Reliable Industrial IoT-Based Distributed Automation
Апстракт
Reconfigurable manufacturing systems supported by Industrial Internet-of-Things (IIoT) are modular and easily integrable, promoting efficient system/component reconfigurations with minimal downtime. Industrial systems are commonly based on sequential controllers described with Control Interpreted Petri Nets (CIPNs). Existing design methodologies to distribute centralized automation/control tasks focus on maintaining functional properties of the system during the process, while disregarding failures that may occur during execution (e. g., communication packet drops, sensing or actuation failures). Consequently, in this work, we provide a missing link for reliable IIoT-based distributed automation. We introduce a method to transform distributed control models based on CIPNs into Stochastic Reward Nets that enable integration of realistic fault models (e. g., probabilistic link models). We show how to specify desired system properties to enable verification under the adopted communication.../fault models, both at design-and run-time; we also show feasibility of runtime verification on the edge, with a continuously updated system model. Our approach is used on real industrial systems, resulting in modifications of local controllers to guarantee reliable system operation in realistic IIoT environments.
Кључне речи:
Petri nets / Performance and reliability / Distributed automationИзвор:
Proceedings of the 2019 International Conference on Internet of Things Design and Implementation (IoTDI ’19), 2019, 94-105Издавач:
- Assoc Computing Machinery, New York
Финансирање / пројекти:
- ONR [N00014-17-1-2012]
- NSF grant [CNS-1652544]
- Иновативни приступ у примени интелигентних технолошких система за производњу делова од лима заснован на еколошким принципима (RS-MESTD-Technological Development (TD or TR)-35004)
- ONR [N00014-17-1-2504]
Колекције
Институција/група
Mašinski fakultetTY - CONF AU - Lesi, Vuk AU - Jakovljević, Živana AU - Pajić, Miroslav PY - 2019 UR - https://machinery.mas.bg.ac.rs/handle/123456789/3119 AB - Reconfigurable manufacturing systems supported by Industrial Internet-of-Things (IIoT) are modular and easily integrable, promoting efficient system/component reconfigurations with minimal downtime. Industrial systems are commonly based on sequential controllers described with Control Interpreted Petri Nets (CIPNs). Existing design methodologies to distribute centralized automation/control tasks focus on maintaining functional properties of the system during the process, while disregarding failures that may occur during execution (e. g., communication packet drops, sensing or actuation failures). Consequently, in this work, we provide a missing link for reliable IIoT-based distributed automation. We introduce a method to transform distributed control models based on CIPNs into Stochastic Reward Nets that enable integration of realistic fault models (e. g., probabilistic link models). We show how to specify desired system properties to enable verification under the adopted communication/fault models, both at design-and run-time; we also show feasibility of runtime verification on the edge, with a continuously updated system model. Our approach is used on real industrial systems, resulting in modifications of local controllers to guarantee reliable system operation in realistic IIoT environments. PB - Assoc Computing Machinery, New York C3 - Proceedings of the 2019 International Conference on Internet of Things Design and Implementation (IoTDI ’19) T1 - Reliable Industrial IoT-Based Distributed Automation EP - 105 SP - 94 DO - 10.1145/3302505.3310072 ER -
@conference{ author = "Lesi, Vuk and Jakovljević, Živana and Pajić, Miroslav", year = "2019", abstract = "Reconfigurable manufacturing systems supported by Industrial Internet-of-Things (IIoT) are modular and easily integrable, promoting efficient system/component reconfigurations with minimal downtime. Industrial systems are commonly based on sequential controllers described with Control Interpreted Petri Nets (CIPNs). Existing design methodologies to distribute centralized automation/control tasks focus on maintaining functional properties of the system during the process, while disregarding failures that may occur during execution (e. g., communication packet drops, sensing or actuation failures). Consequently, in this work, we provide a missing link for reliable IIoT-based distributed automation. We introduce a method to transform distributed control models based on CIPNs into Stochastic Reward Nets that enable integration of realistic fault models (e. g., probabilistic link models). We show how to specify desired system properties to enable verification under the adopted communication/fault models, both at design-and run-time; we also show feasibility of runtime verification on the edge, with a continuously updated system model. Our approach is used on real industrial systems, resulting in modifications of local controllers to guarantee reliable system operation in realistic IIoT environments.", publisher = "Assoc Computing Machinery, New York", journal = "Proceedings of the 2019 International Conference on Internet of Things Design and Implementation (IoTDI ’19)", title = "Reliable Industrial IoT-Based Distributed Automation", pages = "105-94", doi = "10.1145/3302505.3310072" }
Lesi, V., Jakovljević, Ž.,& Pajić, M.. (2019). Reliable Industrial IoT-Based Distributed Automation. in Proceedings of the 2019 International Conference on Internet of Things Design and Implementation (IoTDI ’19) Assoc Computing Machinery, New York., 94-105. https://doi.org/10.1145/3302505.3310072
Lesi V, Jakovljević Ž, Pajić M. Reliable Industrial IoT-Based Distributed Automation. in Proceedings of the 2019 International Conference on Internet of Things Design and Implementation (IoTDI ’19). 2019;:94-105. doi:10.1145/3302505.3310072 .
Lesi, Vuk, Jakovljević, Živana, Pajić, Miroslav, "Reliable Industrial IoT-Based Distributed Automation" in Proceedings of the 2019 International Conference on Internet of Things Design and Implementation (IoTDI ’19) (2019):94-105, https://doi.org/10.1145/3302505.3310072 . .