航空维修中的预测数据分析:文化视角

John K Wilson, Bettina Mrusek, Mark Reimann, Kenneth Witcher, Jim Solti
{"title":"航空维修中的预测数据分析:文化视角","authors":"John K Wilson, Bettina Mrusek, Mark Reimann, Kenneth Witcher, Jim Solti","doi":"10.54941/ahfe100988","DOIUrl":null,"url":null,"abstract":"The use of predictive data analytics in an aviation maintenance environment has been validated as a proven method for improving operational efficiency, safety, and inventory management. The implementation of predictive maintenance processes, however, remains challenging. While the use of predictive techniques has shown clear benefits, a willingness to adopt such practices must exist at all levels to be successful. This paper is the first in a two-part series aimed at evaluating the current perceptions of aircraft maintainers regarding the use of predictive models in scheduling maintenance and repair operations. The results will allow leaders within this industry to effectively communicate the benefits of data-driven analysis, thus improving confidence in predictive solutions. This study also highlights the challenges related to the incorporation of such approaches, including cultural barriers, and provides recommendations for effective implementation in aviation maintenance organizations.","PeriodicalId":292077,"journal":{"name":"Intelligent Human Systems Integration (IHSI 2022) Integrating People and Intelligent Systems","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predictive Data Analytics in Aviation Maintenance: A Cultural Perspective\",\"authors\":\"John K Wilson, Bettina Mrusek, Mark Reimann, Kenneth Witcher, Jim Solti\",\"doi\":\"10.54941/ahfe100988\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The use of predictive data analytics in an aviation maintenance environment has been validated as a proven method for improving operational efficiency, safety, and inventory management. The implementation of predictive maintenance processes, however, remains challenging. While the use of predictive techniques has shown clear benefits, a willingness to adopt such practices must exist at all levels to be successful. This paper is the first in a two-part series aimed at evaluating the current perceptions of aircraft maintainers regarding the use of predictive models in scheduling maintenance and repair operations. The results will allow leaders within this industry to effectively communicate the benefits of data-driven analysis, thus improving confidence in predictive solutions. This study also highlights the challenges related to the incorporation of such approaches, including cultural barriers, and provides recommendations for effective implementation in aviation maintenance organizations.\",\"PeriodicalId\":292077,\"journal\":{\"name\":\"Intelligent Human Systems Integration (IHSI 2022) Integrating People and Intelligent Systems\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Intelligent Human Systems Integration (IHSI 2022) Integrating People and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54941/ahfe100988\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intelligent Human Systems Integration (IHSI 2022) Integrating People and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54941/ahfe100988","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在航空维修环境中使用预测数据分析已被证明是提高运营效率、安全性和库存管理的有效方法。然而,预测性维护流程的实施仍然具有挑战性。虽然使用预测技术已经显示出明显的好处,但要想取得成功,必须在所有层面上都有采用这种做法的意愿。本文是两部分系列文章中的第一篇,旨在评估飞机维护人员在计划维护和维修操作中使用预测模型的当前看法。结果将使该行业的领导者能够有效地传达数据驱动分析的好处,从而提高对预测解决方案的信心。本研究还强调了与采用这些方法有关的挑战,包括文化障碍,并为航空维修组织有效实施这些方法提供了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictive Data Analytics in Aviation Maintenance: A Cultural Perspective
The use of predictive data analytics in an aviation maintenance environment has been validated as a proven method for improving operational efficiency, safety, and inventory management. The implementation of predictive maintenance processes, however, remains challenging. While the use of predictive techniques has shown clear benefits, a willingness to adopt such practices must exist at all levels to be successful. This paper is the first in a two-part series aimed at evaluating the current perceptions of aircraft maintainers regarding the use of predictive models in scheduling maintenance and repair operations. The results will allow leaders within this industry to effectively communicate the benefits of data-driven analysis, thus improving confidence in predictive solutions. This study also highlights the challenges related to the incorporation of such approaches, including cultural barriers, and provides recommendations for effective implementation in aviation maintenance organizations.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信