Production Process Modelling Architecture to Support Improved Cyber-Physical Production Systems

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

With the proliferation of intelligent networks in industrial environments, manufacturing SME’s have been in a continuous search for integrating and retrofitting existing assets with modern technologies that could provide low-cost solutions for optimizations in their production processes. Their willingness to support a technological evolution is firmly based on the perception that, in the future, better tools will guarantee process control, surveillance and maintenance. For this to happen, the digitalization of valuable and extractable information must be held in a cost-effective manner, through contemporary approaches such as IoT, creating the required fluidity between hardware and software, for implementing Cyber-Physical modules in the manufacturing process. The goal of this work is to develop an architecture that will support companies to digitize their machines and processes through an MDA approach, by modeling their production processes and physical resources, and transforming into an implementation model, using contemporary CPS and IoT concepts, to be continuously improved using forecasting/predictive algorithms and analytics.

Original languageEnglish
Title of host publicationTechnological Innovation for Life Improvement - 11th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2020, Proceedings
EditorsLuis M. Camarinha-Matos, Nastaran Farhadi, Fábio Lopes, Helena Pereira
Place of PublicationCham
PublisherSpringer
Pages206-213
Number of pages8
ISBN (Electronic)978-3-030-45124-0
ISBN (Print)978-3-030-45123-3
DOIs
Publication statusPublished - 2020
Event11th Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2020 - Costa de Caparica, Portugal
Duration: 1 Jul 20203 Jul 2020

Publication series

NameIFIP Advances in Information and Communication Technology
PublisherSpringer
Volume577
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X

Conference

Conference11th Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2020
CountryPortugal
CityCosta de Caparica
Period1/07/203/07/20

Keywords

  • Artificial Intelligence
  • Cyber-physical systems
  • Internet of Things
  • Interoperability
  • Model driven architecture
  • Process modelling

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