Location
Online
Event Website
https://hicss.hawaii.edu/
Start Date
4-1-2021 12:00 AM
End Date
9-1-2021 12:00 AM
Description
We present a novel application of business process modelling and simulation of manufacturing workflows. Using formal methods, we produce correct-by-construction executable models that can be simulated in an interleaved way. The simulation draws advanced analytics from live IoT monitoring as well as an ERP system to provide predictive business intelligence. We describe our process and resource modelling efforts in the context of a collaborative project with two manufacturing partners. We evaluate our results based on the improvement of the scheduling accuracy for real production flows.
A Real-world Case Study of Process and Data Driven Predictive Analytics for Manufacturing Workflows
Online
We present a novel application of business process modelling and simulation of manufacturing workflows. Using formal methods, we produce correct-by-construction executable models that can be simulated in an interleaved way. The simulation draws advanced analytics from live IoT monitoring as well as an ERP system to provide predictive business intelligence. We describe our process and resource modelling efforts in the context of a collaborative project with two manufacturing partners. We evaluate our results based on the improvement of the scheduling accuracy for real production flows.
https://aisel.aisnet.org/hicss-54/da/ai_case_studies/2