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.

在许多单位运行的应用中，有新兴的企业级管理需要彻底了解其退化模式。尽管最新的传感技术进步提供了前所未有的数据收集机会，但开发了所需的企业级框架，但面临着几个挑战。一种常见的做法是确定一个代表性退化模型，该模型在整个运营生活中都假定所有单位的同质性。这种方法捕获了平均特征，但忽略了单位之间的差异以及不同单位采取的不同降解路径。鉴于企业级别涉及的单位数量，每个单位的个性化管理操作的个性化管理操作是棘手或不切实际的替代方法。该项目将导致一个可实施的集成框架，用于学习大量单元的异质退化过程，并指导有限监视和维护资源的分配。这项研究的结果将使运营大量工作单位的美国各种制造业或生产企业受益。这项研究与教育努力非常吻合，以准备全国的下一代工程劳动力，通过整合代表性不足的本科生指导，纳入高级研究，K-112外展计划包括基本和高级工程设计活动，并结合了基本和高级工程设计活动，并提供了与国际合作者互动的学生，以与国际合作伙伴进行互动。整合框架将通过研究各个单元之间的差异和相似性来建模大量单元的异构降解过程：人口特征将由形成企业知识基础的可管理数量的大量规范模型来表示，而单个降级特征将通过动态分离来模型，以使每个单元之间的模型降低了单元的模型。结果将有助于以下科学进步：1）一种新的协作降级建模方法，可以在其降解机制中表征人口级和个体级别的异质性； 2）一种可扩展的传感方法，它可以合并统计预后信息和段结构，以有效监视大量单元； 3）企业级维护决策，可以通过在进行多单元维修时利用成本结构的相互依赖性来最大程度地降低整体成本。