A GEMMA-GRAFCET Generator for the Automation Software of Smart Manufacturing Systems

Autor: Juan Manuel Castillo, Giacomo Barbieri, Alejandro Mejia, José Daniel Hernandez, Kelly Garces
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Machines, Vol 9, Iss 10, p 232 (2021)
Druh dokumentu: article
ISSN: 2075-1702
DOI: 10.3390/machines9100232
Popis: Within the Industry 4.0 revolution, manufacturing enterprises are transforming to intelligent enterprises constituted by Smart Manufacturing Systems (SMSs). A key capability of SMSs is the ability to connect and communicate with each other through Industrial Internet of Things technologies, and protocols with standard syntax and semantics. In this context, the GEMMA-GRAFCET Methodology (GG-Methodology) provides a standard approach and vocabulary for the management of the Operational Modes (OMs) of SMSs through the automation software, bringing a common understanding of the exchanged data. Considering the lack of tools to implement the methodology, this work introduces an online tool based on Model-Driven Engineering–GEMMA-GRAFCET Generator (GG-Generator)–to specify and generate PLCopen XML code compliant with the GG-Methodology. The proposed GG-Generator is applied to a case study and validated using Virtual Commissioning and Dynamic Software Testing. Due to the consistency obtained between the GG-Methodology and the generated PLC code, the GG-Generator is expected to support the adoption of the methodology, thus contributing to the interoperability of SMSs through the standardization of the automation software for the management of their OMs.
Databáze: Directory of Open Access Journals