Open AccessDigital Twin-Driven Process and Equipment FMECA Generation for Smart Manufacturing Applications
Author(s) -
Sudipto Ghoshal,
Jay Meyer,
Venkat Malepati,
Caleb Hudson,
Somnath Deb,
Andrew Hess,
Feraidoon Zahiri,
Gregory P. Sutton
Publication year - 2021
Publication title -
proceedings of the annual conference of the prognostics and health management society
Language(s) - English
Resource type - Journals
ISSN - 2325-0178
DOI - 10.36001/phmconf.2021.v13i1.3085
Subject(s) - failure mode, effects, and criticality analysis , process (computing) , automation , systems engineering , failure mode and effects analysis , engineering , reuse , reliability engineering , manufacturing engineering , computer science , mechanical engineering , waste management , operating system
Qualtech Systems, Inc. (QSI)’s integrated tool set, consisting of TEAMS-Designer® and TEAMS-RDS® provides a comprehensive digital twin-driven and 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 deployed equipment. In this paper, we present QSI’s approach towards adapting and enhancing their existing model-based systems engineering (MBSE) approach towards a comprehensive digital twin that incorporates constructs necessary for development of a Process Failure Modes and Criticality Analysis (P-FMECA) and integrates that with an Equipment FMECA. The paper will discuss the various levels of automation towards incorporation of these model constructs and their reuse towards automation of the development of the different digital twins and subsequently the automatic generation of the combined Process and Equipment FMECA. This automated ability to develop the integrated FMECA that incorporates both Process-level Failure Modes and Equipment-level Failure Modes allows the system designer and operators to correlate and identify process failures down to their root causes at the equipment-level and thereby producing a comprehensive actionable systems-level view of the entire Smart Manufacturing facility from a fault management design and operations perspective. The paper will present the application of this novel technology for the Advanced Metal Finishing Facility (AMFF) at the Warner-Robins Air Logistics Complex (WR-ALC) in Robins Air Force Base, Georgia, as part of WR-ALC’s initiative towards model-based enterprise (MBE) and smart manufacturing.