[Iefac.list] Call for Papers due 11/15: ASME MSEC 2020 - Smart Manufacturing System Modeling and Decision Making

[Feng Ju]

- Call for Papers -

A Symposium on

Smart Manufacturing System Modeling and Decision Making



Sponsored by the ASME Manufacturing Engineering Division’s

Manufacturing Systems Technical Committee

2020 ASME International Manufacturing Science and Engineering Conference
(MSEC)*

June 22 - 26, 2020

Cincinnati, Ohio

Hosted by the University of Cincinnati, College of Engineering and Applied
Science


Technical Focus


Modern manufacturing, named Smart Manufacturing, is resulted from the
convergence of advanced manufacturing capabilities with information and
communication technology (ICT). Smart Manufacturing systems are
characterized by the collaboration of human beings with fully or partly
autonomous machines in factories, and integration of customers and business
partners in business and value‐added processes. In this new manufacturing
paradigm, systems are becoming increasingly complex, and face more frequent
and unpredictable changes and disruptions, in which timely decision making
is pressingly needed. The rise of the Internet-of-Things (IoT) and
Cyber-Physical Systems (CPS) technology and approaches is driving increased
efforts to take advantage of the real-time information from interconnected
systems of sensing technology, communication network and physical processes.
By utilizing advanced modeling methodology and information analytics,
manufacturing systems will be able to perform more efficiently, agile,
collaboratively and resiliently. This symposium focuses on innovative
analytical approaches and methods for design, modeling and control of
advanced manufacturing systems. The aim of this symposium is to bring
academic researchers and industry professionals together to review the
latest advances and explore future direction in this filed. Specific topics
of interest include but are not limited to:



・        Smart manufacturing architecture and standardization

・        Smart manufacturing informatics and knowledge management

・        Data-driven and model-driven approaches for manufacturing process
and systems

・        Dynamic and adaptive scheduling and close-loop optimization for
production systems

・        Machine learning based approaches for real-time production
planning, control and management

・        Mass customization and “lot size 1” production

・        Modeling and optimization for sustainable production systems

・        Sensor-enabled process and inventory monitoring and control

・        Advanced diagnostics, prognostics, and asset health management for
production systems




Paper Submission


Authors are encouraged to submit an abstract and full manuscript for review
by November 15, 2019 via the conference website. Final revised manuscripts
must be submitted by March 26, 2020. The copyright transfer form must be
filled out by March 19, 2020 and the presenting author must pre-register by
April 15, 2020 or the paper will be withdrawn from the conference. No papers
are to be submitted to the organizers; submissions will only be accepted via
the conference website at  <https://event.asme.org/MSEC/>
https://event.asme.org/MSEC/ .

All papers accepted by MSEC2020 can be further submitted to any ASME
journals, such as the highly prestigious Journal of Manufacturing Science
and Engineering, for consideration of archival publication. In addition,
high quality MSEC2020 papers will be automatically channeled to relevant
ASME journals for fast-tracked publications.





Additional Symposium Activities


To highlight advancements in this technical area, symposium organizers will:

*   work to attract a high profile international keynote speaker

*   organize a special issue in the ASME Journal of Manufacturing Science
and Engineering

*   organize a state-of-the-art paper that will be the lead article in the
special issue



Organizers:

Dr. Feng Ju, Arizona State University, Tempe, AZ USA, 480-965-1746,
<mailto:fengju at asu.edu> fengju at asu.edu

Dr. Cindy Chang, University of Virginia, Charlottesville, VA USA,
<mailto:qc9nq at virginia.edu> qc9nq at virginia.edu

Dr. Jorge Arinez, General Motors R&D, Warren, MI USA,
<mailto:Jorge.arinez at gm.com> Jorge.arinez at gm.com



=================================

Feng Ju, PhD

Assistant Professor of Industrial Engineering

School of Computing, Informatics, and Decision Systems Engineering

Arizona State University

P.O. Box 878809
Tempe, AZ 85287-8809
https://fengju.engineering.asu.edu/





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