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Integration of MTConnect and Standard-based Sensor Networks for Manufacturing Equipment Monitoring

Published

Author(s)

Kang B. Lee, Yuyin Song, Peter S. Gu

Abstract

MTConnect is an open and extensible protocol designed for the exchange of data between shop floor devices and software applications. MTConnect allows manufacturers to facilitate retrieval of information and data from factory devices, such as machine tools, sensors, and controllers. Currently, MTConnect users read data from sensors through proprietary sensor interfaces using adaptors. The suite of Institute of Electrical and Electronics Engineers (IEEE) 1451 standards defines a set of open, common communication interfaces for sensor networks, including both sensor interfaces and network interfaces. This paper proposes an integration architecture of MTConnect with IEEE 1451 standard-based sensor networks. In the architecture, MTConnect plays a network interface role in the IEEE 1451 standard-based sensor networks via an MTConnect Agent. An adaptor is used to provide the mapping between the MTConnect Agent and the IEEE 1451 sensor network. A prototype system integrating MTConnect with IEEE 1451.2-based sensor network has been developed. Two case studies are provided to illustrate the integration.
Proceedings Title
Proceedings of ASME 2012 International Manufacturing Science and Engineering Conference
Conference Dates
June 4-8, 2012
Conference Location
Notre Dame, IN

Keywords

Adaptor, Agent, Agent Client, Device, IEEE 1451, Manufacturing Equipment, MTConnect, Network Interface, Sensor, Sensor Interface, Sensor Network, Sensor Standards, Smart Transducer

Citation

Lee, K. , Song, Y. and Gu, P. (2012), Integration of MTConnect and Standard-based Sensor Networks for Manufacturing Equipment Monitoring, Proceedings of ASME 2012 International Manufacturing Science and Engineering Conference, Notre Dame, IN, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=911045 (Accessed June 23, 2024)

Issues

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Created June 8, 2012, Updated February 19, 2017