Abstract
The coronavirus disease 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 systems to fluctuating production demands. Sudden and large-scale changes in production needs may be best addressed quickly by leveraging multiple smaller existing work units with diverse capabilities and capacities. 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.