Risk Analysis and Prognostics and Health Management for Smart Manufacturing

Abstract

This paper harmonizes and builds upon methodologies for the fields of risk analysis and prognostics and health management (PHM) in smart manufacturing. It demonstrates that augmenting the theory, methodology, and current practice of both fields can add significant value to one another. This paper also proposes a novel methodology to be used during the design phase of implementing a PHM system for a manufacturing process. The purpose is to provide scope and direction for system design by identifying the most critical manufacturing components or subsystems that would most benefit from PHM. The methodology combines modified versions of hierarchical holographic modeling (HHM); risk filtering, ranking, and management (RFRM); and fault tree analysis (FTA). This paper walks through a case study within US manufacturing that serves to test and demonstrate the efficacy of the methodology.