Complex Aerospace Systems Exchange (CASE)

CASE Mission

To research, understand, and educate on increasingly complex aerospace and astronautics systems and system of systems (SoS) through their entire lifecycle and to prepare for complex emergent system behavior in these systems with the introduction of artificial intelligence (AI) and machine learning (ML).

 The issues that are driving CASE:

• Aerospace and astronautic systems are increasing in complexity and information requirements.
• System of systems integration is becoming more tightly coupled.
• Artificial intelligence (AI), machine learning (ML), and autonomous systems will dramatically increase systems complexity by enabling true system emergent behavior.
• New technological concepts and capabilities are coming online that can help address system complexity (M&S, Digital Twins, AI, VR, AR, ML).
• Computing, storage, and communications technologies are increasing at exponential rates.
• Risk of increasingly costly system failures, project escapes, project delays, and project cost/lifecycle cost overruns have increased.
• Systems engineering has primarily focused on the development phase and is virtually nonexistent in execution phases (manufacturing and operations).
• Systems engineering is too often systems accounting.
• Cultural issues are as important a factor as technological issues.
• The economic requirement for all organizations, both non-governmental and governmental, is to be substantially and increasingly more effective and efficient even as system complexity increases.

 The topics CASE focuses on are:

• Complex and complex adaptive systems in aerospace and astronautic contexts
• Methods and approaches for dealing with complexity in engineering, manufacturing, and operations/sustainment endeavors
• Digital twins and other model-based approaches for complex and complex adaptive/emergent systems
• AI and machine learning as complex adaptive/emergent systems
• AI and machine learning as approaches for dealing with complexity
• Training/education and curricula for complexity
• Complexity-related workforce issues
• The role of information as a value creator in both economic and resource effectiveness and efficiency of complex systems

 The approaches and resources that CASE employs are:

• Presentations, workshops, and papers sessions at AIAA events
• Educational/training courses
• CASE website and repository
• Presentation materials
• Videos
• Curated information and research resources for both industry practitioners and academic researchers
• CASE Scholar program
• CASE books