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An AutomationML model for plug-and-produce assembly systems
conference contribution
posted on 2017-12-08, 10:05 authored by Paul Danny, Pedro FerreiraPedro Ferreira, Niels LohseNiels Lohse, Magno GuedesThis paper aims to support the creation of high performance ‘Plug-and-Produce’ systems by proposing a new semantic model that targets the use of AutomationML (AML). In this direction, the focus is narrowed to the self-description of equipment modules that highlights the use of ‘Skill’ concept. An insight description on how the concept of ‘Skill Recipe’ can be used to execute the equipment ‘Skills’ to fulfil the product's assembly requirements is also provided. This is viewed as a critical concept to achieve high performance in ‘Plug-and-Produce’. To translate the base semantic definitions, we have developed new libraries that are fully compliant with the AML standard. The main purpose of using AML in this context is to bridge production and other engineering domains. An overview of the literature that covers the past and current trends in data exchange and standards is presented, while pointing out the existing challenges and limitations. The vision of this paper is to support the standardization effort of integrating information for design, build, ramp-up and operation of production systems. Hence, this approach elucidates the use of existing AML concepts to model and instantiate Product, Process and Resource (PPR), and the underlying definitions such as: ‘Skills’, ‘Skill Recipes’ and ‘Skill Requirements’. Finally, this paper illustrates the implementation of this approach in AML with a help of an industrial case study demonstrated 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
2017 IEEE 15th International Conference on Industrial Informatics (INDIN)Pages
849 - 854Citation
DANNY, P. ... et al, 2017. An AutomationML model for plug-and-produce assembly systems. Presented at the 2017 IEEE 15th International Conference on Industrial Informatics (INDIN), Emden, Germany, 24th-26th July 2017, pp. 849-854.Publisher
© IEEEVersion
- AM (Accepted Manuscript)
Publication date
2017Notes
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.ISBN
978153860837117eISSN
2378-363XPublisher version
Language
- en