Newbuilding dry-docking is a part of the shipbuilding manufacturing process, common for vessels built on slipways. The subject of this research is steel-built vessels intended for non-restricted sea-going navigation. Based on former experience, the necessity of the dry-docking projects measurement has been noted as a managerial tool for performance estimation and project comparison. The dry-docking project is a complex task which includes the first self-propelled sea passage and the transfer of the manufacturing process to a remote place. The dry-docking result is a surveyed and coated vessel ready for sea trials and five-year service until the next dry-docking. This paper deals with a model which enables process measurement using the analytic hierarchy process (AHP) method for qualitative data related to the dry-docking places and data envelopment analysis (DEA) for quantitative data related to the vessels’ technical and cost data. The modelled data are collected from the completed dry-dockings, and the twenty-nine studied vessels represent the decision-making units (DMU) used in two-step process measurement calculations. The obtained results can distinguish the efficient DMUs, which create an efficient frontier as benchmarks or “the best practice units” in the given DMU set. For the non-efficient DMUs, the efficiency score and rate of improvements needed to reach the efficient frontier will be calculated, and the sources of inefficiency will be recognized.

中文翻译：

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使用定性和定量数据的两步制造过程测量模型—以新建船坞为例

新船干坞是造船生产过程的一部分，通常用于在滑道上建造的船舶。这项研究的主题是旨在用于非限制性海上航行的钢制船。根据以前的经验，干坞项目测量的必要性已被认为是绩效评估和项目比较的管理工具。干船坞项目是一项复杂的任务，其中包括第一条自走式海上通道以及将制造过程转移到偏远地区。干坞结果是经过检验和涂漆的船舶，准备进行试航和五年服务，直到下一次干坞为止。本文讨论了一个模型，该模型能够使用层次分析法（AHP）来处理与停靠码头有关的定性数据，并使用数据包络分析（DEA）来进行与船舶技术和成本数据有关的定量数据的过程测量。从完成的干坞中收集建模数据，研究的29艘船代表了两步过程测量计算中使用的决策单位（DMU）。获得的结果可以区分有效的DMU，从而在给定的DMU集中创建一个有效的边界作为基准或“最佳实践单位”。对于非效率的DMU，将计算效率得分和达到有效边界所需的改进率，并将识别出效率低下的原因。