Collaborative Research: Quantitative Reliability Prediction in Early Design Stages

合作研究：早期设计阶段的定量可靠性预测

• 批准号: 1301075
• 负责人: Rong Pan
• 金额: $ 24.02万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-01 至 2017-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1301075&HistoricalAwards=false
• 关键词: Collaborative; Research; Quantitative; Reliability; Prediction

The objective of this collaborative research project is to predict product reliability in the earliest design stages, such as concept design. The prediction is based on information gathered from a variety of sources such as previous components and products, expert opinions, early prototype testing, and simulations. The project uses a Bayesian framework that aggregates and processes uncertain information. Quantifying product reliability in early design stages helps reduce risk and avoid costly and unnecessary design changes. This project uses a graphical model of probabilities to represent system reliability and a combination of subjective and objective information, using reliability-related data that are scattered, in different formats, at different levels of details, from various sources. Pulling together all this data allows for more accurate reliability prediction, leading to more effective actions identified early to prevent potential failures or reduce their likelihood. If successful, this project will improve design practices for all kinds of products, because reliability is a core element of product performance and directly determines customer satisfaction, product market share, and product safety. Specifically, this project will advance engineering design theory and methodology and expand the scope of reliability engineering. By quantitatively predicting product reliability early, the project provides engineers with a better way to achieve high reliability with reduced cost.

该合作研究项目的目标是在最早的设计阶段（例如概念设计）预测产品的可靠性。该预测基于从各种来源收集的信息，例如以前的组件和产品、专家意见、早期原型测试和模拟。该项目使用贝叶斯框架来聚合和处理不确定信息。在早期设计阶段量化产品可靠性有助于降低风险并避免成本高昂且不必要的设计变更。该项目使用概率的图形模型来表示系统可靠性以及主观和客观信息的组合，使用来自不同来源、以不同格式、不同细节级别分散的可靠性相关数据。将所有这些数据汇总在一起可以进行更准确的可靠性预测，从而尽早发现更有效的行动，以防止潜在故障或降低其可能性。如果成功，该项目将改善各类产品的设计实践，因为可靠性是产品性能的核心要素，直接决定客户满意度、产品市场份额和产品安全性。具体来说，该项目将推进工程设计理论和方法，扩大可靠性工程的范围。通过尽早定量预测产品可靠性，该项目为工程师提供了一种更好的方法，以降低成本实现高可靠性。