TY - GEN
T1 - SDCWorks
T2 - 9th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2018
AU - Potok, Matthew
AU - Chen, Chien Ying
AU - Mitra, Sayan
AU - Mohan, Sibin
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/21
Y1 - 2018/8/21
N2 - 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.
AB - 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.
KW - cyber physical systems
KW - manufacturing
KW - verification
UR - http://www.scopus.com/inward/record.url?scp=85053511971&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85053511971&partnerID=8YFLogxK
U2 - 10.1109/ICCPS.2018.00017
DO - 10.1109/ICCPS.2018.00017
M3 - Conference contribution
AN - SCOPUS:85053511971
SN - 9781538653012
T3 - Proceedings - 9th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2018
SP - 88
EP - 97
BT - Proceedings - 9th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 11 April 2018 through 13 April 2018
ER -