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0 (hodnocen0 x )

EB

ONLINE

1st ed.

Reston : American Institute of Aeronautics & Astronautics, 2019

1 online resource (303 pages)

ISBN 9781624105654 (electronic bk.)

ISBN 9781624105647

Progress in Astronautics and Aeronautics Ser. ; v.256

Print version: Flumerfelt, Shanon Complex Systems Engineering Reston : American Institute of Aeronautics & Astronautics,c2019 ISBN 9781624105647

Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Introduction -- Chapter 1: Systems Thinking for Complexity in Aerospace -- 1.1 Abstract -- 1.2 The Reality of Complexity -- 1.3 Engineering from a Different Point of View -- 1.4 So, What is Systems Thinking? -- 1.5 Are We Designing the System Right or Designing the Right System? -- 1.6 Systems Thinking in Systems Engineering Practice -- 1.7 The Influence of Culture on Systems Thinking -- 1.8 Conclusion -- References -- Chapter 2: The Complexity Leverage in Human System Management -- 2.1 Introduction -- 2.2 What are Human Systems? -- 2.3 Human System Management -- 2.4 The Complexity Leverage -- 2.5 Developing Fit or Congruence in Human System Management -- 2.6 Enhancing the System of Systems Through Better Knowledge Management -- 2.7 Conceptualizing Human System Management as Organizational Sensemaking -- 2.8 Diving into the Impact of Behaviorism on Human System Management -- 2.9 The Need for Systems Competency in Human Complexity Management -- 2.10 Conclusion -- References -- Chapter 3: Challenges in Modeling of Stakeholders in Systems Engineering: From End Users to Designers, Individuals to Groups -- 3.1 The Nature of the Problem -- 3.2 The Foundation-Stakeholder Preferences: Communication, Observation, and Representation -- 3.3 The Decision: Modeling Stakeholder Decisions -- 3.4 Stakeholder Interactions: Modeling with Game Theory and Agent-Based Models -- 3.5 Stakeholder Modeling Challenges -- References -- Chapter 4: Incremental and Agile Development of Aerospace Systems: A Comparative Analysis Framework and Source List -- 4.1 Introduction -- 4.2 Descriptive Framework for Analyzing Incremental/Agile Methods -- 4.3 Model-Based Systems Engineering (MBSE) -- 4.4 MBSE Pattern-Based Systems Engineering (PBSE) and the S*Metamodel.

4.5 Agile Systems Engineering Life Cycle Management (ASELCM) S*Pattern -- 4.6 An Optimal Estimation and Control View of Managing Risk and Learning in Incremental and Agile Development -- 4.7 Conclusions and Future Evolution -- 4.8 Appendix Examples of Incremental-Agile Methods in Aerospace -- 4.9 References -- 4.10 Suggested Reading -- Chapter 5: Addressing the Complexity Challenge with Adaptive Verification and Validation -- 5.1 Introduction -- 5.2 The Nature of the Verification Challenge for Complex Systems -- 5.3 The Adaptive Verification and Validation Framework -- 5.4 Life Cycle Governance of Verification and Validation -- 5.5 Iterative Development and Model-Based Engineering in Verification and Validation -- 5.6 Formal Methods in Verification of Complex Aerospace Systems -- 5.7 Recurrent Surveillance -- 5.8 Organizational Partnerships, Conclusions, and an Action Plan for Adaptive V&amp -- V -- References -- Chapter 6: Hopes, Dreams, and Challenges of Digital Nirvana: The State of the Art and the Art of the Possible in Digital Twin and Digital Thread -- 6.1 Introduction -- 6.2 Model Descriptions and Taxonomies -- 6.3 Model-Based Systems Engineering -- 6.4 Expanding Model-Based Thinking with Digital Thread and Digital Twin -- 6.5 Model-Based Development of a Notional Weapon System -- 6.6 Challenges to Full Implementation of Digital Thread and Digital Twin -- 6.7 If Not Nirvana, Then What? -- 6.8 Conclusion -- References -- Chapter 7: Virtually Intelligent Product Systems: Digital and Physical Twins -- 7.1 Abstract -- 7.2 Introduction -- 7.3 Digital Twin -- 7.4 Physical Twin -- 7.5 Digital Twins, Physical Twins, and System Complexity -- 7.6 Digital Twin Manufacturing Use Cases -- 7.7 Digital Twin Service Use Cases -- 7.8 Digital Twin Issues -- 7.9 Conclusion -- References -- Chapter 8: Cybersecurity as a Complex Adaptive Systems Problem.

4.5 Agile Systems Engineering Life Cycle Management (ASELCM) S*Pattern -- 4.6 An Optimal Estimation and Control View of Managing Risk and Learning in Incremental and Agile Development -- 4.7 Conclusions and Future Evolution -- 4.8 Appendix Examples of Incremental-Agile Methods in Aerospace -- 4.9 References -- 4.10 Suggested Reading -- Chapter 5: Addressing the Complexity Challenge with Adaptive Verification and Validation -- 5.1 Introduction -- 5.2 The Nature of the Verification Challenge for Complex Systems -- 5.3 The Adaptive Verification and Validation Framework -- 5.4 Life Cycle Governance of Verification and Validation -- 5.5 Iterative Development and Model-Based Engineering in Verification and Validation -- 5.6 Formal Methods in Verification of Complex Aerospace Systems -- 5.7 Recurrent Surveillance -- 5.8 Organizational Partnerships, Conclusions, and an Action Plan for Adaptive V& -- V -- References -- Chapter 6: Hopes, Dreams, and Challenges of Digital Nirvana: The State of the Art and the Art of the Possible in Digital Twin and Digital Thread -- 6.1 Introduction -- 6.2 Model Descriptions and Taxonomies -- 6.3 Model-Based Systems Engineering -- 6.4 Expanding Model-Based Thinking with Digital Thread and Digital Twin -- 6.5 Model-Based Development of a Notional Weapon System -- 6.6 Challenges to Full Implementation of Digital Thread and Digital Twin -- 6.7 If Not Nirvana, Then What? -- 6.8 Conclusion -- References -- Chapter 7: Virtually Intelligent Product Systems: Digital and Physical Twins -- 7.1 Abstract -- 7.2 Introduction -- 7.3 Digital Twin -- 7.4 Physical Twin -- 7.5 Digital Twins, Physical Twins, and System Complexity -- 7.6 Digital Twin Manufacturing Use Cases -- 7.7 Digital Twin Service Use Cases -- 7.8 Digital Twin Issues -- 7.9 Conclusion -- References -- Chapter 8: Cybersecurity as a Complex Adaptive Systems Problem.

8.1 Introduction -- 8.2 Cybersecurity in the Aerospace Industry -- 8.3 Understanding Threats, Risks, and Consequences -- 8.4 Cyber Resilience -- 8.5 Guiding Principles for Dealing with Complexity -- 8.6 Conclusions -- References -- Chapter 9: Use of Concurrent Engineering Centers as a Tool for Life Cycle Governance of Complex System Design, Development, Test, and Operations -- 9.1 The Nature of the Problem -- 9.2 Life Cycle Governance -- 9.3 Concurrent Engineering -- 9.4 CEC State of the Art in Aerospace -- 9.5 Application of Concurrent Engineering to Complex System Governance -- 9.6 Challenges for CASE: Recommendations and Conclusions -- References -- Chapter 10: Learning to Master Complexity Through Aerospace Capstone Design and Senior Technical Electives with Enhanced Complex Aerospace Systems Engineering Content -- 10.1 How Complex Systems Fail -- 10.2 Mastering Complexity -- 10.3 Systems Engineering in Academia -- 10.4 Courses Descriptions and Modifications -- 10.5 Assessment, Outcomes, and Experiences -- 10.6 Conclusions and Lessons Learned -- References -- Chapter 11: Complex Aerospace Systems Engineering Education -- 11.1 Overview -- 11.2 Introduction -- 11.3 System Complexity -- 11.4 Capstone Design -- 11.5 ABET Criteria: Curricula and Design -- 11.6 Capstone Design of Complex Aircraft Systems -- 11.7 Summary and Conclusions -- References -- Index -- Supporting Materials.

Complex Systems Engineering: Theory and Practice represents state-of-the-art thought leadership on system complexity for aerospace and aviation, where breakthrough paradigms and strategies are sorely needed. The costs and consequences of current knowledge and practice gaps are substantial. In short, this problem is caused by several factors: the lack of human capacity to comprehend complexity without machine/autonomation interfaces, the rapid pace of changes in the sector, and the increasing complexity and complicatedness of systems of all types and sizes (occurring by design and by default)..

001905868

express

(Au-PeEL)EBL29191773

(MiAaPQ)EBC29191773

(OCoLC)1128832883