Providing actionable insights through interactive visual analytics is essential to effective decision making. Yet, many complex systems engineering (SE) domains still lack such tools. Design reviews are often still based on static snapshots of data, without any dynamic interaction, data curation, and view creation capabilities to answer salient analysis questions. In this study, we report on a tool called DataHawk that helps answer common questions associated with one prominent SE context, namely failure mode and effect analysis (FMEA). The tool provides powerful exploration capabilities that enable system engineers, designers, and managers to probe FMEA data from multiple starting points, build questions dynamically, and find triangulated answers using multiple views rapidly. Field results are illustrated through a usage scenario from the automotive industry and show that the tool demonstrates the needed versatility, scalability, and effectiveness for real-world engineering data.

中文翻译：

---

使用交互式可视化分析了解故障模式影响分析数据

通过交互式可视化分析提供可操作的见解对于有效决策至关重要。然而，许多复杂的系统工程 (SE) 领域仍然缺乏这样的工具。设计审查通常仍然基于数据的静态快照，没有任何动态交互、数据管理和视图创建功能来回答突出的分析问题。在这项研究中，我们报告了一种名为 DataHawk 的工具，该工具有助于回答与一个突出的 SE 上下文相关的常见问题，即故障模式和影响分析 (FMEA)。该工具提供了强大的探索功能，使系统工程师、设计师和管理人员能够从多个起点探测 FMEA 数据，动态构建问题，并使用多个视图快速找到三角答案。