Issue |
MATEC Web Conf.
Volume 249, 2018
2018 5th International Conference on Mechanical, Materials and Manufacturing (ICMMM 2018)
|
|
---|---|---|
Article Number | 03010 | |
Number of page(s) | 6 | |
Section | Mechanical Engineering and Digital Manufacturing | |
DOI | https://doi.org/10.1051/matecconf/201824903010 | |
Published online | 10 December 2018 |
An analytical framework for smart manufacturing
1 Institute for Software Integrated Systems, Vanderbilt University, Nashville, TN 37212
2 National Institute of Standards and Technology, Gaithersburg, MD 20899
Smart manufacturing is an emerging paradigm for the next generation of manufacturing systems. One key to the success of smart manufacturing is the ability to use the production data for defining predictive and descriptive models and their analyses. However, the development and refinement of such models is a labor- and knowledgeintensive activity that involves acquiring data, selecting and refining an analytical method and validating results. This paper presents an analytical framework that facilitates these activities by allowing ad-hoc analyses to be rapidly specified and performed. The proposed framework uses a domain-specific language to allow manufacturing experts to specify analysis models in familiar terms and includes code generators that automatically generate the lower-level artifacts needed for performing the analysis. We also describe the use of our framework with an example problem.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.