DIGITAL LIBRARY
APPLYING THE AUTOMATIONML TOOL TO IMPROVE THE STUDENTS’ SKILLS IN AUTOMATION
UFAM (BRAZIL)
About this paper:
Appears in: ICERI2021 Proceedings
Publication year: 2021
Pages: 6771-6778
ISBN: 978-84-09-34549-6
ISSN: 2340-1095
doi: 10.21125/iceri.2021.1534
Conference name: 14th annual International Conference of Education, Research and Innovation
Dates: 8-9 November, 2021
Location: Online Conference
Abstract:
A current challenge for engineering education involves teaching a new standardization of data integration and communication in automation area by the new modern technologies concerning the fourth industrial revolution.

Automation Markup Language (AutomationML) is an XML-based data format for exchanging plant information. This work has an educational purpose by using the AutomationML and aims to present the experimental report and the step-by-step modelling of a didactic storage plant process by using AutomationML. This API might will be used to teach automation concepts and practical classes for undergraduate students of the Federal University of Amazonas, aiming to improving the skills of this students by using the tool and practicing concepts of automation by the modelling and simulation processes and systems

This representation creates a generic model that integrates several types of data and has as outcome a model in AML (XML file) with relations between objects which can be used to associate data and other information and the dependencies between objects like interlinked engineering data, hierarchies, and roles.

The desired format is neutral, and there is no need to develop a new data format. Already existing used structures, extended, adapted, and merged properly to improve data exchange and join data. Thus, the tool compile and unify the data formats that are already available and designed to store and exchange data. Besides, that supports the storage of information: Plant topology information; Geometry information; Kinematics information; Logic information, and Reference and relation information.
Keywords:
Simprove student's skills, Remote engineering laboratories, Industrial automation learning.