GOALI/Collaborative Research: Event-Log-Based Failure Prediction and Maintenance Service for After-Sales Engineering Systems

GOALI/协作研究：售后工程系统基于事件日志的故障预测和维护服务

• 批准号: 0757683
• 负责人: Shiyu Zhou
• 金额: $ 17.33万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-15 至 2011-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0757683&HistoricalAwards=false
• 关键词: GOALI; Collaborative; Research; Event; Log

GOALI/Collaborative Research: Event-Log-Based Failure Prediction and Maintenance Service for After-Sales Engineering SystemsPrinciple Investigators: Shiyu Zhou and Yong ChenABSTRACTThe objective of this collaborative research project is to test if the system event logs contain enough information to enable statistically sound and accurate prediction of the occurrence of failure events, and if yes, establish a generic event log analysis methodology for failure prediction and condition-based optimal maintenance of after-sales engineering systems. With the rapid development of information technology, an abundance of data that record the events occurred in a system (e.g., machine activities, critical system failures, operator/user actions, task status) are now collected automatically when the system is in use. Targeting the profusion of event logs, this research consists of four components: (1) fitting a system survival model using event logs to quantify the associations between various system events and the key failure event; (2) monitoring discrete events sequence to statistically test if the survival model fitted from historical data can fully represent the present system characteristics; (3) developing robust condition-based service policy based on the survival model and Semi-Markov decision processes; and (4) implementing and validating the established methodology for maintenance service of medical imaging diagnostic systems at the healthcare unit of General Electric company.If successful, this research will advance fundamental knowledge in the planning and control of maintenance service operations for after-sales equipment by fully exploiting the current data-rich environment. The results of this research will help after-sales service industry to evolve from ad hoc experience-based operations into efficient optimized operations. In addition, the interdisciplinary nature of this collaborative research project can provide students a unique opportunity to obtain training in reliability, operations research, data mining, and statistics. Given the ubiquitous existence of system event logs, the established methodologies are potentially applicable to a broader spectrum of after-sales service applications such as manufacturing, communication, and computer network systems.

目标/协作研究：针对售后工程系统的基于事件的失败预测和维护服务人员：Shiyu Zhou和Yong Chenabstracts此协作研究项目的目标是测试系统事件日志是否包含足够的信息，以启用统计上的正当和准确预测失败事件的典型预测，并建立失败事件的预测，并建立了一般的事件，并构建了综合的方法，并构建了综合的方法，并建立了综合的方法。售后工程系统。随着信息技术的快速开发，现在在系统中使用系统中会自动收集大量记录事件发生的数据（例如，机器活动，关键系统失败，操作员/用户操作，操作员/用户操作，任务状态）。针对事件日志的范围，该研究由四个组成部分组成：（1）使用事件日志拟合系统生存模型，以量化各种系统事件与关键故障事件之间的关联； （2）监视离散事件序列以统计测试是否符合历史数据的生存模型是否可以完全表示当前的系统特征； （3）基于生存模型和半马尔科夫决策过程制定基于稳健的条件服务政策； （4）实施和验证通用电气公司医疗保健部门的医学成像诊断系统维护服务的既定方法。这项研究的结果将帮助售后服务行业从基于经验的经验运营发展为有效的优化运营。此外，该协作研究项目的跨学科性质可以为学生提供独特的机会，以获得可靠性，运营研究，数据挖掘和统计的培训。鉴于系统事件日志的普遍存在，已建立的方法可能适用于更广泛的售后服务应用程序，例如制造，通信和计算机网络系统。