Research Area: Cloud Computing
Discrete manufacturing systems are complex cyber-physical systems (CPS) and their availability, performance, and quality have a big impact on the economy. Smart manufacturing promises to improve these aspects. One key approach that is being pursued in this context is the creation of centralized software-defined control (SDC) architectures and strategies that use diverse sensors and data sources to make manufacturing more adaptive, resilient, and programmable. In this paper, we present SDCWorks-a modeling and simulation framework for SDC. It consists of the semantic structures for creating models, a baseline controller, and an open source implementation of a discrete event simulator for SDCWorks models. We provide the semantics of such a manufacturing system in terms of a discrete transition system which sets up the platform for future research in a new class of problems in formal verification, synthesis, and monitoring. We illustrate the expressive power of SDCWorks by modeling the realistic SMART manufacturing testbed of University of Michigan. We show how our open source SDCWorks simulator can be used to evaluate relevant metrics (throughput, latency, and load) for example manufacturing systems.
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Author(s) Name: Matthew Potok; Chien-Ying Chen; Sayan Mitra; Sibin Mohan
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Conferrence name: 2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems
Publisher name: IEEE
DOI: 10.1109/ICCPS.2018.00017
Volume Information: Volume 2018
