Int J Progn Health Manag, 7(Spec Iss on Smart Manufacturing PHM), 012. Present Status and Future Growth of Advanced Maintenance Technology and Strategy in US Manufacturing. The present status and future growth of maintenance in US manufacturing: results from a pilot survey. ISO 13379-1:2012 - Condition monitoring and diagnostics of machines − Data interpretation and diagnostics techniques − Part 1: General guidelines. International Organization for Standardization. ISO 18435-1:2009 - Industrial automation systems and integration − Diagnostics, capability assessment and maintenance applications integration − Part 1: Overview and general requirements. Paper presented at the Prognostics & Health Management Conference, Portland, Oregon. PHM for Automotive Manufacturing & Vehicle Applications. Unsettled Technology Opportunities for Vehicle Health Management and the Role for Health-Ready Components. Paper presented at the ASME 2016 Manufacturing Science and Engineering Conference, MSEC2016. The current state of sensing, health management, and control for small-to-medium-sized manufacturers. 43rd North American Manufacturing Research Conference, NAMRC 43, 1, 86-97. Enabling Smart Manufacturing Research and Development using a Product Lifecycle Test Bed. Making maintenance smarter: Predictive maintenance and the digital supply network. Journal of Manufacturing Science and Engineering, 141(9).Ĭoleman, C., Damodaran, S., Chandramouli, M., & Deuel, E. Where do we start? Guidance for technology implementation in maintenance management for manufacturing. P., Sexton, T., Hodkiewicz, M., Morris, K. International Journal of Production Research, 46(4), 967-992. Reconfigurable manufacturing systems: the state of the art. Paper presented at the ASME International Manufacturing Science and Engineering Conference, MSEC2008, Evanston, IL, United States.īi, Z. Real-time diagnostics, prognostics health management for large-scale manufacturing maintenance systems. International Journal of Machine Tools and Manufacture, 72, 16-24. A new receptance coupling substructure analysis methodology to improve chatter free cutting conditions prediction. Journal of Materials Processing Technology, 107(1-3), 243-251. A new approach for systematic design of condition monitoring systems for milling processes. Based upon the discussions, recommended next steps to advance this technological domain are also presented. This report summarizes the workshop and offers lessons learned regarding the current state of PHM. These contributors discussed 1) what works well, 2) common challenges that need to be addressed, 3) where the community’s priorities should be focused, and 4) how PHM technological adoption can be sped in a cost-effective manner. The participants represented a diverse cross-section of technology developers, integrators, end-users/manufacturers (from small to large), and researchers. This event featured panel presentations and discussions from industry, government, and academic participants who are focused in advancing monitoring, diagnostic, and prognostic (collectively known as prognostic and health management (PHM)) capabilities within manufacturing operations. Personnel from the National Institute of Standards and Technology (NIST) organized and led a Measurement and Evaluation for Prognostics and Health Management for Manufacturing Operations (ME4PHM) workshop at the 2019 Annual Conference of the Prognostics and Health Management Society held on September 23 rd, 2019 in Scottsdale, Arizona.
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