Collaborative Research: Collaborative Degradation Analysis for Enterprise-Level Maintenance Management via Dynamic Segmentation

协作研究：通过动态细分进行企业级维护管理的协作退化分析

• 批准号: 1536924
• 负责人: Eunshin Byon
• 金额: $ 16.33万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1536924&HistoricalAwards=false
• 关键词: Collaborative; Research; Degradation; Analysis; Enterprise

There is an emerging need for enterprise-level management in many applications where a large number of units operate, which requires thorough understanding of their degradation patterns. While recent advancements in sensing technology provide unprecedented data collection opportunities, developing the desired enterprise-level framework, however, faces several challenges. A common practice is to identify a representative degradation model that assumes the homogeneity of all units throughout their operational life. Such approaches capture average characteristics, but ignore differences among the units and the different degradation paths taken by different units. Another alternative, that of individualizing management operations for each unit, is either intractable or unrealistically costly, given the sheer number of units involved at the enterprise level. This project will lead to an implementable integrated framework for learning heterogeneous degradation processes of a large number of units and guiding the allocation of limited monitoring and maintenance resources. The results from this research will benefit a variety of US manufacturing or production enterprises that operate massive number of working units. This research aligns well with the educational efforts to prepare the nation's next-generation engineering workforce for manufacturing enterprises via integration of underrepresented undergraduate student mentoring into advanced research, K-12 outreach programs incorporating basic and advanced engineering design activities and opportunities for students to interact with field engineers in industry and to partner with international collaborators.The objective of this project is to create a collaborative prognostics and health management methodology for manufacturing enterprises. The integrative framework will model the heterogeneous degradation processes of a large number of units by investigating the differences and similarities among individual units: the population characteristics will be represented by a manageable number of canonical models forming an enterprise knowledge base, whereas the individual degradation characteristics will be captured via dynamic segmentation that models the resemblance between each unit's degradation pattern with the canonical models. The results will contribute to the following scientific advancements: 1) a new collaborative degradation modeling method which can characterize both population-level and individual-level heterogeneities in their degradation mechanism; 2) a scalable sensing method which can incorporate both statistical prognostics information and segment structure for effectively monitoring a large number of units; 3) an enterprise-level maintenance decision-making which can minimize the overall costs by exploiting the interdependency of the cost structure while conducting multi-unit repairs.

在大量设备运行的许多应用中，出现了对企业级管理的新需求，这需要彻底了解它们的退化模式。虽然传感技术的最新进展提供了前所未有的数据收集机会，但开发所需的企业级框架仍面临一些挑战。常见的做法是确定一个代表性的退化模型，该模型假设所有单元在其整个使用寿命期间具有同质性。这些方法捕获平均特征，但忽略单元之间的差异以及不同单元所采取的不同退化路径。另一种选择是对每个单位进行个性化的管理操作，但考虑到企业层面涉及的单位数量庞大，要么难以处理，要么成本高昂。该项目将形成一个可实施的综合框架，用于学习大量单元的异构退化过程并指导有限的监测和维护资源的分配。这项研究的结果将使拥有大量工作单元的美国各类制造或生产企业受益。这项研究与教育工作很好地结合起来，通过将代表性不足的本科生指导整合到高级研究中，为制造企业培养国家下一代工程劳动力，K-12 外展计划纳入基础和高级工程设计活动以及学生与其他人互动的机会工业现场工程师并与国际合作者合作。该项目的目标是为制造企业创建协作预测和健康管理方法。综合框架将通过研究各个单元之间的差异和相似性来对大量单元的异质退化过程进行建模：群体特征将由形成企业知识库的可管理数量的规范模型来表示，而个体退化特征将由可管理数量的规范模型来表示，形成企业知识库。通过动态分割来捕获，该动态分割对每个单元的退化模式与规范模型之间的相似性进行建模。研究结果将有助于以下科学进步：1）一种新的协作退化建模方法，可以表征其退化机制中的种群水平和个体水平异质性； 2）一种可扩展的传感方法，可以结合统计预测信息和分段结构，以有效监控大量单位； 3）企业级维护决策，在进行多单元维修的同时，利用成本结构的相互依赖性，最大限度地降低总体成本。