Mitigating Disruption in Production Networks through Dynamic Scheduling Enabled by Integrated Enterprise Data

Published

October 26, 2020

Author(s)

Timothy A. Sprock, Michael P. Brundage, William Z. Bernstein, Thurston B. Sexton, Michael E. Sharp

Abstract

The COVID-19 pandemic has caused unprecedented disruptions for manufacturers and supply chains. To respond to these disruptions and potential future disturbances, manufacturers need to be resilient and adapt their production system to fluctuating production demands. Sudden and large-scale changes in production needs may be best addressed quickly by leveraging multiple smaller existing facilities. These facilities frequently produce enormous amounts of data of varying types from various sources and software systems. Manufacturers can more effectively respond to disruptions by deploying dynamic decision-making tools, such as scheduling, that leverage this heterogeneous data. There are many outstanding challenges to quickly and correctly integrating and curating heterogeneous data sources and extracting knowledge from the resulting data sets. This note lays out the challenge, identifies common use cases that can serve as test cases, and describes qualities of good solutions to this problem.

Citation

The ASTM Journal of Smart and Sustainable Manufacturing

Pub Type

Journals

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DOI Link

Keywords

Smart Manufacturing, Information Modeling, Data Integration, Dynamic Scheduling

Citation

Sprock, T. , Brundage, M. , Bernstein, W. , Sexton, T. and Sharp, M. (2020), Mitigating Disruption in Production Networks through Dynamic Scheduling Enabled by Integrated Enterprise Data, The ASTM Journal of Smart and Sustainable Manufacturing, [online], https://doi.org/10.1520/SSMS20200051 (Accessed December 21, 2024)