470311 Iot-Enabled Cybermanufacturing: Challenges and Possibilities

Tuesday, November 15, 2016: 12:47 PM
Monterey I (Hotel Nikko San Francisco)
Devarshi Shah1, Austin Hancock2, Anthony Skjellum2, Q. Peter He1 and Jin Wang1, (1)Chemical Engineering, Auburn University, Auburn, AL, (2)Computer Science and Software Engineering, Auburn University, Auburn, AL

Although there are many names used to describe next generation manufacturing systems, such as cybermanufacturing and smart/advanced manufacturing, the essence of these is the application of increasingly powerful and low-cost computation and networked information-based technologies in manufacturing enterprises[1].

One potential enabler for cybermanufacturing is the Internet of Things (IoT), and there is a general consensus that factories and plants connected to the Internet are more efficient, productive and smarter than their non-connected counterparts[2], [3].

Industrial IoT devices are sensors/actuators, computers with wireless networks, and, most importantly, systems that are small and easy to embed. IoT devices offer the opportunity to instrument systems with massive numbers of sensors. With the huge amount of data and the programmability of IoT devices, comes the opportunity to shape the data received, to address local redundancy of information, and to improve both the accuracy and precision of measurements locally and across a distributed parameter system such as a reactor. However, many challenges remain in the areas of hardware such as sensor/actuator/network reliability, sensor accuracy; software such as protocols, data management, cyber security; and data analytics such as how to address the 4V’s of Big Data[4].

In this work, we test IoT temperature sensors on a batch system with the goal of better understanding and control of the system. Complete description of the batch system setup, including IoT hardware and software, will be given. Results obtained based on the batch system, challenges encountered and ways to address them, and potential application of IoT devices in chemical processes will be discussed.


[1] S. C. of the A. M. P. 2. 0. (AMP2.0), “Report to the president: accelerating U.S. advanced manufacturing.” 2014.

[2] P. C. Evans and M. Annunziata, “Industrial internet: Pushing the boundaries of minds and machines,” Gen. Electr., 2012.

[3] F. Shrouf, J. Ordieres, and G. Miragliotta, “Smart factories in Industry 4.0: A review of the concept and of energy management approached in production based on the Internet of Things paradigm,” in Industrial Engineering and Engineering Management (IEEM), 2014 IEEE International Conference on, 2014, pp. 697–701.

[4] S. J. Qin, “Process data analytics in the era of big data,” AIChE J., vol. 60, pp. 3092–3100, 2014.

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See more of this Session: Big Data Analytics in Chemical Engineering
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