A GEMMA-GRAFCET generator for the automation software of smart manufacturing systems

Juan Manuel Castillo, Giacomo Barbieri*, Alejandro Mejia, José Daniel Hernandez, Kelly Garces

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)
5 Downloads (Pure)

Abstract

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 tech-nologies, 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 un-derstanding 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.

Original languageEnglish
Article number232
JournalMachines
Volume9
Issue number10
DOIs
Publication statusPublished - Oct 2021
Externally publishedYes

Keywords

  • Automation software
  • GEMMA
  • Interoperability
  • Model-driven engineering
  • PLC
  • Smart manufacturing systems

Fingerprint

Dive into the research topics of 'A GEMMA-GRAFCET generator for the automation software of smart manufacturing systems'. Together they form a unique fingerprint.

Cite this