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Without standardized construction elements such as nuts, bolts, bearings, beams, resistors and the like, the design of physical equipment is hopelessly inefficient, and engineers are continually bogged down with re-designing these elements over and over again. Emphasizing a top-down approach, this volume considers the purpose and basic features of design and how the concept of value can provide a quantitative measure of that wider interaction of the engineered object with its environment. This work also develops the domain in which functional design takes place and explores how the system concept can be embedded in that domain. It proposes a number of functional design elements and develops them in considerable detail, outlining how they can be applied as part of a coherent design framework. For greater understanding of the discussed concepts, numerous examples and analogies are included.
Probability Methods for Cost Uncertainty Analysis: A Systems Engineering Perspective, Second Edition gives you a thorough grounding in the analytical methods needed for modeling and measuring uncertainty in the cost of engineering systems. This includes the treatment of correlation between the cost of system elements, how to present the analysis to
A Text on the Foundation Processes, Analytical Principles, and Implementation Practices of Engineering Risk Management Drawing from the author's many years of hands-on experience in the field, Analytical Methods for Risk Management: A Systems Engineering Perspectivepresents the foundation processes and analytical practices
Although usually well-funded, systems development projects are often late to market and over budget. Worse still, many are obsolete before they can be deployed or the program is cancelled before delivery. Clearly, it is time for a new approach. With coverage ranging from the complex characteristics and behaviors of enterprises to the challenges the
With their ability to cross traditional boundaries and achieve a level of functionality greater than their component elements, mega-systems have helped corporations and government organizations around the world resolve complex challenges that they otherwise couldn't address with stand-alone systems. Engineering Mega-Systems: The Challenge of System
Examines classic algorithms, geometric diagrams, and mechanical principles for enhancing visualization of statistical estimation procedures and mathematical concepts in physics, engineering, and computer programming.
System of Systems Modeling and Analysis provides the reader with motivation, theory, methodology, and examples of modeling and analysis for system of system (SoS) problems. In addition to theory, this book contains history and conceptual definitions, as well as the theoretical fundamentals of SoS modeling and analysis. It then describes methods for SoS modeling and analysis, including use of existing methodology and original work, specifically oriented to SoS. Providing a bridge between theory and practice for modeling and analysis of SoS, this book includes generalized concepts and Methods, Tools, and Processes (MTP) applicable to SoS across any application domain. Examples of application f...
Along with many practical applications, Bayesian Model Selection and Statistical Modeling presents an array of Bayesian inference and model selection procedures. It thoroughly explains the concepts, illustrates the derivations of various Bayesian model selection criteria through examples, and provides R code for implementation. The author shows how to implement a variety of Bayesian inference using R and sampling methods, such as Markov chain Monte Carlo. He covers the different types of simulation-based Bayesian model selection criteria, including the numerical calculation of Bayes factors, the Bayesian predictive information criterion, and the deviance information criterion. He also provid...
Since the emerging discipline of engineering enterprise systems extends traditional systems engineering to develop webs of systems and systems-of-systems, the engineering management and management science communities need new approaches for analyzing and managing risk in engineering enterprise systems. Advanced Risk Analysis in Engineering Enterpri
Mathematical statistics typically represents one of the most difficult challenges in statistics, particularly for those with more applied, rather than mathematical, interests and backgrounds. Most textbooks on the subject provide little or no review of the advanced calculus topics upon which much of mathematical statistics relies and furthermore contain material that is wholly theoretical, thus presenting even greater challenges to those interested in applying advanced statistics to a specific area. Mathematical Statistics with Applications presents the background concepts and builds the technical sophistication needed to move on to more advanced studies in multivariate analysis, decision th...