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This paper proposes a methodology to design production strategy based on risk analysis using an integrated organization and process simulation. A process simulator is developed to evaluate the risk emerging from the integration of an organization model, a production model, feasibility constraints of factory, and teams' production strategies. The process simulation iterates with the following procedure: (1) extract the class of available workers, facilities, and activities in a time horizon, (2) prioritize the work using parameters of production strategy, (3) allocate workers and facilities to activities under the constraints of simulation, (4) determine if each worker can work or not based on an uncertainty ratio, (5) renew the condition of all activities, workers, facilities and time. Better production strategies are searched using a random key based genetic algorithm which minimizes the average total labor cost. The designer selects a production strategy considering average total labor cost and standard deviation of total labor cost. The proposed methodology is applied to case studies of the block assembly process in a shipbuilding company. Results show that the proposed methodology can evaluate organizational performance based on total labor cost including risk. Furthermore, the case studies confirm that an adequate production strategy can be selected given the constraints of a specific factory.
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