Comprehensive resource presenting methods, processes, and tools relating to the digital and model-based transformation from both technical and management views
Systems Engineering for the Digital Age: Practitioner Perspectives covers methods and tools that are made possible by the latest developments in computational modeling, descriptive modeling languages, semantic web technologies, and describes how they can be integrated into existing systems engineering practice, how best to manage their use, and how to help train and educate systems engineers of today and the future. This book explains how digital models can be leveraged for enhancing engineering trades, systems risk and maturity, and the design of safe, secure, and resilient systems, providing an update on the methods, processes, and tools to synthesize, analyze, and make decisions in management, mission engineering, and system of systems.
Composed of nine chapters, the book covers digital and model-based methods, digital engineering, agile systems engineering, improving system risk, and more, representing the latest insights from research in topics related to systems engineering for complicated and complex systems and system-of-systems. Based on validated research conducted via the Systems Engineering Research Center (SERC), this book provides the reader a set of pragmatic concepts, methods, models, methodologies, and tools to aid the development of digital engineering capability within their organization.
Systems Engineering for the Digital Age: Practitioner Perspectives includes information on:
- Fundamentals of digital engineering, graphical concept of operations, and mission and systems engineering methods
- Transforming systems engineering through integrating M&S and digital thread, and interactive model centric systems engineering
- The OODA loop of value creation, digital engineering measures, and model and data verification and validation
- Digital engineering testbed, transformation, and implications on decision making processes, and architecting tradespace analysis in a digital engineering environment
- Expedited systems engineering for rapid capability and learning, and agile systems engineering framework
Based on results and insights from a research center and providing highly comprehensive coverage of the subject, Systems Engineering for the Digital Age: Practitioner Perspectives is written specifically for practicing engineers, program managers, and enterprise leadership, along with graduate students in related programs of study.
Table of Contents
1 Transforming Engineering through Digital and Model-Based Methods
1.1 Fundamentals of Digital Engineering
1.2 Mission and Systems Engineering Methods
1.3 Transforming Systems Engineering through Integrating Modeling & Simulation and the Digital Thread
1.4 Digital Engineering Visualization Technologies and Techniques
1.5 Interactive Model-Centric Systems Engineering
2 Executing Digital Engineering
2.1 Value Creation though Digital Engineering
2.2 Measuring Systems Engineering Progress Using Digital Engineering
2.3 Digital Engineering Implications on Decision Making Processes
2.4 Expedited Systems Engineering for Rapid Capability and Learning
2.5 Scaling Agile Principles to an Enterprise
2.6 System Behavior Specification Verification and Validation (V&V)
2.7 Digital Engineering Transformation: A Case Study
3 Tradespace Analysis in a Digital Engineering Ecosystem - Context and Implications
3.1 A Landscape of Trades: The Importance of Process, Ilities, and Practice
3.2 Architecting a Tradespace Analysis Framework in a Digital Engineering Environment
3.3 Set-Based Design: Foundations for Practice
3.4 Exploiting Formal Modeling in Resilient System Design: Key Concepts, Current Practice, and Innovative Approach
3.5 Augmented Intelligence: A Human Productivity and Performance Amplifier in Systems Engineering and Engineered Human-Machine Systems
4 Evaluating and Improving System Risk
4.1 Complexity and Risk in Systems Engineering
4.2 Risk and Technical Debt
4.3 Risk and System Maturity: TRLs and SRLs in Risk Management
4.4 Managing Risk
5 Model-Based Design of Safety, Security, and Resilience Systems
5.1 Concepts of trust and resilience in Cyber-Physical Systems
5.2 Introduction to STPA-Sec
5.3 The “Mission Aware” concept and meta-model for design of cyber-resilience
5.4 The “FOREST” concept and meta-model for life cycle evaluation of resilience
5.5 The Cyber Security Requirements Methodology and Meta-Model for Design of Cyber-Resilience
5.6 Implementation example: “Silverfish”
6 Analytic Methods for Design and Analysis of Missions and Systems-of-Systems
6.1 Unique Challenges in System of Systems Analysis and Architecting
6.2 System of Systems Analytic Workbench
6.3 Computational Intelligence Approach to SoS Architecting and Analysis
6.4 Unique Challenges in Mission Engineering and Technology Integration
6.5 Reference Architecture: An Integration and Interoperability Driven Framework
6.6 Mission Engineering Competency Framework
7 Applying Systems Engineering to Enterprise Systems and Portfolio Management
7.1 Central Challenges in Modeling and Analyzing Enterprises as Systems
7.2 Methods for Integrating Dynamic Requirements and Emerging Technologies
7.3 Portfolio Optimization & Management for System of Systems
7.4 Assessing Benefits of Modularity in Missions & System of Systems
8 Systems Education and Competencies in the Age of Digital Engineering, Convergence, and AI
8.1 Using the Systems Engineering Body of Knowledge
8.2 Understanding Critical Skills for Systems Engineers
8.3 Evolving University Programs on Systems Engineering
8.4 Evolving University Programs for the Other 95% of Engineers- A Capstone Marketplace
