Description

This course presents a comprehensive guide to new trends in System Engineering analysis, design, and development via an integrated set of concepts, principles, practices, and methodologies. Provides a common focal point for “bridging the gap” between and unifying System Users, System Acquirers, multi-discipline system engineering, and project, al, and Executive Management education, knowledge, and decision-making for developing systems, products, or services. Moreover, Addresses concepts employed in Model-Based Systems Engineering (MBSE), Model-Driven Design (MDD), Unified Modeling Language (UML) / Systems Modeling Language (SysML), and Agile/Spiral/V-Model Development such as user needs, stories, and use cases analysis specification development system architecture development User-Centric System Design (UCSD) interface definition & control system integration & test and Verification & Validation (V&V). The course highlights/introduces a new 21st Century Systems Engineering & Development (SE&D) paradigm. It also provides practices that are critical staging points for technical decision making such as Technical Strategy Development Life Cycle requirements Phases, Modes, & States SE Process Requirements Derivation System Architecture Development, User-Centric System Design (UCSD) Coordinate Systems, and Conventions. The course describes the latest research and developments in the area of reliability and systems engineering. It helps students identifying gaps in the current knowledge and presents fruitful areas for further research in the field. The course covers reliability measures, reliability assessment of multi-state systems, optimization of multi-state systems, continuous multi-state systems, new computational techniques applied to multi-state systems and probabilistic and non-probabilistic safety assessment. Cybersecurity for Systems Engineers will also be covered with Engineering Optimization: Method/Application. Various techniques will be covered related to performance analysis, safety margins, system Reliability, maintainability, and availability.
Upon completion of this course students will be able to:

• Identify, generalize and adapt methodologies for analyzing designs and systems.
• Develop and implement models and tools to enhance and optimize complex systems
• Design and conduct experiments, as well as to analyze and interpret data
• Apply and critique analysis techniques to review and construct arguments for design or operational decisions under uncertainty.
• Architect, design, implement, integrate, verify and validate complex systems
• Synthesize technical engineering discipline knowledge and whole-of-system methodologies to improve outcomes for a real-world client in a team environment.
• Design, research and defend an analysis of complex engineering problems.
• Manage system-intensive projects within cost and schedule constraints
• Manage system-intensive projects within cost and schedule constraints
• Be able to approach analysis of systems from multiple perspectives for effective design evaluation, and as means for improving and optimizing new and existing systems

Program

PhD Program

Objectives

• This course intends to help postgraduate students to develop the capability of systems thinking by introducing classical and advanced systems engineering theory, methods, and tools. After taking this course, student should be able to develop a systems engineering plan for a realistic project. Judge the applicability of any proposed process, strategy, or methodology for systems engineering using the fundamental concepts from disciplines such as probability, economics, and cognitive science. Apply systems engineering tools (e.g., requirements development and management, robust design, Design Structure Matrix) to realistic problems. Recognize the value and limitations of modeling and simulation. Formulate an effective plan for gathering and using data. Finally, know how to proactively design for and manage system lifecycle targets.