posted on 2018-07-23, 09:44authored byPaul Danny, Pedro Ferreira, Niels Lohse, Kirill Dorofeev
Assembly systems today are facing significant pressure to deliver high performance process executions, while being responsive to the fluctuating market demands. However, the implementation the trending Cyber Physical Systems concepts via ‘Plug-and-Produce’ devices produces some communication overheads. In this direction, the openMOS project aims to decouple the elements that are responsible for adaptation and general operations of the system. This allows the system to have two parallel processes. Towards this end, the priority is to deliver high performance process executions, while the other process focuses on delivering the required agility. The focus of this work is narrowed down to the development of task execution tables that guarantees high performance process executions. In this direction, the definition of task execution table is based on an existing AutomationML (AML) model that highlights the explicit relationships between the Product, Process and Resource (PPR) domains. A new decisional attribute has been added to the existing ‘Skill’ concept, which provides the flexibility to incorporate event-based process alternatives. An insight description on how the system handles process executions during run-time failures is also provided. Finally, this paper illustrates the run-time implementation of the execution table with a help of an industrial case study that has been used for a demonstration activity within the openMOS project.
Funding
The reported work is a part of the openMOS project partially funded by the European Commission as a part of the EC-H2020-IA (GA 680735).
History
School
Mechanical, Electrical and Manufacturing Engineering
Published in
IEEE 16th International Conference of Industrial Informatics (INDIN 2018)
Citation
DANNY, P. ... et al., 2018. An event-based automationML model for the process execution of ‘plug-and-produce’ assembly systems. Presented at the IEEE 16th International Conference of Industrial Informatics (INDIN 2018), Porto, Portugal, 18-20th July, pp.49-54.
Publisher
IEEE
Version
AM (Accepted Manuscript)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/