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August 2017


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Thu, 31 Aug 2017 14:29:14 -0400
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Dear Colleagues,

We are organizing an invited session "Process monitoring in the era of Big
Data" at the 10th IFAC Symposium on Advanced Control of Chemical
Processes, which will be held in Shenyang, China, July 25 - 27, 2018. The
conference website is

With ever-accelerating advancement of information, communication, sensing
and characterization technologies, such as industrial Internet of Things
(IoT) and high-throughput instruments, the amount of data collected and
stored by chemical and process industry has grown exponentially. Driven by
the availability of these data, it is expected that a new generation of
networked, information based technologies, data analytics, and predictive
modeling will provide unprecedented embedded computing capabilities as
well as access to previously unimagined potential uses of data and

How to create manufacturing intelligence from real-time data to support
accurate and timely decision-making is expected to contribute
significantly to the advancement of process operation. In the past 25
years, multivariate statistical process data analytic tools, such as
principal component analysis, partial least squares, have been effectively
used in process operation and control. However, some existing challenges
such as strong nonlinear dynamics and time varying characteristics, and
the new challenges associated with Big Data (i.e., volume, variety,
velocity and veracity), are driving for the development of new approaches
to process monitoring.

The aim of this invited session on “Process monitoring in the era of Big
Data” is to call for contributions that apply and develop big data
analytics and modeling for the purpose of process operation, monitoring
and control. Contributions are especially sought on how data mining,
multivariate statistical and machine learning methods might be developed
and applied to data-enhanced operations, that can effectively address the
existing and new challenges, including but not limited to process
nonlinearities, multi-modal distribution, time-varying characteristics,
and 4Vs of big data.

We would like to invite you submitting a paper to this session. If you are
interested in doing so, please send a tentative title before September
20th by email to [log in to unmask]

Best regards,
Jin Wang & Jinsong Zhao

Session organizers:
Jin Wang, Auburn University, USA ([log in to unmask])
Jinsong Zhao, Tsinghua University, P.R. China
([log in to unmask])