Automated Aircraft Maintenance Data Processing and Analytics

NSERC ARD Grant的行业合作伙伴是MHIRJ航空集团（https://mhirj.com，三菱重工-支线飞机，前身为庞巴迪公司）。支线飞机)。MHIRJ为全球支线飞机行业提供全面的关键运营、工程和客户支持解决方案。MHIRJ需要亨伯学院的应用研究援助，以解决两个互补的维护相关需求。第一个需求是自动维护数据处理系统，该系统将处理由飞机运营商（航空公司）以多种格式和不同间隔提交的维护数据。这些数据将被接收、处理、分析并作为数据库输出，用于进一步分析各个机队中飞机的个别性能；以及单个车队的整体性能如何与竞争运营商的车队的汇总和匿名视图进行比较。建议的解决方案可以显著减少MHIRJ人员管理和维护流程所需的时间和精力。只要输出在数据提交后24小时内可用，自动数据处理就不需要时间限制。第二个需求是需要一个综合分析工具，以帮助地面维护人员在航班间隔的非常短的时间内，根据每次航班的实时运行数据，做出关键的、对时间敏感的“可调度性”决策：“起飞”、“有限制地起飞”和“不起飞”。集成分析工具的设计将基于与自动维护数据处理相同的数据处理和分析算法。这将导致更一致的数据解释，提高飞机维修人员的效率，缩短飞机的周转时间，提高安全性。亨伯学院的应用研究团队将在文本数据挖掘、语言处理、机器学习、数据分析和数据库设计方面提供相关专业知识，以协助开发预期解决方案所需的软件算法和工具。该项目将提高MIHRJ的竞争力，并加强MIHRJ与亨伯学院之间的合作。

The industry partner for this NSERC ARD Grant is MHIRJ Aviation Group (https://mhirj.com, Mitsubishi Heavy Industries - Regional Jet, formerly Bombardier Inc. Regional Jet). MHIRJ provides comprehensive critical operational, engineering and customer support solutions for the global regional aircraft industry. MHIRJ needs applied research assistance from Humber College to address two complementary maintenance-related needs. The first need is for Automated Maintenance Data Processing system that will work with maintenance data submitted - in multiple formats and over varying intervals - by aircraft operators (airline companies). This data will be ingested, processed, analyzed, and outputted as databases for further analytics of the individual performance of aircraft in the individual fleets; as well as how the overall performance of individual fleets compare to an aggregated and anonymized view of the fleets of competing operators. The proposed solution can reduce significantly the time and effort required by MHIRJ personnel to administer and maintain the process. The automated data processing is not time critical as long as the output is available within 24 hours of data submission. The second need is for an Integrated Analytical Tool to assist ground maintenance crews in their critical and time-sensitive 'dispatchability' decision: 'go,' 'go with limitation,' and 'no go,' in a very narrow window of time between flights, based on real-time operational data from each flight. The design of the Integrated Analytic Tool will be based upon the same data processing and analytics algorithms developed for Automated Maintenance Data Processing. This will result in more consistent data interpretation, improved efficiency by aircraft maintenance crews, faster turn-around times of aircraft with improved safety. Humber College's applied research team will provide relevant expertise in textual data mining, language processing, machine learning, data analytics, and database design, to assist in developing software algorithms and tools necessary for the intended solutions. The project will improve the competitiveness for MIHRJ and establish a stronger collaboration between MHIRJ and Humber College.