Measurement Science for Prognostics and Health Management for Smart Manufacturing Systems: Key Findings from a Roadmapping Workshop

Published

October 23, 2015

Author(s)

Brian A. Weiss, Gregory W. Vogl, Moneer Helu, Guixiu Qiao, Joan Pellegrino, Mauricio Justiniano, Anand Raghunathan

Abstract

The National Institute of Standards and Technology (NIST) hosted the Roadmapping Workshop - Measurement Science for Prognostics and Health Management for Smart Manufacturing Systems (PHM4SMS) in Fall 2014 to discuss the needs and priorities of stakeholders in the PHM4SMS technology area. The workshop brought together over 70 members of the PHM community. The attendees included small, medium, and large manufacturers; technology developers and integrators; academic researchers; government organizations; trade associations; and standards bodies. The attendees discussed the current and anticipated measurement science challenges to advance PHM methods and techniques for smart manufacturing systems; the associated research and development (R&D) needed to implement condition monitoring, diagnostic, and prognostic technologies within manufacturing environments; and the priorities to meet the needs of PHM in manufacturing. This paper will summarize the key findings of this workshop, and present some of the critical measurement science challenges and corresponding roadmaps, i.e., suggested courses of action, to advance PHM for manufacturing. Milestones and targeted capabilities will be presented for each roadmap across three areas: PHM Manufacturing Process Techniques; PHM Performance Assessment; and PHM Infrastructure - Hardware, Software, and Integration. An analysis of these roadmaps and crosscutting themes seen across the breakout sessions will also be discussed.

Proceedings Title

Annual Conference Of The Prognostics And Health Management Society 2015

Conference Dates

October 18-24, 2015

Conference Location

Coronado, CA, US

Pub Type

Conferences

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Keywords

smart manufacturing, diagnostics, prognostics, condition-monitoring, maintenance, machine tools, industrial robotics

Citation

Weiss, B. , Vogl, G. , Helu, M. , Qiao, G. , Pellegrino, J. , Justiniano, M. and Raghunathan, A. (2015), Measurement Science for Prognostics and Health Management for Smart Manufacturing Systems: Key Findings from a Roadmapping Workshop, Annual Conference Of The Prognostics And Health Management Society 2015, Coronado, CA, US, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=918941 (Accessed January 15, 2025)