A Conceptual Architecture and Model for Smart Manufacturing Relying on Service-Based Digital Twins

Abstract

The technological foundation of smart manufacturing consists of cyber-physical systems and the Internet-of-Things (IoT). Each IoT device in a smart factory can be coupled with a digital twin, that is, a dynamic virtual representation of the physical system across its life-cycle using real-time sensor data. Currently, the manufacturing process itself, the involved devices, and how they interact, is designed by human experts in a traditional way. We envision an architecture where humans can instead specify a goal and take advantage of technologies such as digital twins to automatically compose the corresponding physical processes, sharing some analogies with the notion of Web service composition.

Enterprise Integration and Interoperability for Big Data-Driven Processes in the Frame of Industry 4.0

“…In this context, a digital twin is the container for integrating information, executing operations, and producing data describing its activity which can be in different formats, from different software tools, and not necessarily deployed in one central repository (Ganz, 2018 ; Catarci et al, 2019 ). Both the physical and the digital twins are equipped with networking devices to guarantee a seamless connection and a continuous data exchange between a generic physical system (or process) and its respective Digital Twin (Platform Industrie 4.0, 2019 ), while they facilitate predictions about future situations and prescriptions about production optimization (Grieves and Vickers, 2017 ; Zillner et al, 2018 ; Barricelli et al, 2019 ).…”

Towards Smart Manufacturing with Dynamic Dataspace Alignment

“…We now summarize the main features of the architecture in [4] and discuss how it can be used for the purpose of agile recovery of smart manufacturing processes.…”

“…Other sources for the data space may include relational and no-SQL databases or unstructured sources which constitute the factory information system. In the approach in [4], the data space can be modelled as a polystore. We inherit the data modelling approach proposed in [9] where a polystore is made of a set of databases stored in a variety of data management systems, each one potentially offered by a twin through the query interface.…”

“…Our Contribution. In this paper we discuss available technologies that can be used to achieve our final goal and describe how a user can leverage the adaptive architecture for smart manufacturing described in [4]. The considered architecture captures indeed analogies between DTs and traditional software services (accessible for instance through Web technologies) and enables automatic integration and composition of DTs through data available in the data space.…”

Towards Digital Twin Implementation for Assessing Production Line Performance and Balancing

“…Knight et al [34] demonstrated how accelerometers mounted on a wearable system may be used to collect data in order to assess human performances in a work environment. Catarci et al [35] provided a detailed literature review about DTs and their modeling techniques. Moreover, they proposed a complex DT architecture for digital factories.…”