This paper presents a procedure model that allows for a systematic analysis of execution risk in ship production by using stochastic risk simulation. Hence, planners can increase the depth of production planning to reduce disruptions and delays even with insufficient information density. The derived four-step model was then applied to the planning process at a German shipyard. Effects and probabilities of risks were estimated using stochastic distribution functions for two exemplary work packages in outfitting. Simulating the risk profiles for all work steps, the critical work steps and accordingly proposed planning tasks to increase the depth of production planning were identified. The application showed altogether that the Monte Carlo method can be used to mitigate the overall execution risk. In addition to increasing objectivity in the production planning process, the approach offers automation possibilities for future use cases and integration into planning software.

本文提出了一个程序模型，允许使用随机风险模拟对船舶生产中的执行风险进行系统分析。因此，即使信息密度不足，规划人员也可以增加生产规划的深度，以减少中断和延误。然后将得出的四步模型应用于德国造船厂的规划过程。使用随机分布函数对舾装中的两个示例性工作包估计了风险的影响和概率。模拟所有工作步骤的风险概况、关键工作步骤以及相应提出的计划任务，以增加生产计划的深度。该应用程序总体表明蒙特卡罗方法可以用来降低整体执行风险。除了提高生产规划过程的客观性之外，该方法还为未来用例和集成到规划软件中提供了自动化的可能性。