Learn the fundamentals of quantitative methods in systems engineering and determine when, where, and how to employ these methods and techniques. The curriculum provides learners with an overview of design space exploration using models, as well as methods for analyzing and presenting the output of a model. A number of tradespace models will be presented and exercised as case studies.
- Define the criteria and decisions to be answered with quantitative analysis.
- Evaluate concept alternatives in order to recommend a preferred alternative.
- Structure a trade study.
- Identify the multiple key cost and benefit criteria that frame a system decision opportunity.
- Construct a value hierarchy for a stakeholder/beneficiary/decision-maker to inform system design decisions.
- Articulate the core concepts of value-based thinking.
- Choose the relevant axes and representations for a tradespace.
- Interpret the results of a tradespace.
- Identify the fuzzy Pareto front in a tradespace.
- Perform a sensitivity analysis.
- Critique a decision analysis model by identifying sources of uncertainty and variation.
- Identify the core tenets of MBSE and the situations in which it is recommended.
- Distinguish the differences between MBSE and traditional systems engineering.
- Choose an appropriate scope, define the purpose, and define the approach for an MBSE project.
- Describe the intent and basic structure of SysML, and interpret a simple SysML model.
- Critique a project’s implementation of MBSE using a set of criteria.
- Build a model management plan.
- Reference existing industry examples of MBSE to anchor choices about the scope of MBSE to undertake, and communicate potential approaches using industry examples as signposts.
- Enumerate the purposes for which models are created in engineering and evaluate the success of modeling for those purposes against your own career experience.
- Describe a potential model development process, leading to models of increasing levels of fidelity.
- Demonstrate through examples how models are used to make decisions in engineering and how models can be used for optimization, including the definition of design variables, fixed parameters, objective functions and constraints.
- Evaluate the credibility and fidelity of existing models using a set of clear criteria.
- Evaluate and explain whether it is better to pursue a single model or an ensemble of models in support of a specific problem/decision. This includes the resolution of conflicts when multiple models provide contradictory results.
- Explain the basic principles of combining subsystem models together into a system model in a multidisciplinary computational environment.
- Understand the basic principles of verifying and validating models.
- Examine the tradeoffs between the use of physical and virtual prototypes for system verification, validation, and testing. Decide when to invest in additional modeling versus additional physical testing of systems.
- Contrast several definitions of system architecture and construct a personal definition from your career examples.
- Differentiate systems thinking from other kinds of "thinking;" define a system, and articulate examples of things that are and are not systems. Apply system thinking to provide a perspective on a given project.
-Describe the architecture of systems and identify both architectural decisions and non-architectural decisions.
- Define and illustrate the system boundary and use it to identify system interfaces.
- Identify the constituent elements in architecture representations and place these in the context of the overall documentation of the system.
- Provide constructive criticism on the system architecture representations of others, including checking for completeness and consistency.
- Articulate more solution-neutral and less solution-neutral framings of a problem, and evaluate how solution-neutral to be for a given problem.
- Construct a design DSM, either by analyzing the design or by converting a graph of the system.
- Construct a process DSM and identify how it is different from a design DSM.
- Given a DSM, apply a sequencing algorithm to sort the components into modules or to sort tasks into groups.
- Describe rework and articulate the principles by which an analysis of change propagation could be conducted from a database of changes.
- Define the role of the architect and the stakeholders with whom the architect should work.
- Define the deliverables of the architect, with references to architectural frameworks and your career examples.