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13 May 2019 Low cost wireless accelerometer sensor platform with internet-of-things for manufacturing (IOT4MFG) applications
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Abstract
Sensors are ubiquitous in modern manufacturing operations, and they generate significant quantities of data. With the advent of low cost, readily available broad band communication and virtually infinite cloud storage, many of the old stigmatisms related to taking data from a plant are no longer of concern. However, the question still remains as to what to do with the data. This lecture will discuss the use of large scale data sets from production operations and how they can be leveraged to better understand not only traditional operations, but untapped opportunities from data that are readily available today. Such opportunities provide an improved platform for classical analytic techniques as well as more modern, data intensive approaches to process and operations modeling. The talk will then focus on a specific next generation digital representations and their application to low cost, highly flexible implementations. Examples will be given for both manufacturing operations (additive and subtractive) and validation/verification, as well as how this capability is extensible to cloud computing operations, and next generation technology and business models such as Desktop as a Service (DAAS). A Wireless Accelerometer Sensor Platform (WASP) is presented as an extremely low-cost, wireless, and robust method to monitor manufacturing equipment of any age. The talk will conclude with a discussion of the technology, workforce and infrastructural directions and needs to fully enable the next generation digital twin, and where such a capability will drive the future of manufacturing.
Conference Presentation
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kyle S. Saleeby and Thomas R. Kurfess "Low cost wireless accelerometer sensor platform with internet-of-things for manufacturing (IOT4MFG) applications", Proc. SPIE 10982, Micro- and Nanotechnology Sensors, Systems, and Applications XI, 1098210 (13 May 2019); https://doi.org/10.1117/12.2517437
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