Share
Title
Architecture for managing AAS-based business processesPublished Date
2023Publisher
ElsevierKeywords
Service Orchestration
Asset Administration Shell
Service Discovery
Business Process Modeling ... [+]
Asset Administration Shell
Service Discovery
Business Process Modeling ... [+]
Service Orchestration
Asset Administration Shell
Service Discovery
Business Process Modeling
Internet of Things
Industry 4.0 [-]
Asset Administration Shell
Service Discovery
Business Process Modeling
Internet of Things
Industry 4.0 [-]
Abstract
Industries frequently encounter the need to orchestrate services provided by devices as business processes. These industrial business process models need to meet Industry 4.0 (I4.0) specifications to ... [+]
Industries frequently encounter the need to orchestrate services provided by devices as business processes. These industrial business process models need to meet Industry 4.0 (I4.0) specifications to handle unpredictable scenarios in the manufacturing process. Asset Administration Shell (AAS) is considered the cornerstone of interoperability between machines and applications that compose manufacturing systems. AAS facilitates the digitization of physical things (assets) for virtual representation, turning an object into an I4.0 component. This paper investigates the usage of AAS in the context of business process orchestration and a proposal is presented based on those drawbacks. The contributions of this paper are 1) Present an architecture for the management of AAS-based business processes. 2) Introduce an AAS Submodel template that enables the description and registration of the RestServices of an asset. 3) Present a plugin for Camunda Modeler that enables the Service-Discovery mechanism from a chosen AAS repository and maps assets services into BPMN Service-Tasks. And, 4) Outline opportunities for future work between AAS and business process management systems with a primary focus on context-aware capabilities for enhancing the dynamicity of workflows. [-]
Publisher’s version
https://doi.org/10.1016/j.procs.2022.12.217ISSN
1877-0509Published at
Procedia Computer Science Vol. 217. Pp. 217-226Document type
Conference paper
Version
Published
Rights
© 2022 The AuthorsAccess
Open AccessCollections
The following license files are associated with this item: