Fundamentals of Systems Engineering - Product, Process, People and Performance

Fundamentals:

• What is a System?
• Systems Hierarchy & Complexity
• Decomposition and Encapsulation
• Practical Examples
• Physical Systems - Class, instances, objects

Design:

• Artificial x Natural System - Design Principles & Methods
• Design of Systems, Subsystems and System of Systems

Methods and Analysis:

• Lifecycle Characteristics
• Decision Gates, Lifecycle stages, Pre-concept, Concept, Development, Production, Operation, Support, Retirement
• Value Chain Overview Product and Process
• Flowing through the system
• LEAN Principles
• System Architecture Process
• Product Creation Process
• Basic sources for process managements

People and Performance:

• Perceptual Aspect - How "good" is perceived among stakeholders?
• Decision Making Theory
• Measures of Merit
• Decision Matrix and AHP
• Decision Tree - What is the "value" of a decision?

Complex Systems Theory:

• Complexity theory applied to SE
• Data, Information, Knowledge and Wisdom (DIKW)
• Five Aspects of Complexity Taxonomy
• Near-decomposable systems
• Industrial Case Studies
• Combining Methods
• SE techniques x non-SE Techniques
• RSC and Epoch-Era Analysis

At the end of the course the student should be able to:

• Identify the fundamental components of engineered systems
• Understand how products, processes, people and performance are connected for a given system
• Understanding the mission and performance concept in these systems.
• Be acquainted with state of the art literature for systems engineering.
• Apply SE techniques, with preliminary requirements, analyses and evaluation.

The student should understand the complexity of large engineering projects:

• Understanding the mapping between Form/Function of a design problem.
• Converging these basic design problem to a specific research question within engineering design.
• Filter state of art literature of methods and analyses to specific problems of their research.
• Identify these methods in real engineer systems, applying them to solve a specific problem from their research.

The course is organized with lectures on background topics, examples and exercises in class (case studies). The case studies will be solved individually or in groups and documented in a project report.