# Quantitative Set-Based Design to Inform Design Teams
## 2 Set-Based Design
### Quantitative Set-Based Design with System Design Teams
\begin{table}
\begin{tabular}{c c} \hline \hline
**Role** & **Responsibilities** \\ \hline Decision Authority/Project Manager & Make decisions, answer for the successes or failures of the project, and communicate with stakeholders \\ \hline Stakeholders & Provide insight into project needs and requirements \\ \hline System Analysts & Work with system designers and engineers to gather relevant models to develop and analyze the integrated model to provide information to the decision authority \\ \hline System Architects & Develop overall system architecture, concepts, and models \\ \hline Subsystem Designers & Develop subsystem designs and models \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Roles and Responsibilities of Team-Based Set-Based Design Process. Figure 6: Quantitative Set-Based Design Process Swim Lane. Systems analysts use this integrated model to uniformly generate alternatives based upon the desired decision variables in the order of hundreds of thousands of alternatives by using Monte Carlo simulation. Based on the generated alternatives and the integrated models, the systems analysts identify and define the set-drivers which define design sets in the cost vs. value tradespace. As new information is provided, the designers and analysts refine the decision options and the models. All feasible sets should be retained in the model in case uncertainty resolution determines that the previous most promising sets are infeasible, which allows analysts to return to these sets. This process is continued until the system architects, subsystem designers and systems analysts agree with the tradespace, which is sent to the decision authorities to obtain approval prior to design selection. If the tradespace is not approved, the decision authority informs the stakeholders of issues, such as requirements issues, who then may update the requirements. System analysts then repeat the integrated model refinement through tradespace evaluation processes until the tradespace is resent to the decision authority for approval. Once approved, system analysts evaluate and identify the most promising sets for uncertainty resolution. At this point, the system architects and subsystem designers provide higher fidelity models and develop prototypes to resolve uncertainty and inform set selection. Resolving uncertainty is key for any SBD process. These higher fidelity models and prototypes help increase the detail of the system as development continues. This aligns with [PERSON] et al. 's [PERSON] et al. (2018) elements to \"establish feasibility\". Any changes require an update to the integrated model to repeat the integrated model refinement through set evaluation/selection processes. Ultimately, this process converges to a few points, which are presented to the decision authority in a tradespace. The decision authority selects a final design to move to production. A key aspect of this process is the ability to efficiently revise and integrate updated design information from designers, results from models and simulations, and requirements from stakeholders, without incurring significant added delays or costs in the design process. Our process accomplishes this through the use of integrated MBE methodologies, maintaining numerous potential design alternatives, and delaying design decisions until uncertainty is adequately resolved. The result of this quantitative SBD process is the development of a Pareto optimal set of alternatives, presented to the decision authority for final selection and approval.