Nancy Diaz-Elsayed, Luis Hernandez, Ravi Rajamani,
Unscheduled downtime in manufacturing systems can be a major source of lost productivity, profits, and, ultimately, reduced process quality and reliability. However, the incorporation of asset condition management (ACM) into manufacturing systems offers an approach to improve equipment and plant operations by providing real-time condition awareness, system diagnostics, and estimates of future health to enable predictive maintenance. ACM refers to the capability of assessing the current and future state of health of a manufacturing system and integrating that knowledge with enterprise applications to meet the demand of production operations. In smart manufacturing systems, successful operations rely on the ability to easily and rapidly reconfigure factory production to optimize operations and system performance. While this is one of the ultimate goals of ACM, most current manufacturers fall short of this goal. Some large corporations have made great strides in incorporating ACM features into their advanced industrial installations; however, small- and medium-sized enterprises (SMEs) face distinct challenges. One of the key challenges is that most SMEs do not have the wherewithal to invest in new machines nor is there standard guidance on how older machines can be integrated into an ACM solution, so that their end-to-end manufacturing process can be optimized from a health management point of view. This research presents a framework for ACM to facilitate its introduction into manufacturing systems based on their "healthready" capabilities. Specifically, an ACM system architecture is defined for manufacturing systems, the health-ready principles and capability levels from the aerospace and automotive industries are adapted to the manufacturing domain, and the results from outreach efforts to the manufacturing community are discussed.
Proceedings of the ASME 2020 15th International Manufacturing Science and Engineering Conference MSEC2020
June 22-26, 2020
industrial robot systems, diagnostics, manufacturing processes, manufacturing systems, condition monitoring, prognostics, use cases, asset management