Affordability Measurement and Prediction Methods to Support Affordable Design of Ship Systems

Maximum reduction of cost occurs early in ship design when there is significant uncertainty. In this environment, development of novel ship systems means historic and probabilistic data is absent, and uncertainty based-heuristics (fuzzy systems) are necessary. The hierarchical and extendable decision tool developed in this project uses uncertainty-based heuristics (fuzzy logic/systems) to evaluate maintenance cost of ship systems. Maintenance, repair, and reconditioning (overhaul) represents a major and difficult to predict component of Total Ownership Cost (TOC). By developing a fuzzy system to address maintenance cost, new capability can be developed, not possible with current historic and parametric cost models. This project includes demonstration of decision making for maintenance, repair, and reconditioning of SSGTG's (Ship Service Gas Turbine Generators) on destroyers as an initial proof of concept. This research is conducted in collaboration with Ingalls Shipbuilding. This project also includes plans for software evaluation and development with organizational behavior in mind, and it includes provisions for interoperability with ASSET, PASS, VAMOSC, and other models. Cognition Corporation is the dominant software company in rule-based costing, and this project adds fuzzy inference to Cognition's product line.