Title
An Event-Based AutomationML Model for the Process Execution of Plug-and-Produce’ Assembly Systems
Abstract
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 eventbased 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.
Year
DOI
Venue
2018
10.1109/INDIN.2018.8471955
2018 IEEE 16th International Conference on Industrial Informatics (INDIN)
Keywords
Field
DocType
AutomationML,Task Execution Table,‘Plug-and-Produce’,Cyber Physical Systems,Semantic Models,Product,Skill,Skill Recipe,Skill Requirement
Systems engineering,Software engineering,Assembly systems,Automation,Cyber-physical system,Engineering,Overhead (business),Cloud computing
Conference
ISSN
ISBN
Citations 
1935-4576
978-1-5386-4830-8
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Paul Danny100.34
Pedro S. Ferreira2225.89
Niels Lohse35112.44
Kirill Dorofeev473.65