An integrated model-based approach for fmeca development for smart manufacturing applications

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Abstract

Qualtech Systems, Inc. (QSI)'s integrated tool set, consisting of TEAMS-Designer® and TEAMS-RDS® provides a comprehensive model-based systems engineering approach that can be deployed for fault management throughout the equipment life-cycle - from its design for fault management to condition-based maintenance of the equipment. The TEAMS® failure-cause effect dependency model is a digital twin representation of the equipment in its failure-space and allows for various types of analyses such as testability, serviceability, failure propagation and others that facilitate fault management design of the equipment. The same model is deployed through TEAMS-RDS® for condition monitoring, prognostics, real-time health assessment, failure impact analysis, guided troubleshooting and others that facilitate condition-based maintenance as well as ensure efficient and rapid maintenance actions. In this paper, we present an overview of QSI's integrated toolset, with a focus on a systematic model-based approach towards an automated development of Failure Effects and Criticality Analysis (FMECA) and other relevant analyses for the equipment, for an improved understanding of failure effects and their causality at the system-level. The eventual objective here is improved equipment design as well as designing improved failure detection, failure isolation and failure mitigation. The paper will also discuss examples of such real-world applications for smart manufacturing in major depot maintenance facilities in the US. A subsequent paper will focus on the development and integration of process-level and equipment-level FMECAs for Smart Manufacturing applications.

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APA

Ghoshal, S., Deb, S., Haste, D., Hess, A., Zahiri, F., & Sutton, G. (2019). An integrated model-based approach for fmeca development for smart manufacturing applications. In Proceedings of the Annual Conference of the Prognostics and Health Management Society, PHM (Vol. 11). Prognostics and Health Management Society. https://doi.org/10.36001/phmconf.2019.v11i1.899

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