A Real-world Case Study of Process and Data Driven Predictive Analytics for Manufacturing Workflows

Date
2021-01-05
Authors
Papapanagiotou, Petros
Vaughan, James
Smola, Filip
Fleuriot, Jacques
Contributor
Advisor
Department
Instructor
Depositor
Speaker
Researcher
Consultant
Interviewer
Annotator
Journal Title
Journal ISSN
Volume Title
Publisher
Volume
Number/Issue
Starting Page
1001
Ending Page
Alternative Title
Abstract
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.
Description
Keywords
Case Studies of Artificial Intelligence, Business Intelligence, Analytics Technologies for Industry Platforms, analytics, formal methods, manufacturing, simulation, workflow
Citation
Extent
10 pages
Format
Geographic Location
Time Period
Related To
Proceedings of the 54th Hawaii International Conference on System Sciences
Table of Contents
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights Holder
Local Contexts
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.