TY - GEN
T1 - Data modeling and workflow analysis of cyber-manufacturing systems
AU - Song, Zhengyi
AU - Moon, Young
N1 - Publisher Copyright:
© 2020 The Author(s). This is an Open Access article under the CC BY license.
PY - 2020
Y1 - 2020
N2 - Cyber-Manufacturing System (CMS) is a vision for the factory of the future, where physical manufacturing resources and processes are integrated with computational workflows to provide on-demand, adaptive, and scalable manufacturing services. In CMS, functional manufacturing components in a factory floor are digitized and encapsulated in production services; and are accessible by users throughout the network. CMS utilizes data-centric technologies to program manufacturing activities in factory floors. Leveraging advanced technologies, CMS can provide robust solutions to achieve better manufacturing agility, flexibility, scalability, and sustainability than from traditional factories. While data is the main driver of the manufacturing activities in CMS, the lack of (i) a generic data model of explicit representation of the entities and stakeholders in CMS and (ii) workflow definition and analysis for service-orientated functionalities and manufacturing intelligence of CMS is still hindering the implementation of a fully executable CMS. To address such problems, this paper (i) formalizes a data modeling of CMS using Entity-Relationship (E-R) diagram, (ii) presents the definition and analysis of workflows along with data pipelines and Extract/Transform/Load (ETL) processes that automate the entire lifecycle activities in CMS and (iii) deploys the proposed data model and workflows in a Web-based application, and (iv) tests the functionality of this application with an industrial case and eventually validates the proposed data model and workflows.
AB - Cyber-Manufacturing System (CMS) is a vision for the factory of the future, where physical manufacturing resources and processes are integrated with computational workflows to provide on-demand, adaptive, and scalable manufacturing services. In CMS, functional manufacturing components in a factory floor are digitized and encapsulated in production services; and are accessible by users throughout the network. CMS utilizes data-centric technologies to program manufacturing activities in factory floors. Leveraging advanced technologies, CMS can provide robust solutions to achieve better manufacturing agility, flexibility, scalability, and sustainability than from traditional factories. While data is the main driver of the manufacturing activities in CMS, the lack of (i) a generic data model of explicit representation of the entities and stakeholders in CMS and (ii) workflow definition and analysis for service-orientated functionalities and manufacturing intelligence of CMS is still hindering the implementation of a fully executable CMS. To address such problems, this paper (i) formalizes a data modeling of CMS using Entity-Relationship (E-R) diagram, (ii) presents the definition and analysis of workflows along with data pipelines and Extract/Transform/Load (ETL) processes that automate the entire lifecycle activities in CMS and (iii) deploys the proposed data model and workflows in a Web-based application, and (iv) tests the functionality of this application with an industrial case and eventually validates the proposed data model and workflows.
KW - Cyber-Manufacturing system
KW - Data analytics
KW - ETL process
KW - Entity-Relationship (ER) diagram
KW - Workflow model
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U2 - 10.1115/IMECE2020-23149
DO - 10.1115/IMECE2020-23149
M3 - Conference contribution
AN - SCOPUS:85101191722
T3 - ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
BT - Advanced Manufacturing
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2020 International Mechanical Engineering Congress and Exposition, IMECE 2020
Y2 - 16 November 2020 through 19 November 2020
ER -