Visual Data Analysis for Advanced Composite Materials Quality Control

先进复合材料质量控制的可视化数据分析

• 批准号: 521665-2017
• 负责人: Paulovich, Fernando
• 金额: $ 1.82万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=639300
• 关键词: Visual; Data; Analysis; Advanced; Composite

Stelia North America is a company specialized in the design and fabrication of composites structures for theaeronautic, defense and space market. In their manufacturing process, several parameters affect the quality of afinal product, from the material properties to environmental factors (temperature, humidity, etc.). To controlthe product quality and support inspections, throughout the production process different types of data arecollected and stored. Stelia has identified that if they can develop more robust manufacturing processes, theywill reduce material losses and improve the quality of their products, helping them to pursue a leadershipposition in the composite structures industry. Stelia is hindered in this goal by not being able to identify wherein their manufacturing process issues are injected. Stelia believes that it can acquire this knowledge throughdetailed analysis of the various data streams they collect. However, the very heterogeneous nature of such datais a challenge, hampering them to take full advantage of all collected information for analytical purposes. Theproposed project will investigate the application of state-of-the-art data mining and visualization techniques onthe analysis of the manufacturing parameters that affect the quality of a composites part. We will work onintegrating different sources of data to allow the execution of analytical tasks. Our goal is to understand theinfluence of the manufacturing parameters on the quality of a composite material, ultimately helping ondeveloping more robust processes.

Stelia North America是一家专门为航空、国防和航天市场设计和制造复合材料结构的公司。在其制造过程中，从材料特性到环境因素(温度、湿度等)，有几个参数会影响最终产品的质量。为了控制产品质量并支持检查，在整个生产过程中收集和存储不同类型的数据。Stelia已经确定，如果他们能够开发更强大的制造工艺，他们将减少材料损失并提高产品质量，帮助他们在复合材料结构行业寻求领先地位。Stelia在这一目标上受到阻碍，因为无法确定他们的制造工艺问题是在哪里注入的。Stelia认为，它可以通过对他们收集的各种数据流进行详细分析来获得这些知识。然而，这类数据的异质性是一项挑战，妨碍它们充分利用所有收集的信息进行分析。该项目将研究最先进的数据挖掘和可视化技术在分析影响复合材料零件质量的制造参数方面的应用。我们将致力于整合不同的数据源，以便执行分析任务。我们的目标是了解制造参数对复合材料质量的影响，最终帮助开发更强大的工艺。