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Optimization of Shipboard Manning Levels Using Imprint Pro Forces Module

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Technical Report,01 Jan 2013,01 Jul 2015

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Naval Postgraduate School Monterey United States

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The Improved Performance Research Integration Tool IMPRINT is a dynamic, stochastic, discrete-event modeling tool used to develop a model of the system of interest. In this project, we used the IMPRINT Pro Forces Module to build models of the crew of the Littoral Combat Ship LCS. The basic concept underlying the development of a model using the Forces module is that crewmembers spend all of their time in some sort of planned activitiesevents. In the context of the model, this term refers to activities typically occurring in the ships daily schedule e.g., specified times for meals, personal time, watch standing for crewmembers who stand watch, training, preventive maintenance, sleep, etc.. These planned activities, however, are interrupted or augmented by unforeseen emergencies and events i.e., unplanned activities to which the crew must respond and resolve such as flooding, collision, equipment casualties, etc. Phase 1 of this effort was focused on model development for naval applicationsspecifically, to validate the use of IMPRINT Pro Forces model simulations for the LCS manpower requirements Hollins and Leszczynski, 2014. This phase included two tasks. First, to develop the design concept of a model describing the manpower requirements of LCS-1 Freedom. Second, to develop the appropriate manning models in IMPRINT. Phase 1 successfully showed that IMPRINT Pro Forces could be used to estimate manning levels with regard to the distribution of crew rates and required qualifications Navy Enlisted Classifications NECs for the LCS 1 mission requirements through simulations of planned and unplanned events, based on actual data collected from the LCS crew. Building upon that work, Phase 2 further investigated the usefulness of Forces model simulations by focusing on determining which individual crewmembers should maintain particular qualifications Albrecht, Fitzsimmons, Chambers, and Schultz, 2014.

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