Complex Systems Engineering: Theory and Practice

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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).

The chapters in this volume are derived from the work of the noted Complex Aerospace Systems Exchange (CASE) Scholars, who presented their work at the AIAA SPACE Forums in 2016 and 2017. The CASE Scholars program was begun to support the needs of practitioners facing perplexing systems challenges through the work of outstanding systems academics from engineering and the social sciences. In addition, the CASE Scholars program enabled CASE to better capture and document the well-informed intersection of users and theorists regarding system complexity aerospace/aviation challenges and possibilities.

Featured topics include:

Challenging the culture of systems engineering
Human systems
Human systems, calling upon Bayesian game theory to capture the issues of complexity management
Incremental and agile methods, with futuristic insights into optimal estimation and control
Adaptive validation and verification
The digital twin and digital thread, a critical breakthrough technology for systems engineering
The digital and physical twins and futuristic methods that deconstruct the traditional engineering V-model in favor of virtual intelligence
Cybersecurity, urging for the conceptualization of cybersecurity as a complex system
Concurrent engineering centers as a strategy for each essential phase of lifecycle governance
Teaching complexity in systems engineering, providing advocacy for the development of systems competency through specified methods
The pedagogy needed for systems engineering education, with the use of experiential learning for lessons on drones

The breadth of topics was selected to provide an enriched view of all types of systems technical, machine, and human systems to both practitioners and academics. There are many sides to every system, and this volume attempts to challenge the critical process owners of systems engineering education and practice to consider the heft of what is possible for leveraging the bright future of system complexity in aerospace and aviation.

Author(s): Shannon Flumerfelt, Katherine G. Schwartz, Dimitri Mavris, Simon Briceno
Series: Progress in Astronautics and Aeronautics
Publisher: American Institute of Aeronautics and Astronautics
Year: 2019

Language: English
Pages: 301
City: Reston

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&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