continuously evolving through the advancements of mathematics and simulation to follow up the development of new engineering technology and the changes in management perspectives. For this, advancements in the fields of operations research, reliability, and optimization theory and computation continuously improve the methods and techniques for system reliability assessment and optimization and for their application to very large and increasingly complex systems made of a large number of heterogeneous components with many interdependencies under various physical and economic constraints.

Within the ongoing efforts of development and advancement, this book presents an overview of methods for assessing and optimizing system reliability. We address different types of system reliability assessment and optimization problems and the different approaches for their solutions. We consider the development and advancement in the fields of operations research, reliability, and optimization theory to tackle the reliability assessment and optimization of complex systems in different technological domains.

The book is directed to graduate students, researchers and practitioners in the areas of system reliability, availability, maintainability and Safety (RAMS), and it is intended to provide an overview of the state of knowledge of and tools for reliability assessment and system optimization. It is organized in three parts to introduce fundamentals, and illustrate methods and applications.

The first part reviews the concepts, definitions and metrics of reliability assessment and the formulations of different types of reliability optimization problems depending on the nature of the decision variables and considering redundancy allocation and maintenance and testing policies. Plenty of numerical examples are provided to accompany the understanding of the theoretical concepts and methods.

The second part covers multi-state system (MSS) modeling and reliability evaluation, Markov processes, Monte Carlo simulation (MCS), and uncertainty treatment under poor knowledge. The reviewed methods range from piecewise-deterministic Markov processes (PDMPs) to belief functions.

The third part of the book is devoted to system reliability optimization. In general terms, system reliability optimization involves defining the decision variables, the constraints and the single or multiple objective functions that describe the system reliability performance and involves searching for the combination of values of the decision variables that realize the target values the objective functions. Different formulations and methods are described with precise mathematical details and illustrative numerical examples, covering mathematical programming, evolutionary algorithms, multi-objective optimization (MOO) and optimization under uncertainty, including robust optimization (RO).

Applications of the assessment and optimization methods to real-world cases are also given, concerning for example the reliability of renewable energy systems. From this point of view, the book bridges the gap between theoretical development and engineering practice.