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Public corporations and private businesses operate in an increasingly complex, uncertain, and interconnected world. When evaluating investment decisions, business managers can no longer base their decisions primarily on expected financial return. They now must now consider a host of performance value measures (i.e., criteria) pertaining to issues such as environmental and social governance, sustainability, and stakeholder satisfaction. In addition, corporate managers must ensure that their investment decisions are aligned with the company’s vision, mission, and values in order to maintain investor confidence and protect brand image. Lastly, to be truly successful, business managers must assess the risks associated with each performance measure and manage their impacts during project implementation. This book takes a pragmatic business and economics view towards evaluating competing investment alternatives and/or capital project strategies. It provides a practical step-by- step process using a structured decision analysis framework to evaluate, understand, quantify, and measure project invesment strategies in light of multiple stakeholder objectives and success criteria. This process assists in helping stakeholders (internal and external) achieve a shared understanding of project issues and to facilitate convergence towards a mutually acceptable solution. The approach considers available choices, identified uncertainties, constraints, necessary tradeoffs, and preferences so as to identify solutions that maximize overall benefits while minimizing overall costs and risk. A real world case study is presented in the early chapters and the process steps are demonstrated through application to this case study. Recent advances in technology allow for investment strategies to be evaluated against multiple criteria within one integrated platform. This book guides the reader in performing multi-criteria decision analysis, including the use of Monte Carlo simulation, within an MS Excel environment using native MS Excel and as well as add-in programs such Palisades Decision Tools suite. Example model structures, screen shots, formulas, and output results are provided throughout the book using an illustrative case study.

Decision Analysis, Financial Analysis, Operations Research/Management Science (ORMS), Business Analytics, Systems Modeling.

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Agile Systems Engineering presents a vision of systems engineering where precise specification of requirements, structure, and behavior meet larger concerns as such as safety, security, reliability, and performance in an agile engineering context.World-renown author and speaker Dr. Bruce Powel Douglass incorporates agile methods and model-based systems engineering (MBSE) to define the properties of entire systems while avoiding errors that can occur when using traditional textual specifications. Dr. Douglass covers the lifecycle of systems development, including requirements, analysis, design, and the handoff to specific engineering disciplines. Throughout, Dr. Douglass couples agile methods with SysML and MBSE to arm system engineers with the conceptual and methodological tools they need to avoid specification defects and improve system quality while simultaneously reducing the effort and cost of systems engineering.

Systems engineering. --- Agile software development. --- SysML (Computer science) --- OMG SysML (Computer science) --- Systems Modeling Language (Computer science) --- Computer software --- Modeling languages (Computer science) --- UML (Computer science) --- Agile development (Computer science) --- Agile methods (Computer science) --- Agile processes (Computer science) --- Engineering systems --- System engineering --- Engineering --- Industrial engineering --- System analysis --- Development --- Design and construction

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Systems engineers and architects must understand how all the parts of a system work together to satisfy its requirements. SysML is a general purpose graphical modeling language used to specify, analyze, and design systems that may include hardware, software, and personnel. This book offers a practical guide for modeling systems with SysML.

Systems engineering. --- SysML (Computer science) --- OMG SysML (Computer science) --- Systems Modeling Language (Computer science) --- Computer software --- Modeling languages (Computer science) --- UML (Computer science) --- Engineering systems --- System engineering --- Engineering --- Industrial engineering --- System analysis --- Development --- Design and construction --- Information Technology --- General and Others

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A general purpose graphical modeling language used to specify, analyze, and design systems that may include hardware, software, and personnel, SysML is now being adopted by companies across a broad range of industries, including aerospace and defense, automotive, and IT system developers. This book is the bestselling, authoritative guide to SysML for systems and software engineers, providing a comprehensive and practical resource for modeling systems with SysML. Fully updated to cover newly released version 1.3, it includes a full description of the modeling language along with a quick refe

Systems engineering. --- Computer simulation. --- SysML (Computer science) --- Information Technology --- General and Others --- OMG SysML (Computer science) --- Systems Modeling Language (Computer science) --- Computer software --- Modeling languages (Computer science) --- UML (Computer science) --- Computer modeling --- Computer models --- Modeling, Computer --- Models, Computer --- Simulation, Computer --- Electromechanical analogies --- Mathematical models --- Simulation methods --- Model-integrated computing --- Engineering systems --- System engineering --- Engineering --- Industrial engineering --- System analysis --- Development --- Design and construction --- Systems engineering --- Computer simulation

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Verification and validation represents an important process used for the quality assessment of engineered systems and their compliance with the requirements established at the beginning of or during the development cycle. Debbabi and his coauthors investigate methodologies and techniques that can be employed for the automatic verification and validation of systems engineering design models expressed in standardized modeling languages. Their presentation includes a bird’s eye view of the most prominent modeling languages for software and systems engineering, namely the Unified Modeling Language (UML) and the more recent Systems Modeling Language (SysML). Moreover, it elaborates on a number of quantitative and qualitative techniques that synergistically combine automatic verification techniques, program analysis, and software engineering quantitative methods applicable to design models described in these modeling languages. Each of these techniques is additionally explained using a case study highlighting the process, its results, and resulting changes in the system design. Researchers in academia and industry as well as students specializing in software and systems engineering will find here an overview of state-of-the-art validation and verification techniques. Due to their close association with the UML standard, the presented approaches are also applicable to industrial software development.

Quality assurance. --- Quality control. --- System failures (Engineering) -- Prevention. --- Systems engineering. --- Testing. --- Systems engineering --- Expert systems (Computer science) --- UML (Computer science) --- SysML (Computer science) --- Engineering & Applied Sciences --- Computer Science --- Verification --- Validation --- Information Technology --- Software Engineering --- Unified Modeling Language (Computer science) --- OMG SysML (Computer science) --- Systems Modeling Language (Computer science) --- Engineering systems --- System engineering --- Design and construction --- Computer science. --- Computer system failures. --- Software engineering. --- Management information systems. --- Computer Science. --- Software Engineering/Programming and Operating Systems. --- Software Engineering. --- System Performance and Evaluation. --- Management of Computing and Information Systems. --- Computer software --- Modeling languages (Computer science) --- Object-oriented methods (Computer science) --- Engineering --- Industrial engineering --- System analysis --- Development --- Computer system performance. --- Information Systems. --- Computer software engineering --- Informatics --- Science --- Computer-based information systems --- EIS (Information systems) --- Executive information systems --- MIS (Information systems) --- Sociotechnical systems --- Information resources management --- Management --- Computer failures --- Computer malfunctions --- Computer systems --- Failure of computer systems --- System failures (Engineering) --- Fault-tolerant computing --- Communication systems --- Failures