Automated ENCON Assessment & Optimization Decision Support Tool
Small Business Information
IMPACT TECHNOLOGIES, LLC
200 Canal View Blvd, Rochester, NY, 14623
AbstractEnergy Conservation (ENCON) measures currently employed by Navy surface combatants require labor-intensive, time-consuming data entry from which fuel curves are generated for each ship’s propulsion plant machinery alignment. From these rudimentary curves optimal transit speeds, configurations, and refueling requirements are determined for specific operational demands and mission profiles. Impact Technologies, LLC proposes to automate this process by interfacing with ICAS and other existing shipboard information systems and use diagnostics and maintenance information to minimize fuel consumption. The automated ENCON assessment & optimization decision support tool will address all fossil fuel propulsion (gas turbines, steam turbines and diesel engines), power generation and auxiliary systems. The tool will consist of Diagnostics, Fuel Management and Maintenance modules. The Diagnostics module will track the health state of those components that use fuel and their supporting systems to provide real-time information on the impact of their current condition on fuel consumption. The Fuel Management module will automate data collection and the generation of fuel curves through open-systems architecture communication with ICAS. It will also enable underway planning by recommending an optimal machinery configuration to minimize fuel consumption based on either speed or time to destination constraints. Additionally, the Fuel Management module will provide real-time information on fuel consumption as well as optimize the load of each component based on its health condition, operating requirements and the number and condition of similar components. Moreover, fuel consumption at the component level will be monitored and trended. The third component of the decision tool is the Maintenance module that will track the maintenance actions being performed on fuel consuming systems and recommend maintenance to be performed based on current health information and from a fuel conservation standpoint. This decision support tool will function within the ICAS environment thus alleviating the need for dedicated hardware and will require very limited operator training.
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