Studies have been being carried out to make production faster and more organised in the shipbuilding industry, as in other industry. The fact that automation-based works are limited in the shipbuilding industry is one of the biggest challenges encountered in block production as in other stages of shipbuilding. The blocks are time-consuming and difficult components to produce in the shipbuilding process. They are the structures formed by joining the cut metal sheets, profiles and other components. These activities are carried out at the different stations of shipyards. Labour planning is one of the crucial issues in shipbuilding. In this study, the allocation of the required capacity during the pre-production stations of the block production, namely C and D, is examined stochastically. The amount of work, revisions and worker performance under uncertainty factors to be experienced in the production process are included in the problem. A two-stage stochastic mathematical recourse model was established to determine the amount of workforce capacity requirement (man*day) of the planning period at the pre-production station depending on the factors. Scenarios are determined randomly and the near-optimum solution was tried to be obtained by the Sample Average Approximation (SAA) approach.

与其他行业一样，一直在进行研究，以使造船业的生产更快、更有组织。与造船的其他阶段一样，基于自动化的工程在造船行业中受到限制，这是块生产中遇到的最大挑战之一。在造船过程中，这些块是耗时且难以生产的组件。它们是通过连接切割的金属板、型材和其他部件形成的结构。这些活动在造船厂的不同站点进行。劳动力计划是造船业的关键问题之一。在这项研究中，随机检查了块生产的预生产站（即 C 和 D）期间所需产能的分配。工作量，问题包括在生产过程中要经历的不确定因素下的修正和工人绩效。建立两阶段随机数学追索模型，根据因素确定预生产站计划期的劳动力需求量（人*天）。场景是随机确定的，并试图通过样本平均近似 (SAA) 方法获得接近最佳的解决方案。