Dear Community Members,
Please see the note below, courtesy of Dr. Chris McComb, regarding a special
issue in JCISE on Data Wrangling.
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Special Issue on Data Wrangling to Support Research on Engineering Design and
Manufacturing
The digitalization of manufacturing and the technologies associated with
Industry 4.0 has led to an explosion in unstructured data across the entire
product lifecycle, including engineering design and manufacturing activities,
which are embodied in the emerging "digital thread" and corresponding "digital
twin" of the product. These technologies expose rich information that can be
used to achieve data-driven (re)design of products and engineering, support
continuous improvement of manufacturing operations, and enhance product
development practices. However, challenges persist across the entire product
lifecycle due to the massive scale at which this data is generated and shared
(e.g., some researchers have reportedly resorted to the inelegant solution of
mailing hard drives). Significant challenges also arise due to the format,
variety, and content of the data as well, limiting its broader use in
engineering design and manufacturing research.
This special issue aims to capture contemporary perspectives on both the
challenges and opportunities regarding the generation, collection, curation,
storage, transmission, and transformation of engineering design and
manufacturing data in digital databases and repositories. Topics of interest
include, but are not limited to:
* Methods for data storage, management, and curation of product lifecycle
data
* Repository-based exploration of design and manufacturing data
* Translation and transmission techniques for facilitating scalable
data-driven pipelines
* Automated data/model generation for engineering workflows (e.g., virtual
scenes and data-driven decision-making)
* Opportunities of standards development for data management in engineering
* Data representations and data schemas to enable the digital thread
Authors may submit either editorials (~5,000 words) or research articles
(~10,000 words). The express focus of this special issue is on the generation,
collection, curation, storage, transmission, and transformation of the data
itself. Research and development contributions should explicitly relate to the
domain-specific challenges of mechanical design, product development,
manufacturing, and/or similar areas. Submissions that propose novel machine
learning or other algorithms, for instance, will be considered out-of-scope. To
the extent possible, authors are encouraged to make accessible the data and
software used in their submissions.
Publication Target Dates
* Paper Submission: March 2022
* Initial Review Completed: June 2022
* Special Issue Publication Date: December 2022
Standard Submission Instructions
Papers should be submitted electronically to the Journal at
http://journaltool.asme.org. If you already have an account, log in as author ;
and select Submit Paper at the bottom of the page. If you do not have an
account, select Submissions and follow the steps. In either case, at the Paper
Submittal page, select the Journal of Computing and Information Science in
Engineering and then select the special issue Data Wrangling to Support
Research on Engineering Design and Manufacturing. Papers received after the
deadline or papers not selected for inclusion in the Special Issue may be
accepted for publication in a regular issue. Early submission is highly
encouraged. Please also email the Editor, Professor Satyandra K. Gupta, at
guptask@xxxxxxx<mailto:guptask@xxxxxxx>, to alert him that your paper is
intended for the special issue.
Special Issue Guest Editors
* Christopher McComb, Carnegie Mellon University,
ccm@xxxxxxx<mailto:ccm@xxxxxxx>
* William Bernstein, Air Force Research Laboratory,
william.bernstein@xxxxxxxxx<mailto:william.bernstein@xxxxxxxxx>
* Vincenzo Ferrero, National Institute of Standards and Technology,
vincenzo.ferrero@xxxxxxxx<mailto:vincenzo.ferrero@xxxxxxxx>
* Timothy W. Simpson, The Pennsylvania State University,
tws8@xxxxxxx<mailto:tws8@xxxxxxx>
* Nicholas A. Meisel, The Pennsylvania State University,
nam20@xxxxxxx<mailto:nam20@xxxxxxx>
* Binil Starly, North Carolina State University,
bstarly@xxxxxxxx<mailto:bstarly@xxxxxxxx>
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--
Paul T. Grogan, Ph.D.
Assistant Professor
School of Systems and Enterprises
Stevens Institute of Technology
E: pgrogan@xxxxxxxxxxx<mailto:pgrogan@xxxxxxxxxxx> | O: (201) 216-5378 (Babbio
Center 517) | W: code-lab.org<https://www.code-lab.org/>
