Risk Metric for Multi‐Objective Design of Naval Ships

The DoD Risk Management Guide requires risk assessment of acquisition performance, cost, and schedule through the identification, subsequent analysis and prioritization of adverse program events based on their probability and consequences. This type of risk assessment is very important in concept exploration and design when considering new technologies, unique processes, and novel concepts.

Uncertainty associated with the design process itself and the definition and selection of specific design alternatives can also have a significant impact on performance, cost, and schedule risk. Inherent, statistical and modeling uncertainty and uncertainty because of human error, must be considered in the design process, but uncertainty analysis requires a more detailed and computationally intensive probabilistic approach. It is most appropriate for post‐exploration design optimization, after specific cost and performance goals and thresholds have been set to maximize the probability of achieving these goals.

In this paper, a two‐stage concept design strategy is proposed that uses a multi‐objective optimization and simplified risk event approach for concept exploration and a more rigorous multi‐disciplinary optimization with uncertainty for concept development. Concept exploration identifies nondominated design concepts and establishes the optimum relationship between effectiveness, cost, and risk given a broad selection of technologies and design alternatives. In this context, non‐dominated (N‐D) refers to designs with the maximum effectiveness for a given cost and level of risk. This is a global optimization design problem that considers a wide range of performance, cost and risk possibilities. Risk is defined using a separate objective attribute, an overall measure of risk (OMOR), which specifically addresses the high‐risk events associated with the selection of new technologies, processes, and concepts. With this perspective, decision‐makers may establish ratio‐nal requirements, select technologies, narrow the design space, and establish a non‐dominated concept baseline design or set of designs.

Once these early decisions are made, concept development and the remaining design phases add detail, refine requirements and reduce risk. Optimization continues into concept development, but a single objective optimization based on uncertainty analysis is used, maximizing the probability of success (POS) of satisfying cost and effectiveness thresholds and other constraints established in concept exploration.

The methodology and a simple application of the multi‐objective optimization and risk event approach are described in this paper.