Reliability Prediction for System Designs with Outsourced Components

Missouri University Of Science And Technology, Rolla MO

Investigators

Abstract

The goal of this project is to predict the system reliability of products whose components are outsourced to outside suppliers. Outsourcing is a common practice because of lower operational and labor costs. The detailed designs of outsourced components, however, are mostly proprietary to component designers and are black boxes to system designers. This poses a great challenge for system designers to estimate the system reliability during the system design stage. This project performs feasibility studies to explore possible ways for system designers to predict the system reliability without revealing proprietary details of outsourced components. As a result, this project offers to help engineers make more reliable, safer, and cheaper products, thereby increasing competitiveness and improving quality of life. This research could impact broad areas of design methodologies and wide engineering applications, ranging from large structural systems to small integrated circuit systems. Beyond engineering design, this project also benefits system engineering, reliability engineering, and operations research where system reliability plays a vital role. This research addresses reliability prediction at both component and system levels. From the perspective of component design, this project determines what reliability information a supplier should provide to system designers and how to do so. The information will be sufficient for system reliability analysis, and the proprietary information of the supplier will also be protected. From the perspective of system design, this project provides theories to system designers so that they could use the above component information to reconstruct component reliability models that accommodate dependencies between component failures, thereby producing an accurate system reliability prediction for decision making on system configurations, optimization, life cycle cost, maintenance, warranty, and so on.