Systems Engineering and Architecting: Creating Formal Requirements presents formal requirements to help you accomplish key systems engineering and architecting activities more efficiently. The formal requirements—explicit, executable, verifiable instructions—explain how to model systems behavior, make decisions, establish natural language requirements, and improve your systems engineering and architecting processes.
Each chapter opens with case studies and lessons learned, which supply the real-world context for the formal requirements. Topics covered include how to use fuzzy logic and agents to model uncertainty and how to make decisions when confronted with ambiguity. The book also clarifies the differences between architecting and systems engineering.
Mathematical Tools for Systems Engineering and Architecting
Written in Mathematica®, each formal requirement provides a tool or serves as the algorithm for a more efficient implementation in another form. All of the requirements are available as an open source library for anyone to use, improve upon, or add to. Worked examples, illustrations, and example surveys help you apply the requirements to your own systems. The book also lists heuristics to guide you in those systems engineering or architecting activities that cannot yet be formally stipulated.
Bring More Consistency to Your Systems Development and Management
Acknowledging that much of the practice remains an art, this book brings as much scientific rigor as possible to the tasks performed by systems engineers and architects. Written by a director of engineering who led systems engineering or architecting efforts for the Space Shuttle Program, Space Control Architecture Development, and others, this book shows you how to develop more consistent processes for large-scale systems.
Motivation, Objective, Definitions and Approach
Motivations and Objective
Appendix: Mathematica in Brief
Model Systems and Architecture Behavior
Model Systems and Architectures Using Diagrams
Model Systems and Architecture Using Mathematics
Mathematically Model Uncertainty
Monitoring System or Architecture Technical Performance Measures
Make Good Decisions
Make Good Decisions by Specific Means
Appendix: Results of Testing Mathematica’s Parameter Optimization Routines
Appendix: Data for Fuzzy Logic Controller for Rocket
Establish Natural Language Requirements
Define Three Types of Natural Language Requirements: Functional, Performance, and Sought
Write Good Natural Language Requirements
Reduce Ambiguities in the Natural Language Requirement Statement
Determine the Natural Language Requirements
Maintain a Natural Language Requirement Database
Verify Requirements are Complied With
Measure Requirements Volatility
Improve an Organization’s Ability to Do Systems Engineering and Architecting
Measure Systems Engineering or Architecting Progress
Improve Processes Used
Improve Process Product Quality
Use Surveys to Determine What Is Most Urgent to Improve at Any Point in a Program
Appendix: System Engineering Effectiveness Survey
Appendix: Architecting Effectiveness Survey
Chapters include references.
Laurence Bellagamba was director of engineering for Rockwell International, Northrop Grumman, and TASC. He has led systems engineering or architecting efforts for the Space Shuttle Program, Shuttle-C, Global Positioning System, Anti-satellite System, Ground Based Missile Defense, Airborne Laser, Space Based Laser, and Space Control Architecture Development. He was awarded the NASA Certificate of Appreciation. He received BSAE, MS, and PhD degrees from the School of Aeronautics and Astronautics at Purdue University.